open_dropout_risk.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.1"
    },
    "colab": {
      "name": "dropout_risk.ipynb",
      "provenance": []
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "VRfP5Al9gKHK",
        "outputId": "1ab1e903-08e9-4644-b40d-ad1cf62583f5"
      },
      "source": [
        "# Projeto - Detecção de Risco de Evasão Escolar (Versão com 121 atributos)\n",
        "\n",
        "# Autor: José Ahirton Batista Lopes Filho\n",
        "\n",
        "# Bibliotecas utilizadas (9):\n",
        "\n",
        "import numpy as np # biblioteca para nossas operações de álgebra linear\n",
        "import pandas as pd # processamento de dados e leitura/criação de arquivos .CSV (ex. pd.read_csv)\n",
        "import seaborn as sns # construção de nossos plots\n",
        "import matplotlib.ticker as mtick # especificação do formato de nossos eixos \n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.preprocessing import LabelEncoder # encoder para distinção entre nossoa atributos binários e multi-classe\n",
        "from sklearn.preprocessing import MinMaxScaler # pre-processamento para normalização em 0-1\n",
        "import plotly.offline as py # visualização via plotly\n",
        "py.init_notebook_mode(connected=True) # visualização via plotly\n",
        "import plotly.graph_objs as go # visualização via plotly\n",
        "import plotly.graph_objs as go # visualização via plotly\n",
        "import plotly.subplots as tls # visualização via plotly\n",
        "import plotly.figure_factory as ff # visualização via plotly\n",
        "import imblearn\n",
        "from yellowbrick.classifier import DiscriminationThreshold\n",
        "import csv\n",
        "sns.set(style = 'white') # estilização de nossos plots em cor branca"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "text/html": [
              "        <script type=\"text/javascript\">\n",
              "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
              "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
              "        if (typeof require !== 'undefined') {\n",
              "        require.undef(\"plotly\");\n",
              "        requirejs.config({\n",
              "            paths: {\n",
              "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
              "            }\n",
              "        });\n",
              "        require(['plotly'], function(Plotly) {\n",
              "            window._Plotly = Plotly;\n",
              "        });\n",
              "        }\n",
              "        </script>\n",
              "        "
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/home/administrador/anaconda2/envs/py3/lib/python3.8/site-packages/sklearn/utils/deprecation.py:144: FutureWarning:\n",
            "\n",
            "The sklearn.metrics.classification module is  deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.metrics. Anything that cannot be imported from sklearn.metrics is now part of the private API.\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZkOhu8yLgKHM",
        "outputId": "b500ea1c-50db-4777-a52f-0f68333b35b3"
      },
      "source": [
        "# Input de nossos dados via arquivo .CSV, separador ',', tratamento de valores N/A\n",
        "\n",
        "#dropout_df = pd.read_csv(\"dados_evasao/teste_treinamento_2018AllB.csv\", sep=',', na_values=\" \") # dataset treino (100.000 linhas)\n",
        "#dropout_df = pd.read_csv(\"250000_dados_AllBimestres_2018.csv\", sep=',', na_values=\" \") # dataset treino (250.000 linhas)\n",
        "#dropout_df = pd.read_csv(\"teste2_treinamento_2018AllB.csv\", sep=',', na_values=\" \") # dataset treino (500.000 linhas)\n",
        "\n",
        "dropout_df = pd.read_csv(\"dados_evasao/dados_ml_treinamento_2018_4bimestres.csv\", sep=',', na_values=\" \") # dataset treino (+2.500.000 linhas)\n",
        "\n",
        "# Observação de nosso cabeçalho/primeiras 5 linhas, exibição de todas as colunas\n",
        "\n",
        "pd.set_option('display.max_columns', None)\n",
        "dropout_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "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>CD_MATRICULA_ALUNO</th>\n",
              "      <th>CD_ALUNO</th>\n",
              "      <th>Y</th>\n",
              "      <th>CD_TURMA</th>\n",
              "      <th>CD_ESCOLA</th>\n",
              "      <th>TP_SEXO</th>\n",
              "      <th>VL_IDADE</th>\n",
              "      <th>VL_DISTORCAO</th>\n",
              "      <th>CD_TIPO_ENSINO</th>\n",
              "      <th>NR_SERIE</th>\n",
              "      <th>CD_TURNO</th>\n",
              "      <th>VL_IDESP</th>\n",
              "      <th>VL_REPASSE_ALUNO</th>\n",
              "      <th>VL_INSE</th>\n",
              "      <th>QT_ALUNO_ESCOLA</th>\n",
              "      <th>TX_EVASAO</th>\n",
              "      <th>VL_NOTA_LP</th>\n",
              "      <th>VL_NOTA_GEO</th>\n",
              "      <th>VL_NOTA_HIST</th>\n",
              "      <th>VL_NOTA_MAT</th>\n",
              "      <th>VL_NOTA_ING</th>\n",
              "      <th>VL_NOTA_ART</th>\n",
              "      <th>VL_NOTA_EDFIS</th>\n",
              "      <th>VL_NOTA_CIEN</th>\n",
              "      <th>VL_NOTA_LP2</th>\n",
              "      <th>VL_NOTA_GEO2</th>\n",
              "      <th>VL_NOTA_HIST2</th>\n",
              "      <th>VL_NOTA_MAT2</th>\n",
              "      <th>VL_NOTA_ING2</th>\n",
              "      <th>VL_NOTA_ART2</th>\n",
              "      <th>VL_NOTA_EDFIS2</th>\n",
              "      <th>VL_NOTA_CIEN2</th>\n",
              "      <th>VL_NOTA_LP3</th>\n",
              "      <th>VL_NOTA_GEO3</th>\n",
              "      <th>VL_NOTA_HIST3</th>\n",
              "      <th>VL_NOTA_MAT3</th>\n",
              "      <th>VL_NOTA_ING3</th>\n",
              "      <th>VL_NOTA_ART3</th>\n",
              "      <th>VL_NOTA_EDFIS3</th>\n",
              "      <th>VL_NOTA_CIEN3</th>\n",
              "      <th>VL_NOTA_LP4</th>\n",
              "      <th>VL_NOTA_GEO4</th>\n",
              "      <th>VL_NOTA_HIST4</th>\n",
              "      <th>VL_NOTA_MAT4</th>\n",
              "      <th>VL_NOTA_ING4</th>\n",
              "      <th>VL_NOTA_ART4</th>\n",
              "      <th>VL_NOTA_EDFIS4</th>\n",
              "      <th>VL_NOTA_CIEN4</th>\n",
              "      <th>TX_FREQ_LP</th>\n",
              "      <th>TX_FREQ_GEO</th>\n",
              "      <th>TX_FREQ_HIST</th>\n",
              "      <th>TX_FREQ_MAT</th>\n",
              "      <th>TX_FREQ_ING</th>\n",
              "      <th>TX_FREQ_ART</th>\n",
              "      <th>TX_FREQ_EDFIS</th>\n",
              "      <th>TX_FREQ_CIEN</th>\n",
              "      <th>TX_FREQ_LP2</th>\n",
              "      <th>TX_FREQ_GEO2</th>\n",
              "      <th>TX_FREQ_HIST2</th>\n",
              "      <th>TX_FREQ_MAT2</th>\n",
              "      <th>TX_FREQ_ING2</th>\n",
              "      <th>TX_FREQ_ART2</th>\n",
              "      <th>TX_FREQ_EDFIS2</th>\n",
              "      <th>TX_FREQ_CIEN2</th>\n",
              "      <th>TX_FREQ_LP3</th>\n",
              "      <th>TX_FREQ_GEO3</th>\n",
              "      <th>TX_FREQ_HIST3</th>\n",
              "      <th>TX_FREQ_MAT3</th>\n",
              "      <th>TX_FREQ_ING3</th>\n",
              "      <th>TX_FREQ_ART3</th>\n",
              "      <th>TX_FREQ_EDFIS3</th>\n",
              "      <th>TX_FREQ_CIEN3</th>\n",
              "      <th>TX_FREQ_LP4</th>\n",
              "      <th>TX_FREQ_GEO4</th>\n",
              "      <th>TX_FREQ_HIST4</th>\n",
              "      <th>TX_FREQ_MAT4</th>\n",
              "      <th>TX_FREQ_ING4</th>\n",
              "      <th>TX_FREQ_ART4</th>\n",
              "      <th>TX_FREQ_EDFIS4</th>\n",
              "      <th>TX_FREQ_CIEN4</th>\n",
              "      <th>ESC_Código_de_situação_do_setor_censitário</th>\n",
              "      <th>ESC_Setor_é_Aglomerado_subnormal_</th>\n",
              "      <th>ESC_Grupo_do_IPVS</th>\n",
              "      <th>ESC_Domicílios_particulares_e_coletivos</th>\n",
              "      <th>ESC_Média_de_moradores_em_domicílios_particulares_permanentes</th>\n",
              "      <th>ESC_Proporção_de_crianças_de_0_a_5_anos_na_população</th>\n",
              "      <th>ESC_Rendimento_médio_domiciliar_dos_domicílios</th>\n",
              "      <th>ESC_Renda_per_capita_nos_domicílios</th>\n",
              "      <th>ESC_Proporção_de_Domicílios_sem_Renda_per_Capita</th>\n",
              "      <th>ESC_Idade_média_das_pessoas_responsáveis</th>\n",
              "      <th>ESC_Rendimento_médio_do_responsável_pelo_domicílio</th>\n",
              "      <th>ESC_Proporção_de_pessoas_responsáveis_alfabetizadas</th>\n",
              "      <th>ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos</th>\n",
              "      <th>ESC_Participação_da_renda_do_responsável</th>\n",
              "      <th>ESC_Idade_média_mulheres_respon_pelo_domicílio</th>\n",
              "      <th>ESC_Prop_mulheres_respon_domicílio_alfabet</th>\n",
              "      <th>ESC_Prop_mulheres_respon_domicílio_menos_30_anos</th>\n",
              "      <th>ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio</th>\n",
              "      <th>ESC_Prop_abastecimento_de_água</th>\n",
              "      <th>ESC_Prop_banheiro</th>\n",
              "      <th>ESC_Prop_domicílios_pp_lixo_coletado</th>\n",
              "      <th>ESC_Prop_domicílios_pp_energia_elétrica</th>\n",
              "      <th>ESC_Pop_total_residente_Mun</th>\n",
              "      <th>AL_Código_de_situação_do_setor_censitário</th>\n",
              "      <th>AL_Setor_é_Aglomerado_subnormal_</th>\n",
              "      <th>AL_Grupo_do_IPVS</th>\n",
              "      <th>AL_Domicílios_particulares_e_coletivos</th>\n",
              "      <th>AL_Média_de_moradores_em_domicílios_particulares_permanentes</th>\n",
              "      <th>AL_Proporção_de_crianças_de_0_a_5_anos_na_população</th>\n",
              "      <th>AL_Rendimento_médio_domiciliar_dos_domicílios</th>\n",
              "      <th>AL_Renda_per_capita_nos_domicílios</th>\n",
              "      <th>AL_Proporção_de_Domicílios_sem_Renda_per_Capita</th>\n",
              "      <th>AL_Idade_média_das_pessoas_responsáveis</th>\n",
              "      <th>AL_Rendimento_médio_do_responsável_pelo_domicílio</th>\n",
              "      <th>AL_Proporção_de_pessoas_responsáveis_alfabetizadas</th>\n",
              "      <th>AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos</th>\n",
              "      <th>AL_Participação_da_renda_do_responsável</th>\n",
              "      <th>AL_Idade_média_mulheres_respon_pelo_domicílio</th>\n",
              "      <th>AL_Prop_mulheres_respon_domicílio_alfabet</th>\n",
              "      <th>AL_Prop_mulheres_respon_domicílio_menos_30_anos</th>\n",
              "      <th>AL_Rend_médio_mulheres_responsáveis_pelo_domicílio</th>\n",
              "      <th>AL_Prop_abastecimento_de_água</th>\n",
              "      <th>AL_Prop_banheiro</th>\n",
              "      <th>AL_Prop_domicílios_pp_lixo_coletado</th>\n",
              "      <th>AL_Prop_domicílios_pp_energia_elétrica</th>\n",
              "      <th>AL_Pop_total_residente_Mun</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>900006532477</td>\n",
              "      <td>25340195</td>\n",
              "      <td>0</td>\n",
              "      <td>35499250</td>\n",
              "      <td>17735</td>\n",
              "      <td>F</td>\n",
              "      <td>14.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>14</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>3.14</td>\n",
              "      <td>33.7304</td>\n",
              "      <td>5.22</td>\n",
              "      <td>1092</td>\n",
              "      <td>0.0440</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>89.0</td>\n",
              "      <td>3.17</td>\n",
              "      <td>5.673759</td>\n",
              "      <td>3814.752809</td>\n",
              "      <td>1203.946809</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>49.696629</td>\n",
              "      <td>2405.000000</td>\n",
              "      <td>98.876404</td>\n",
              "      <td>3.370787</td>\n",
              "      <td>63.044714</td>\n",
              "      <td>49.380952</td>\n",
              "      <td>95.238095</td>\n",
              "      <td>14.285714</td>\n",
              "      <td>1516.666667</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>36686.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>N</td>\n",
              "      <td>4.0</td>\n",
              "      <td>263.0</td>\n",
              "      <td>3.07</td>\n",
              "      <td>7.673267</td>\n",
              "      <td>1567.311787</td>\n",
              "      <td>510.152228</td>\n",
              "      <td>0.380228</td>\n",
              "      <td>47.437262</td>\n",
              "      <td>816.015209</td>\n",
              "      <td>93.155894</td>\n",
              "      <td>12.547529</td>\n",
              "      <td>52.064638</td>\n",
              "      <td>45.604396</td>\n",
              "      <td>94.505495</td>\n",
              "      <td>15.384615</td>\n",
              "      <td>578.527472</td>\n",
              "      <td>97.338403</td>\n",
              "      <td>98.859316</td>\n",
              "      <td>97.718631</td>\n",
              "      <td>100.0</td>\n",
              "      <td>17266.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>900007800631</td>\n",
              "      <td>28127559</td>\n",
              "      <td>0</td>\n",
              "      <td>35768828</td>\n",
              "      <td>20357</td>\n",
              "      <td>M</td>\n",
              "      <td>12.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "      <td>4.17</td>\n",
              "      <td>39.7149</td>\n",
              "      <td>2.35</td>\n",
              "      <td>1221</td>\n",
              "      <td>0.0385</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.8214</td>\n",
              "      <td>0.9524</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.8621</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8421</td>\n",
              "      <td>0.8929</td>\n",
              "      <td>0.9444</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8947</td>\n",
              "      <td>0.9259</td>\n",
              "      <td>0.9474</td>\n",
              "      <td>0.9474</td>\n",
              "      <td>0.9630</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.9286</td>\n",
              "      <td>0.9545</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9091</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.7895</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>1.0</td>\n",
              "      <td>176.0</td>\n",
              "      <td>2.59</td>\n",
              "      <td>2.197802</td>\n",
              "      <td>6775.170455</td>\n",
              "      <td>2620.725275</td>\n",
              "      <td>0.568182</td>\n",
              "      <td>58.312500</td>\n",
              "      <td>5577.102273</td>\n",
              "      <td>99.431818</td>\n",
              "      <td>5.113636</td>\n",
              "      <td>82.316782</td>\n",
              "      <td>63.258427</td>\n",
              "      <td>98.876404</td>\n",
              "      <td>6.741573</td>\n",
              "      <td>8402.943820</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>41907.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>186.0</td>\n",
              "      <td>3.15</td>\n",
              "      <td>6.153846</td>\n",
              "      <td>2949.784946</td>\n",
              "      <td>937.880342</td>\n",
              "      <td>1.075269</td>\n",
              "      <td>56.016129</td>\n",
              "      <td>1752.752688</td>\n",
              "      <td>94.623656</td>\n",
              "      <td>4.838710</td>\n",
              "      <td>59.419677</td>\n",
              "      <td>58.760563</td>\n",
              "      <td>90.140845</td>\n",
              "      <td>8.450704</td>\n",
              "      <td>1238.521127</td>\n",
              "      <td>93.548387</td>\n",
              "      <td>99.462366</td>\n",
              "      <td>99.462366</td>\n",
              "      <td>100.0</td>\n",
              "      <td>41907.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>900000040498</td>\n",
              "      <td>23470924</td>\n",
              "      <td>0</td>\n",
              "      <td>35567174</td>\n",
              "      <td>36687</td>\n",
              "      <td>F</td>\n",
              "      <td>15.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14</td>\n",
              "      <td>9</td>\n",
              "      <td>3</td>\n",
              "      <td>2.42</td>\n",
              "      <td>24.4031</td>\n",
              "      <td>5.24</td>\n",
              "      <td>1116</td>\n",
              "      <td>0.0645</td>\n",
              "      <td>5.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>0.9143</td>\n",
              "      <td>0.8810</td>\n",
              "      <td>0.7313</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5909</td>\n",
              "      <td>0.9375</td>\n",
              "      <td>0.6667</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.5714</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>0.8667</td>\n",
              "      <td>0.8235</td>\n",
              "      <td>0.7500</td>\n",
              "      <td>0.7576</td>\n",
              "      <td>0.7755</td>\n",
              "      <td>0.8571</td>\n",
              "      <td>0.3750</td>\n",
              "      <td>0.7885</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.8750</td>\n",
              "      <td>0.9118</td>\n",
              "      <td>0.6818</td>\n",
              "      <td>0.6875</td>\n",
              "      <td>0.6842</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.7273</td>\n",
              "      <td>0.9565</td>\n",
              "      <td>0.7045</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>4.0</td>\n",
              "      <td>186.0</td>\n",
              "      <td>3.17</td>\n",
              "      <td>8.319185</td>\n",
              "      <td>1856.000000</td>\n",
              "      <td>586.105263</td>\n",
              "      <td>0.537634</td>\n",
              "      <td>48.112903</td>\n",
              "      <td>1131.784946</td>\n",
              "      <td>96.236559</td>\n",
              "      <td>11.827957</td>\n",
              "      <td>60.979792</td>\n",
              "      <td>48.318841</td>\n",
              "      <td>94.202899</td>\n",
              "      <td>11.594203</td>\n",
              "      <td>728.884058</td>\n",
              "      <td>100.0</td>\n",
              "      <td>97.849462</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>1221979.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>4.0</td>\n",
              "      <td>77.0</td>\n",
              "      <td>3.34</td>\n",
              "      <td>7.003891</td>\n",
              "      <td>1608.532468</td>\n",
              "      <td>481.933852</td>\n",
              "      <td>2.597403</td>\n",
              "      <td>44.467532</td>\n",
              "      <td>769.441558</td>\n",
              "      <td>93.506494</td>\n",
              "      <td>15.584416</td>\n",
              "      <td>47.835003</td>\n",
              "      <td>44.217391</td>\n",
              "      <td>91.304348</td>\n",
              "      <td>13.043478</td>\n",
              "      <td>511.847826</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>1221979.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>900009201305</td>\n",
              "      <td>23690042</td>\n",
              "      <td>0</td>\n",
              "      <td>35268391</td>\n",
              "      <td>16433</td>\n",
              "      <td>M</td>\n",
              "      <td>12.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "      <td>4.35</td>\n",
              "      <td>32.6051</td>\n",
              "      <td>1.83</td>\n",
              "      <td>1897</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.9718</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8571</td>\n",
              "      <td>0.9701</td>\n",
              "      <td>0.9524</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9583</td>\n",
              "      <td>0.9592</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9375</td>\n",
              "      <td>0.9744</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8750</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.9583</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.8667</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.8824</td>\n",
              "      <td>0.9697</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.9825</td>\n",
              "      <td>0.9130</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9500</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>2.33</td>\n",
              "      <td>3.267974</td>\n",
              "      <td>5504.192893</td>\n",
              "      <td>2362.366013</td>\n",
              "      <td>3.045685</td>\n",
              "      <td>60.406091</td>\n",
              "      <td>3624.081218</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>3.553299</td>\n",
              "      <td>65.842191</td>\n",
              "      <td>62.023077</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>1.538462</td>\n",
              "      <td>2891.076923</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>586625.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>209.0</td>\n",
              "      <td>3.20</td>\n",
              "      <td>5.829596</td>\n",
              "      <td>3336.818182</td>\n",
              "      <td>1042.443946</td>\n",
              "      <td>1.435407</td>\n",
              "      <td>48.995215</td>\n",
              "      <td>1939.569378</td>\n",
              "      <td>97.607656</td>\n",
              "      <td>11.004785</td>\n",
              "      <td>58.126313</td>\n",
              "      <td>52.276923</td>\n",
              "      <td>93.846154</td>\n",
              "      <td>13.846154</td>\n",
              "      <td>1351.384615</td>\n",
              "      <td>93.301435</td>\n",
              "      <td>96.172249</td>\n",
              "      <td>99.043062</td>\n",
              "      <td>100.0</td>\n",
              "      <td>78821.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>900000098705</td>\n",
              "      <td>27752606</td>\n",
              "      <td>0</td>\n",
              "      <td>35376701</td>\n",
              "      <td>39810</td>\n",
              "      <td>F</td>\n",
              "      <td>14.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>14</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>3.60</td>\n",
              "      <td>50.1011</td>\n",
              "      <td>3.18</td>\n",
              "      <td>592</td>\n",
              "      <td>0.0017</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.9344</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8966</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9677</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9545</td>\n",
              "      <td>0.8846</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.9459</td>\n",
              "      <td>0.9200</td>\n",
              "      <td>0.9048</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9375</td>\n",
              "      <td>0.9322</td>\n",
              "      <td>0.9231</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9130</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>354.0</td>\n",
              "      <td>3.02</td>\n",
              "      <td>6.378987</td>\n",
              "      <td>2416.283286</td>\n",
              "      <td>800.138837</td>\n",
              "      <td>1.694915</td>\n",
              "      <td>47.954802</td>\n",
              "      <td>1400.566572</td>\n",
              "      <td>96.327684</td>\n",
              "      <td>14.971751</td>\n",
              "      <td>57.963674</td>\n",
              "      <td>48.522936</td>\n",
              "      <td>93.577982</td>\n",
              "      <td>16.513761</td>\n",
              "      <td>878.568807</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>51242.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>306.0</td>\n",
              "      <td>2.94</td>\n",
              "      <td>7.119021</td>\n",
              "      <td>2522.130719</td>\n",
              "      <td>858.478309</td>\n",
              "      <td>1.307190</td>\n",
              "      <td>48.300654</td>\n",
              "      <td>1422.614379</td>\n",
              "      <td>96.078431</td>\n",
              "      <td>16.666667</td>\n",
              "      <td>56.405260</td>\n",
              "      <td>48.654412</td>\n",
              "      <td>93.382353</td>\n",
              "      <td>16.911765</td>\n",
              "      <td>782.448529</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>99.346405</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>51242.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   CD_MATRICULA_ALUNO  CD_ALUNO  Y  CD_TURMA  CD_ESCOLA TP_SEXO  VL_IDADE  \\\n",
              "0        900006532477  25340195  0  35499250      17735       F      14.0   \n",
              "1        900007800631  28127559  0  35768828      20357       M      12.0   \n",
              "2        900000040498  23470924  0  35567174      36687       F      15.0   \n",
              "3        900009201305  23690042  0  35268391      16433       M      12.0   \n",
              "4        900000098705  27752606  0  35376701      39810       F      14.0   \n",
              "\n",
              "   VL_DISTORCAO  CD_TIPO_ENSINO  NR_SERIE  CD_TURNO  VL_IDESP  \\\n",
              "0           2.0              14         7         3      3.14   \n",
              "1           1.0              14         6         3      4.17   \n",
              "2           1.0              14         9         3      2.42   \n",
              "3           1.0              14         6         3      4.35   \n",
              "4           2.0              14         7         3      3.60   \n",
              "\n",
              "   VL_REPASSE_ALUNO  VL_INSE  QT_ALUNO_ESCOLA  TX_EVASAO  VL_NOTA_LP  \\\n",
              "0           33.7304     5.22             1092     0.0440         NaN   \n",
              "1           39.7149     2.35             1221     0.0385         3.0   \n",
              "2           24.4031     5.24             1116     0.0645         5.0   \n",
              "3           32.6051     1.83             1897     0.0148         7.0   \n",
              "4           50.1011     3.18              592     0.0017         9.0   \n",
              "\n",
              "   VL_NOTA_GEO  VL_NOTA_HIST  VL_NOTA_MAT  VL_NOTA_ING  VL_NOTA_ART  \\\n",
              "0          NaN           NaN          NaN          NaN          NaN   \n",
              "1          5.0           3.0          1.0          7.0          5.0   \n",
              "2         10.0           5.0          3.0          4.0          7.0   \n",
              "3          8.0          10.0         10.0          6.0          8.0   \n",
              "4         10.0          10.0          6.0          9.0          9.0   \n",
              "\n",
              "   VL_NOTA_EDFIS  VL_NOTA_CIEN  VL_NOTA_LP2  VL_NOTA_GEO2  VL_NOTA_HIST2  \\\n",
              "0            NaN           NaN          NaN           NaN            NaN   \n",
              "1            7.0           1.0          4.0           5.0            5.0   \n",
              "2            4.0           7.0          3.0          10.0            3.0   \n",
              "3            8.0           6.0          7.0          10.0            7.0   \n",
              "4           10.0           7.0          9.0          10.0           10.0   \n",
              "\n",
              "   VL_NOTA_MAT2  VL_NOTA_ING2  VL_NOTA_ART2  VL_NOTA_EDFIS2  VL_NOTA_CIEN2  \\\n",
              "0           NaN           NaN           NaN             NaN            NaN   \n",
              "1           2.0           3.0           5.0             2.0            2.0   \n",
              "2           7.0           6.0           7.0             8.0           10.0   \n",
              "3           5.0           8.0           9.0             4.0            7.0   \n",
              "4           7.0          10.0           9.0             9.0            8.0   \n",
              "\n",
              "   VL_NOTA_LP3  VL_NOTA_GEO3  VL_NOTA_HIST3  VL_NOTA_MAT3  VL_NOTA_ING3  \\\n",
              "0          NaN           NaN            NaN           NaN           NaN   \n",
              "1          4.0           5.0            6.0           2.0           6.0   \n",
              "2          5.0           8.0            2.0           5.0           6.0   \n",
              "3          6.0           8.0            6.0           4.0           8.0   \n",
              "4         10.0           7.0           10.0           7.0          10.0   \n",
              "\n",
              "   VL_NOTA_ART3  VL_NOTA_EDFIS3  VL_NOTA_CIEN3  VL_NOTA_LP4  VL_NOTA_GEO4  \\\n",
              "0           NaN             NaN            NaN          NaN           NaN   \n",
              "1           6.0             2.0            6.0          4.0           5.0   \n",
              "2           8.0             7.0            9.0          6.0           8.0   \n",
              "3           6.0             4.0            7.0          6.0           9.0   \n",
              "4           9.0             9.0            8.0          7.0           9.0   \n",
              "\n",
              "   VL_NOTA_HIST4  VL_NOTA_MAT4  VL_NOTA_ING4  VL_NOTA_ART4  VL_NOTA_EDFIS4  \\\n",
              "0            NaN           NaN           NaN           NaN             NaN   \n",
              "1            7.0           1.0           3.0           5.0             5.0   \n",
              "2            4.0           6.0           6.0           6.0             7.0   \n",
              "3            6.0           5.0           7.0           8.0             9.0   \n",
              "4           10.0           8.0           9.0          10.0             9.0   \n",
              "\n",
              "   VL_NOTA_CIEN4  TX_FREQ_LP  TX_FREQ_GEO  TX_FREQ_HIST  TX_FREQ_MAT  \\\n",
              "0            NaN         NaN       1.0000        1.0000          NaN   \n",
              "1            4.0      0.8214       0.9524        0.8333       0.8621   \n",
              "2            6.0      0.7015       0.9143        0.8810       0.7313   \n",
              "3            7.0      0.9718       1.0000        0.8571       0.9701   \n",
              "4            8.0      0.9344       1.0000        1.0000       1.0000   \n",
              "\n",
              "   TX_FREQ_ING  TX_FREQ_ART  TX_FREQ_EDFIS  TX_FREQ_CIEN  TX_FREQ_LP2  \\\n",
              "0          NaN          1.0            NaN           NaN       1.0000   \n",
              "1       1.0000          0.9         1.0000        0.8421       0.8929   \n",
              "2       0.8800          1.0         0.5909        0.9375       0.6667   \n",
              "3       0.9524          1.0         1.0000        0.9583       0.9592   \n",
              "4       1.0000          1.0         1.0000        1.0000       0.8966   \n",
              "\n",
              "   TX_FREQ_GEO2  TX_FREQ_HIST2  TX_FREQ_MAT2  TX_FREQ_ING2  TX_FREQ_ART2  \\\n",
              "0        1.0000         1.0000        1.0000        1.0000        1.0000   \n",
              "1        0.9444         1.0000        0.8889        0.8000        1.0000   \n",
              "2        0.8333         0.5714        0.8800        0.8667        0.8235   \n",
              "3        1.0000         0.9375        0.9744        1.0000        0.8750   \n",
              "4        1.0000         1.0000        0.9677        1.0000        1.0000   \n",
              "\n",
              "   TX_FREQ_EDFIS2  TX_FREQ_CIEN2  TX_FREQ_LP3  TX_FREQ_GEO3  TX_FREQ_HIST3  \\\n",
              "0          1.0000         1.0000       1.0000           NaN         1.0000   \n",
              "1          0.8000         0.8947       0.9259        0.9474         0.9474   \n",
              "2          0.7500         0.7576       0.7755        0.8571         0.3750   \n",
              "3          0.9167         0.9412       0.9583           NaN         1.0000   \n",
              "4          1.0000         0.9545       0.8846           NaN         0.9459   \n",
              "\n",
              "   TX_FREQ_MAT3  TX_FREQ_ING3  TX_FREQ_ART3  TX_FREQ_EDFIS3  TX_FREQ_CIEN3  \\\n",
              "0        1.0000           NaN           NaN          1.0000            NaN   \n",
              "1        0.9630           NaN        0.9000          1.0000            NaN   \n",
              "2        0.7885           NaN        0.8333          0.8750         0.9118   \n",
              "3        0.9167        0.9412        0.8667          0.9412         0.8824   \n",
              "4        0.9200        0.9048           NaN          1.0000         0.9375   \n",
              "\n",
              "   TX_FREQ_LP4  TX_FREQ_GEO4  TX_FREQ_HIST4  TX_FREQ_MAT4  TX_FREQ_ING4  \\\n",
              "0       1.0000        1.0000            NaN        1.0000        1.0000   \n",
              "1       0.9286        0.9545            NaN        0.8800        1.0000   \n",
              "2       0.6818        0.6875         0.6842        1.0000        0.9412   \n",
              "3       0.9697        1.0000            NaN        0.9825        0.9130   \n",
              "4       0.9322        0.9231            NaN        1.0000        0.9130   \n",
              "\n",
              "   TX_FREQ_ART4  TX_FREQ_EDFIS4  TX_FREQ_CIEN4  \\\n",
              "0        1.0000          1.0000         1.0000   \n",
              "1        0.9091          1.0000         0.7895   \n",
              "2        0.7273          0.9565         0.7045   \n",
              "3        1.0000          0.9500         1.0000   \n",
              "4        1.0000          1.0000         1.0000   \n",
              "\n",
              "   ESC_Código_de_situação_do_setor_censitário  \\\n",
              "0                                         1.0   \n",
              "1                                         1.0   \n",
              "2                                         1.0   \n",
              "3                                         1.0   \n",
              "4                                         1.0   \n",
              "\n",
              "  ESC_Setor_é_Aglomerado_subnormal_  ESC_Grupo_do_IPVS  \\\n",
              "0                                 N                2.0   \n",
              "1                                 N                1.0   \n",
              "2                                 N                4.0   \n",
              "3                                 N                2.0   \n",
              "4                                 N                2.0   \n",
              "\n",
              "   ESC_Domicílios_particulares_e_coletivos  \\\n",
              "0                                     89.0   \n",
              "1                                    176.0   \n",
              "2                                    186.0   \n",
              "3                                    197.0   \n",
              "4                                    354.0   \n",
              "\n",
              "   ESC_Média_de_moradores_em_domicílios_particulares_permanentes  \\\n",
              "0                                               3.17               \n",
              "1                                               2.59               \n",
              "2                                               3.17               \n",
              "3                                               2.33               \n",
              "4                                               3.02               \n",
              "\n",
              "   ESC_Proporção_de_crianças_de_0_a_5_anos_na_população  \\\n",
              "0                                           5.673759      \n",
              "1                                           2.197802      \n",
              "2                                           8.319185      \n",
              "3                                           3.267974      \n",
              "4                                           6.378987      \n",
              "\n",
              "   ESC_Rendimento_médio_domiciliar_dos_domicílios  \\\n",
              "0                                     3814.752809   \n",
              "1                                     6775.170455   \n",
              "2                                     1856.000000   \n",
              "3                                     5504.192893   \n",
              "4                                     2416.283286   \n",
              "\n",
              "   ESC_Renda_per_capita_nos_domicílios  \\\n",
              "0                          1203.946809   \n",
              "1                          2620.725275   \n",
              "2                           586.105263   \n",
              "3                          2362.366013   \n",
              "4                           800.138837   \n",
              "\n",
              "   ESC_Proporção_de_Domicílios_sem_Renda_per_Capita  \\\n",
              "0                                          0.000000   \n",
              "1                                          0.568182   \n",
              "2                                          0.537634   \n",
              "3                                          3.045685   \n",
              "4                                          1.694915   \n",
              "\n",
              "   ESC_Idade_média_das_pessoas_responsáveis  \\\n",
              "0                                 49.696629   \n",
              "1                                 58.312500   \n",
              "2                                 48.112903   \n",
              "3                                 60.406091   \n",
              "4                                 47.954802   \n",
              "\n",
              "   ESC_Rendimento_médio_do_responsável_pelo_domicílio  \\\n",
              "0                                        2405.000000    \n",
              "1                                        5577.102273    \n",
              "2                                        1131.784946    \n",
              "3                                        3624.081218    \n",
              "4                                        1400.566572    \n",
              "\n",
              "   ESC_Proporção_de_pessoas_responsáveis_alfabetizadas  \\\n",
              "0                                          98.876404     \n",
              "1                                          99.431818     \n",
              "2                                          96.236559     \n",
              "3                                         100.000000     \n",
              "4                                          96.327684     \n",
              "\n",
              "   ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos  \\\n",
              "0                                           3.370787       \n",
              "1                                           5.113636       \n",
              "2                                          11.827957       \n",
              "3                                           3.553299       \n",
              "4                                          14.971751       \n",
              "\n",
              "   ESC_Participação_da_renda_do_responsável  \\\n",
              "0                                 63.044714   \n",
              "1                                 82.316782   \n",
              "2                                 60.979792   \n",
              "3                                 65.842191   \n",
              "4                                 57.963674   \n",
              "\n",
              "   ESC_Idade_média_mulheres_respon_pelo_domicílio  \\\n",
              "0                                       49.380952   \n",
              "1                                       63.258427   \n",
              "2                                       48.318841   \n",
              "3                                       62.023077   \n",
              "4                                       48.522936   \n",
              "\n",
              "   ESC_Prop_mulheres_respon_domicílio_alfabet  \\\n",
              "0                                   95.238095   \n",
              "1                                   98.876404   \n",
              "2                                   94.202899   \n",
              "3                                  100.000000   \n",
              "4                                   93.577982   \n",
              "\n",
              "   ESC_Prop_mulheres_respon_domicílio_menos_30_anos  \\\n",
              "0                                         14.285714   \n",
              "1                                          6.741573   \n",
              "2                                         11.594203   \n",
              "3                                          1.538462   \n",
              "4                                         16.513761   \n",
              "\n",
              "   ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio  \\\n",
              "0                                        1516.666667     \n",
              "1                                        8402.943820     \n",
              "2                                         728.884058     \n",
              "3                                        2891.076923     \n",
              "4                                         878.568807     \n",
              "\n",
              "   ESC_Prop_abastecimento_de_água  ESC_Prop_banheiro  \\\n",
              "0                           100.0         100.000000   \n",
              "1                           100.0         100.000000   \n",
              "2                           100.0          97.849462   \n",
              "3                           100.0         100.000000   \n",
              "4                           100.0         100.000000   \n",
              "\n",
              "   ESC_Prop_domicílios_pp_lixo_coletado  \\\n",
              "0                                 100.0   \n",
              "1                                 100.0   \n",
              "2                                 100.0   \n",
              "3                                 100.0   \n",
              "4                                 100.0   \n",
              "\n",
              "   ESC_Prop_domicílios_pp_energia_elétrica  ESC_Pop_total_residente_Mun  \\\n",
              "0                                    100.0                      36686.0   \n",
              "1                                    100.0                      41907.0   \n",
              "2                                    100.0                    1221979.0   \n",
              "3                                    100.0                     586625.0   \n",
              "4                                    100.0                      51242.0   \n",
              "\n",
              "   AL_Código_de_situação_do_setor_censitário AL_Setor_é_Aglomerado_subnormal_  \\\n",
              "0                                        2.0                                N   \n",
              "1                                        1.0                                N   \n",
              "2                                        1.0                                N   \n",
              "3                                        1.0                                N   \n",
              "4                                        1.0                                N   \n",
              "\n",
              "   AL_Grupo_do_IPVS  AL_Domicílios_particulares_e_coletivos  \\\n",
              "0               4.0                                   263.0   \n",
              "1               2.0                                   186.0   \n",
              "2               4.0                                    77.0   \n",
              "3               2.0                                   209.0   \n",
              "4               2.0                                   306.0   \n",
              "\n",
              "   AL_Média_de_moradores_em_domicílios_particulares_permanentes  \\\n",
              "0                                               3.07              \n",
              "1                                               3.15              \n",
              "2                                               3.34              \n",
              "3                                               3.20              \n",
              "4                                               2.94              \n",
              "\n",
              "   AL_Proporção_de_crianças_de_0_a_5_anos_na_população  \\\n",
              "0                                           7.673267     \n",
              "1                                           6.153846     \n",
              "2                                           7.003891     \n",
              "3                                           5.829596     \n",
              "4                                           7.119021     \n",
              "\n",
              "   AL_Rendimento_médio_domiciliar_dos_domicílios  \\\n",
              "0                                    1567.311787   \n",
              "1                                    2949.784946   \n",
              "2                                    1608.532468   \n",
              "3                                    3336.818182   \n",
              "4                                    2522.130719   \n",
              "\n",
              "   AL_Renda_per_capita_nos_domicílios  \\\n",
              "0                          510.152228   \n",
              "1                          937.880342   \n",
              "2                          481.933852   \n",
              "3                         1042.443946   \n",
              "4                          858.478309   \n",
              "\n",
              "   AL_Proporção_de_Domicílios_sem_Renda_per_Capita  \\\n",
              "0                                         0.380228   \n",
              "1                                         1.075269   \n",
              "2                                         2.597403   \n",
              "3                                         1.435407   \n",
              "4                                         1.307190   \n",
              "\n",
              "   AL_Idade_média_das_pessoas_responsáveis  \\\n",
              "0                                47.437262   \n",
              "1                                56.016129   \n",
              "2                                44.467532   \n",
              "3                                48.995215   \n",
              "4                                48.300654   \n",
              "\n",
              "   AL_Rendimento_médio_do_responsável_pelo_domicílio  \\\n",
              "0                                         816.015209   \n",
              "1                                        1752.752688   \n",
              "2                                         769.441558   \n",
              "3                                        1939.569378   \n",
              "4                                        1422.614379   \n",
              "\n",
              "   AL_Proporção_de_pessoas_responsáveis_alfabetizadas  \\\n",
              "0                                          93.155894    \n",
              "1                                          94.623656    \n",
              "2                                          93.506494    \n",
              "3                                          97.607656    \n",
              "4                                          96.078431    \n",
              "\n",
              "   AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos  \\\n",
              "0                                          12.547529      \n",
              "1                                           4.838710      \n",
              "2                                          15.584416      \n",
              "3                                          11.004785      \n",
              "4                                          16.666667      \n",
              "\n",
              "   AL_Participação_da_renda_do_responsável  \\\n",
              "0                                52.064638   \n",
              "1                                59.419677   \n",
              "2                                47.835003   \n",
              "3                                58.126313   \n",
              "4                                56.405260   \n",
              "\n",
              "   AL_Idade_média_mulheres_respon_pelo_domicílio  \\\n",
              "0                                      45.604396   \n",
              "1                                      58.760563   \n",
              "2                                      44.217391   \n",
              "3                                      52.276923   \n",
              "4                                      48.654412   \n",
              "\n",
              "   AL_Prop_mulheres_respon_domicílio_alfabet  \\\n",
              "0                                  94.505495   \n",
              "1                                  90.140845   \n",
              "2                                  91.304348   \n",
              "3                                  93.846154   \n",
              "4                                  93.382353   \n",
              "\n",
              "   AL_Prop_mulheres_respon_domicílio_menos_30_anos  \\\n",
              "0                                        15.384615   \n",
              "1                                         8.450704   \n",
              "2                                        13.043478   \n",
              "3                                        13.846154   \n",
              "4                                        16.911765   \n",
              "\n",
              "   AL_Rend_médio_mulheres_responsáveis_pelo_domicílio  \\\n",
              "0                                         578.527472    \n",
              "1                                        1238.521127    \n",
              "2                                         511.847826    \n",
              "3                                        1351.384615    \n",
              "4                                         782.448529    \n",
              "\n",
              "   AL_Prop_abastecimento_de_água  AL_Prop_banheiro  \\\n",
              "0                      97.338403         98.859316   \n",
              "1                      93.548387         99.462366   \n",
              "2                     100.000000        100.000000   \n",
              "3                      93.301435         96.172249   \n",
              "4                     100.000000         99.346405   \n",
              "\n",
              "   AL_Prop_domicílios_pp_lixo_coletado  \\\n",
              "0                            97.718631   \n",
              "1                            99.462366   \n",
              "2                           100.000000   \n",
              "3                            99.043062   \n",
              "4                           100.000000   \n",
              "\n",
              "   AL_Prop_domicílios_pp_energia_elétrica  AL_Pop_total_residente_Mun  \n",
              "0                                   100.0                     17266.0  \n",
              "1                                   100.0                     41907.0  \n",
              "2                                   100.0                   1221979.0  \n",
              "3                                   100.0                     78821.0  \n",
              "4                                   100.0                     51242.0  "
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KqLvypnUgKHN",
        "outputId": "faf4155f-af92-481a-b16d-c006676fefb1"
      },
      "source": [
        "# Pré-processamento/limpeza de nossos dados (se houver - usando a moda Ref. https://pt.wikipedia.org/wiki/Moda_(estat%C3%ADstica))\n",
        "\n",
        "dropout_df.fillna(dropout_df.mode(), inplace=True)\n",
        "\n",
        "# \"Dropando\" CD_MATRICULA_ALUNO, CD_TURMA e CD_ESCOLA\n",
        "\n",
        "dropout_df.drop(['CD_MATRICULA_ALUNO'],axis=1,inplace=True)\n",
        "dropout_df.drop(['CD_TURMA'],axis=1,inplace=True)\n",
        "dropout_df.drop(['CD_ESCOLA'],axis=1,inplace=True)\n",
        "\n",
        "# Observação de nosso cabeçalho/primeiras 5 linhas, exibição de todas as colunas\n",
        "\n",
        "pd.set_option('display.max_columns', None)\n",
        "dropout_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "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>CD_ALUNO</th>\n",
              "      <th>Y</th>\n",
              "      <th>TP_SEXO</th>\n",
              "      <th>VL_IDADE</th>\n",
              "      <th>VL_DISTORCAO</th>\n",
              "      <th>CD_TIPO_ENSINO</th>\n",
              "      <th>NR_SERIE</th>\n",
              "      <th>CD_TURNO</th>\n",
              "      <th>VL_IDESP</th>\n",
              "      <th>VL_REPASSE_ALUNO</th>\n",
              "      <th>VL_INSE</th>\n",
              "      <th>QT_ALUNO_ESCOLA</th>\n",
              "      <th>TX_EVASAO</th>\n",
              "      <th>VL_NOTA_LP</th>\n",
              "      <th>VL_NOTA_GEO</th>\n",
              "      <th>VL_NOTA_HIST</th>\n",
              "      <th>VL_NOTA_MAT</th>\n",
              "      <th>VL_NOTA_ING</th>\n",
              "      <th>VL_NOTA_ART</th>\n",
              "      <th>VL_NOTA_EDFIS</th>\n",
              "      <th>VL_NOTA_CIEN</th>\n",
              "      <th>VL_NOTA_LP2</th>\n",
              "      <th>VL_NOTA_GEO2</th>\n",
              "      <th>VL_NOTA_HIST2</th>\n",
              "      <th>VL_NOTA_MAT2</th>\n",
              "      <th>VL_NOTA_ING2</th>\n",
              "      <th>VL_NOTA_ART2</th>\n",
              "      <th>VL_NOTA_EDFIS2</th>\n",
              "      <th>VL_NOTA_CIEN2</th>\n",
              "      <th>VL_NOTA_LP3</th>\n",
              "      <th>VL_NOTA_GEO3</th>\n",
              "      <th>VL_NOTA_HIST3</th>\n",
              "      <th>VL_NOTA_MAT3</th>\n",
              "      <th>VL_NOTA_ING3</th>\n",
              "      <th>VL_NOTA_ART3</th>\n",
              "      <th>VL_NOTA_EDFIS3</th>\n",
              "      <th>VL_NOTA_CIEN3</th>\n",
              "      <th>VL_NOTA_LP4</th>\n",
              "      <th>VL_NOTA_GEO4</th>\n",
              "      <th>VL_NOTA_HIST4</th>\n",
              "      <th>VL_NOTA_MAT4</th>\n",
              "      <th>VL_NOTA_ING4</th>\n",
              "      <th>VL_NOTA_ART4</th>\n",
              "      <th>VL_NOTA_EDFIS4</th>\n",
              "      <th>VL_NOTA_CIEN4</th>\n",
              "      <th>TX_FREQ_LP</th>\n",
              "      <th>TX_FREQ_GEO</th>\n",
              "      <th>TX_FREQ_HIST</th>\n",
              "      <th>TX_FREQ_MAT</th>\n",
              "      <th>TX_FREQ_ING</th>\n",
              "      <th>TX_FREQ_ART</th>\n",
              "      <th>TX_FREQ_EDFIS</th>\n",
              "      <th>TX_FREQ_CIEN</th>\n",
              "      <th>TX_FREQ_LP2</th>\n",
              "      <th>TX_FREQ_GEO2</th>\n",
              "      <th>TX_FREQ_HIST2</th>\n",
              "      <th>TX_FREQ_MAT2</th>\n",
              "      <th>TX_FREQ_ING2</th>\n",
              "      <th>TX_FREQ_ART2</th>\n",
              "      <th>TX_FREQ_EDFIS2</th>\n",
              "      <th>TX_FREQ_CIEN2</th>\n",
              "      <th>TX_FREQ_LP3</th>\n",
              "      <th>TX_FREQ_GEO3</th>\n",
              "      <th>TX_FREQ_HIST3</th>\n",
              "      <th>TX_FREQ_MAT3</th>\n",
              "      <th>TX_FREQ_ING3</th>\n",
              "      <th>TX_FREQ_ART3</th>\n",
              "      <th>TX_FREQ_EDFIS3</th>\n",
              "      <th>TX_FREQ_CIEN3</th>\n",
              "      <th>TX_FREQ_LP4</th>\n",
              "      <th>TX_FREQ_GEO4</th>\n",
              "      <th>TX_FREQ_HIST4</th>\n",
              "      <th>TX_FREQ_MAT4</th>\n",
              "      <th>TX_FREQ_ING4</th>\n",
              "      <th>TX_FREQ_ART4</th>\n",
              "      <th>TX_FREQ_EDFIS4</th>\n",
              "      <th>TX_FREQ_CIEN4</th>\n",
              "      <th>ESC_Código_de_situação_do_setor_censitário</th>\n",
              "      <th>ESC_Setor_é_Aglomerado_subnormal_</th>\n",
              "      <th>ESC_Grupo_do_IPVS</th>\n",
              "      <th>ESC_Domicílios_particulares_e_coletivos</th>\n",
              "      <th>ESC_Média_de_moradores_em_domicílios_particulares_permanentes</th>\n",
              "      <th>ESC_Proporção_de_crianças_de_0_a_5_anos_na_população</th>\n",
              "      <th>ESC_Rendimento_médio_domiciliar_dos_domicílios</th>\n",
              "      <th>ESC_Renda_per_capita_nos_domicílios</th>\n",
              "      <th>ESC_Proporção_de_Domicílios_sem_Renda_per_Capita</th>\n",
              "      <th>ESC_Idade_média_das_pessoas_responsáveis</th>\n",
              "      <th>ESC_Rendimento_médio_do_responsável_pelo_domicílio</th>\n",
              "      <th>ESC_Proporção_de_pessoas_responsáveis_alfabetizadas</th>\n",
              "      <th>ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos</th>\n",
              "      <th>ESC_Participação_da_renda_do_responsável</th>\n",
              "      <th>ESC_Idade_média_mulheres_respon_pelo_domicílio</th>\n",
              "      <th>ESC_Prop_mulheres_respon_domicílio_alfabet</th>\n",
              "      <th>ESC_Prop_mulheres_respon_domicílio_menos_30_anos</th>\n",
              "      <th>ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio</th>\n",
              "      <th>ESC_Prop_abastecimento_de_água</th>\n",
              "      <th>ESC_Prop_banheiro</th>\n",
              "      <th>ESC_Prop_domicílios_pp_lixo_coletado</th>\n",
              "      <th>ESC_Prop_domicílios_pp_energia_elétrica</th>\n",
              "      <th>ESC_Pop_total_residente_Mun</th>\n",
              "      <th>AL_Código_de_situação_do_setor_censitário</th>\n",
              "      <th>AL_Setor_é_Aglomerado_subnormal_</th>\n",
              "      <th>AL_Grupo_do_IPVS</th>\n",
              "      <th>AL_Domicílios_particulares_e_coletivos</th>\n",
              "      <th>AL_Média_de_moradores_em_domicílios_particulares_permanentes</th>\n",
              "      <th>AL_Proporção_de_crianças_de_0_a_5_anos_na_população</th>\n",
              "      <th>AL_Rendimento_médio_domiciliar_dos_domicílios</th>\n",
              "      <th>AL_Renda_per_capita_nos_domicílios</th>\n",
              "      <th>AL_Proporção_de_Domicílios_sem_Renda_per_Capita</th>\n",
              "      <th>AL_Idade_média_das_pessoas_responsáveis</th>\n",
              "      <th>AL_Rendimento_médio_do_responsável_pelo_domicílio</th>\n",
              "      <th>AL_Proporção_de_pessoas_responsáveis_alfabetizadas</th>\n",
              "      <th>AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos</th>\n",
              "      <th>AL_Participação_da_renda_do_responsável</th>\n",
              "      <th>AL_Idade_média_mulheres_respon_pelo_domicílio</th>\n",
              "      <th>AL_Prop_mulheres_respon_domicílio_alfabet</th>\n",
              "      <th>AL_Prop_mulheres_respon_domicílio_menos_30_anos</th>\n",
              "      <th>AL_Rend_médio_mulheres_responsáveis_pelo_domicílio</th>\n",
              "      <th>AL_Prop_abastecimento_de_água</th>\n",
              "      <th>AL_Prop_banheiro</th>\n",
              "      <th>AL_Prop_domicílios_pp_lixo_coletado</th>\n",
              "      <th>AL_Prop_domicílios_pp_energia_elétrica</th>\n",
              "      <th>AL_Pop_total_residente_Mun</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>25340195</td>\n",
              "      <td>0</td>\n",
              "      <td>F</td>\n",
              "      <td>14.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>14</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>3.14</td>\n",
              "      <td>33.7304</td>\n",
              "      <td>5.22</td>\n",
              "      <td>1092</td>\n",
              "      <td>0.0440</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>89.0</td>\n",
              "      <td>3.17</td>\n",
              "      <td>5.673759</td>\n",
              "      <td>3814.752809</td>\n",
              "      <td>1203.946809</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>49.696629</td>\n",
              "      <td>2405.000000</td>\n",
              "      <td>98.876404</td>\n",
              "      <td>3.370787</td>\n",
              "      <td>63.044714</td>\n",
              "      <td>49.380952</td>\n",
              "      <td>95.238095</td>\n",
              "      <td>14.285714</td>\n",
              "      <td>1516.666667</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>36686.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>N</td>\n",
              "      <td>4.0</td>\n",
              "      <td>263.0</td>\n",
              "      <td>3.07</td>\n",
              "      <td>7.673267</td>\n",
              "      <td>1567.311787</td>\n",
              "      <td>510.152228</td>\n",
              "      <td>0.380228</td>\n",
              "      <td>47.437262</td>\n",
              "      <td>816.015209</td>\n",
              "      <td>93.155894</td>\n",
              "      <td>12.547529</td>\n",
              "      <td>52.064638</td>\n",
              "      <td>45.604396</td>\n",
              "      <td>94.505495</td>\n",
              "      <td>15.384615</td>\n",
              "      <td>578.527472</td>\n",
              "      <td>97.338403</td>\n",
              "      <td>98.859316</td>\n",
              "      <td>97.718631</td>\n",
              "      <td>100.0</td>\n",
              "      <td>17266.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>28127559</td>\n",
              "      <td>0</td>\n",
              "      <td>M</td>\n",
              "      <td>12.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "      <td>4.17</td>\n",
              "      <td>39.7149</td>\n",
              "      <td>2.35</td>\n",
              "      <td>1221</td>\n",
              "      <td>0.0385</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.8214</td>\n",
              "      <td>0.9524</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.8621</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8421</td>\n",
              "      <td>0.8929</td>\n",
              "      <td>0.9444</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8947</td>\n",
              "      <td>0.9259</td>\n",
              "      <td>0.9474</td>\n",
              "      <td>0.9474</td>\n",
              "      <td>0.9630</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.9286</td>\n",
              "      <td>0.9545</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9091</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.7895</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>1.0</td>\n",
              "      <td>176.0</td>\n",
              "      <td>2.59</td>\n",
              "      <td>2.197802</td>\n",
              "      <td>6775.170455</td>\n",
              "      <td>2620.725275</td>\n",
              "      <td>0.568182</td>\n",
              "      <td>58.312500</td>\n",
              "      <td>5577.102273</td>\n",
              "      <td>99.431818</td>\n",
              "      <td>5.113636</td>\n",
              "      <td>82.316782</td>\n",
              "      <td>63.258427</td>\n",
              "      <td>98.876404</td>\n",
              "      <td>6.741573</td>\n",
              "      <td>8402.943820</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>41907.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>186.0</td>\n",
              "      <td>3.15</td>\n",
              "      <td>6.153846</td>\n",
              "      <td>2949.784946</td>\n",
              "      <td>937.880342</td>\n",
              "      <td>1.075269</td>\n",
              "      <td>56.016129</td>\n",
              "      <td>1752.752688</td>\n",
              "      <td>94.623656</td>\n",
              "      <td>4.838710</td>\n",
              "      <td>59.419677</td>\n",
              "      <td>58.760563</td>\n",
              "      <td>90.140845</td>\n",
              "      <td>8.450704</td>\n",
              "      <td>1238.521127</td>\n",
              "      <td>93.548387</td>\n",
              "      <td>99.462366</td>\n",
              "      <td>99.462366</td>\n",
              "      <td>100.0</td>\n",
              "      <td>41907.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>23470924</td>\n",
              "      <td>0</td>\n",
              "      <td>F</td>\n",
              "      <td>15.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14</td>\n",
              "      <td>9</td>\n",
              "      <td>3</td>\n",
              "      <td>2.42</td>\n",
              "      <td>24.4031</td>\n",
              "      <td>5.24</td>\n",
              "      <td>1116</td>\n",
              "      <td>0.0645</td>\n",
              "      <td>5.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>0.9143</td>\n",
              "      <td>0.8810</td>\n",
              "      <td>0.7313</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5909</td>\n",
              "      <td>0.9375</td>\n",
              "      <td>0.6667</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.5714</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>0.8667</td>\n",
              "      <td>0.8235</td>\n",
              "      <td>0.7500</td>\n",
              "      <td>0.7576</td>\n",
              "      <td>0.7755</td>\n",
              "      <td>0.8571</td>\n",
              "      <td>0.3750</td>\n",
              "      <td>0.7885</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.8750</td>\n",
              "      <td>0.9118</td>\n",
              "      <td>0.6818</td>\n",
              "      <td>0.6875</td>\n",
              "      <td>0.6842</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.7273</td>\n",
              "      <td>0.9565</td>\n",
              "      <td>0.7045</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>4.0</td>\n",
              "      <td>186.0</td>\n",
              "      <td>3.17</td>\n",
              "      <td>8.319185</td>\n",
              "      <td>1856.000000</td>\n",
              "      <td>586.105263</td>\n",
              "      <td>0.537634</td>\n",
              "      <td>48.112903</td>\n",
              "      <td>1131.784946</td>\n",
              "      <td>96.236559</td>\n",
              "      <td>11.827957</td>\n",
              "      <td>60.979792</td>\n",
              "      <td>48.318841</td>\n",
              "      <td>94.202899</td>\n",
              "      <td>11.594203</td>\n",
              "      <td>728.884058</td>\n",
              "      <td>100.0</td>\n",
              "      <td>97.849462</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>1221979.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>4.0</td>\n",
              "      <td>77.0</td>\n",
              "      <td>3.34</td>\n",
              "      <td>7.003891</td>\n",
              "      <td>1608.532468</td>\n",
              "      <td>481.933852</td>\n",
              "      <td>2.597403</td>\n",
              "      <td>44.467532</td>\n",
              "      <td>769.441558</td>\n",
              "      <td>93.506494</td>\n",
              "      <td>15.584416</td>\n",
              "      <td>47.835003</td>\n",
              "      <td>44.217391</td>\n",
              "      <td>91.304348</td>\n",
              "      <td>13.043478</td>\n",
              "      <td>511.847826</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>1221979.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23690042</td>\n",
              "      <td>0</td>\n",
              "      <td>M</td>\n",
              "      <td>12.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "      <td>4.35</td>\n",
              "      <td>32.6051</td>\n",
              "      <td>1.83</td>\n",
              "      <td>1897</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.9718</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8571</td>\n",
              "      <td>0.9701</td>\n",
              "      <td>0.9524</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9583</td>\n",
              "      <td>0.9592</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9375</td>\n",
              "      <td>0.9744</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8750</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.9583</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.8667</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.8824</td>\n",
              "      <td>0.9697</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.9825</td>\n",
              "      <td>0.9130</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9500</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>2.33</td>\n",
              "      <td>3.267974</td>\n",
              "      <td>5504.192893</td>\n",
              "      <td>2362.366013</td>\n",
              "      <td>3.045685</td>\n",
              "      <td>60.406091</td>\n",
              "      <td>3624.081218</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>3.553299</td>\n",
              "      <td>65.842191</td>\n",
              "      <td>62.023077</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>1.538462</td>\n",
              "      <td>2891.076923</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>586625.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>209.0</td>\n",
              "      <td>3.20</td>\n",
              "      <td>5.829596</td>\n",
              "      <td>3336.818182</td>\n",
              "      <td>1042.443946</td>\n",
              "      <td>1.435407</td>\n",
              "      <td>48.995215</td>\n",
              "      <td>1939.569378</td>\n",
              "      <td>97.607656</td>\n",
              "      <td>11.004785</td>\n",
              "      <td>58.126313</td>\n",
              "      <td>52.276923</td>\n",
              "      <td>93.846154</td>\n",
              "      <td>13.846154</td>\n",
              "      <td>1351.384615</td>\n",
              "      <td>93.301435</td>\n",
              "      <td>96.172249</td>\n",
              "      <td>99.043062</td>\n",
              "      <td>100.0</td>\n",
              "      <td>78821.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>27752606</td>\n",
              "      <td>0</td>\n",
              "      <td>F</td>\n",
              "      <td>14.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>14</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>3.60</td>\n",
              "      <td>50.1011</td>\n",
              "      <td>3.18</td>\n",
              "      <td>592</td>\n",
              "      <td>0.0017</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.9344</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8966</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9677</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9545</td>\n",
              "      <td>0.8846</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.9459</td>\n",
              "      <td>0.9200</td>\n",
              "      <td>0.9048</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9375</td>\n",
              "      <td>0.9322</td>\n",
              "      <td>0.9231</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9130</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>354.0</td>\n",
              "      <td>3.02</td>\n",
              "      <td>6.378987</td>\n",
              "      <td>2416.283286</td>\n",
              "      <td>800.138837</td>\n",
              "      <td>1.694915</td>\n",
              "      <td>47.954802</td>\n",
              "      <td>1400.566572</td>\n",
              "      <td>96.327684</td>\n",
              "      <td>14.971751</td>\n",
              "      <td>57.963674</td>\n",
              "      <td>48.522936</td>\n",
              "      <td>93.577982</td>\n",
              "      <td>16.513761</td>\n",
              "      <td>878.568807</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>51242.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>2.0</td>\n",
              "      <td>306.0</td>\n",
              "      <td>2.94</td>\n",
              "      <td>7.119021</td>\n",
              "      <td>2522.130719</td>\n",
              "      <td>858.478309</td>\n",
              "      <td>1.307190</td>\n",
              "      <td>48.300654</td>\n",
              "      <td>1422.614379</td>\n",
              "      <td>96.078431</td>\n",
              "      <td>16.666667</td>\n",
              "      <td>56.405260</td>\n",
              "      <td>48.654412</td>\n",
              "      <td>93.382353</td>\n",
              "      <td>16.911765</td>\n",
              "      <td>782.448529</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>99.346405</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>51242.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   CD_ALUNO  Y TP_SEXO  VL_IDADE  VL_DISTORCAO  CD_TIPO_ENSINO  NR_SERIE  \\\n",
              "0  25340195  0       F      14.0           2.0              14         7   \n",
              "1  28127559  0       M      12.0           1.0              14         6   \n",
              "2  23470924  0       F      15.0           1.0              14         9   \n",
              "3  23690042  0       M      12.0           1.0              14         6   \n",
              "4  27752606  0       F      14.0           2.0              14         7   \n",
              "\n",
              "   CD_TURNO  VL_IDESP  VL_REPASSE_ALUNO  VL_INSE  QT_ALUNO_ESCOLA  TX_EVASAO  \\\n",
              "0         3      3.14           33.7304     5.22             1092     0.0440   \n",
              "1         3      4.17           39.7149     2.35             1221     0.0385   \n",
              "2         3      2.42           24.4031     5.24             1116     0.0645   \n",
              "3         3      4.35           32.6051     1.83             1897     0.0148   \n",
              "4         3      3.60           50.1011     3.18              592     0.0017   \n",
              "\n",
              "   VL_NOTA_LP  VL_NOTA_GEO  VL_NOTA_HIST  VL_NOTA_MAT  VL_NOTA_ING  \\\n",
              "0         5.0          5.0           5.0          5.0          5.0   \n",
              "1         3.0          5.0           3.0          1.0          7.0   \n",
              "2         5.0         10.0           5.0          3.0          4.0   \n",
              "3         7.0          8.0          10.0         10.0          6.0   \n",
              "4         9.0         10.0          10.0          6.0          9.0   \n",
              "\n",
              "   VL_NOTA_ART  VL_NOTA_EDFIS  VL_NOTA_CIEN  VL_NOTA_LP2  VL_NOTA_GEO2  \\\n",
              "0          5.0            8.0           5.0          5.0           5.0   \n",
              "1          5.0            7.0           1.0          4.0           5.0   \n",
              "2          7.0            4.0           7.0          3.0          10.0   \n",
              "3          8.0            8.0           6.0          7.0          10.0   \n",
              "4          9.0           10.0           7.0          9.0          10.0   \n",
              "\n",
              "   VL_NOTA_HIST2  VL_NOTA_MAT2  VL_NOTA_ING2  VL_NOTA_ART2  VL_NOTA_EDFIS2  \\\n",
              "0            5.0           5.0           5.0           5.0             8.0   \n",
              "1            5.0           2.0           3.0           5.0             2.0   \n",
              "2            3.0           7.0           6.0           7.0             8.0   \n",
              "3            7.0           5.0           8.0           9.0             4.0   \n",
              "4           10.0           7.0          10.0           9.0             9.0   \n",
              "\n",
              "   VL_NOTA_CIEN2  VL_NOTA_LP3  VL_NOTA_GEO3  VL_NOTA_HIST3  VL_NOTA_MAT3  \\\n",
              "0            5.0          5.0           5.0            5.0           5.0   \n",
              "1            2.0          4.0           5.0            6.0           2.0   \n",
              "2           10.0          5.0           8.0            2.0           5.0   \n",
              "3            7.0          6.0           8.0            6.0           4.0   \n",
              "4            8.0         10.0           7.0           10.0           7.0   \n",
              "\n",
              "   VL_NOTA_ING3  VL_NOTA_ART3  VL_NOTA_EDFIS3  VL_NOTA_CIEN3  VL_NOTA_LP4  \\\n",
              "0           5.0           5.0             8.0            5.0          5.0   \n",
              "1           6.0           6.0             2.0            6.0          4.0   \n",
              "2           6.0           8.0             7.0            9.0          6.0   \n",
              "3           8.0           6.0             4.0            7.0          6.0   \n",
              "4          10.0           9.0             9.0            8.0          7.0   \n",
              "\n",
              "   VL_NOTA_GEO4  VL_NOTA_HIST4  VL_NOTA_MAT4  VL_NOTA_ING4  VL_NOTA_ART4  \\\n",
              "0           5.0            5.0           5.0           5.0           5.0   \n",
              "1           5.0            7.0           1.0           3.0           5.0   \n",
              "2           8.0            4.0           6.0           6.0           6.0   \n",
              "3           9.0            6.0           5.0           7.0           8.0   \n",
              "4           9.0           10.0           8.0           9.0          10.0   \n",
              "\n",
              "   VL_NOTA_EDFIS4  VL_NOTA_CIEN4  TX_FREQ_LP  TX_FREQ_GEO  TX_FREQ_HIST  \\\n",
              "0             8.0            5.0      1.0000       1.0000        1.0000   \n",
              "1             5.0            4.0      0.8214       0.9524        0.8333   \n",
              "2             7.0            6.0      0.7015       0.9143        0.8810   \n",
              "3             9.0            7.0      0.9718       1.0000        0.8571   \n",
              "4             9.0            8.0      0.9344       1.0000        1.0000   \n",
              "\n",
              "   TX_FREQ_MAT  TX_FREQ_ING  TX_FREQ_ART  TX_FREQ_EDFIS  TX_FREQ_CIEN  \\\n",
              "0       1.0000       1.0000          1.0         1.0000        1.0000   \n",
              "1       0.8621       1.0000          0.9         1.0000        0.8421   \n",
              "2       0.7313       0.8800          1.0         0.5909        0.9375   \n",
              "3       0.9701       0.9524          1.0         1.0000        0.9583   \n",
              "4       1.0000       1.0000          1.0         1.0000        1.0000   \n",
              "\n",
              "   TX_FREQ_LP2  TX_FREQ_GEO2  TX_FREQ_HIST2  TX_FREQ_MAT2  TX_FREQ_ING2  \\\n",
              "0       1.0000        1.0000         1.0000        1.0000        1.0000   \n",
              "1       0.8929        0.9444         1.0000        0.8889        0.8000   \n",
              "2       0.6667        0.8333         0.5714        0.8800        0.8667   \n",
              "3       0.9592        1.0000         0.9375        0.9744        1.0000   \n",
              "4       0.8966        1.0000         1.0000        0.9677        1.0000   \n",
              "\n",
              "   TX_FREQ_ART2  TX_FREQ_EDFIS2  TX_FREQ_CIEN2  TX_FREQ_LP3  TX_FREQ_GEO3  \\\n",
              "0        1.0000          1.0000         1.0000       1.0000        0.8889   \n",
              "1        1.0000          0.8000         0.8947       0.9259        0.9474   \n",
              "2        0.8235          0.7500         0.7576       0.7755        0.8571   \n",
              "3        0.8750          0.9167         0.9412       0.9583           NaN   \n",
              "4        1.0000          1.0000         0.9545       0.8846           NaN   \n",
              "\n",
              "   TX_FREQ_HIST3  TX_FREQ_MAT3  TX_FREQ_ING3  TX_FREQ_ART3  TX_FREQ_EDFIS3  \\\n",
              "0         1.0000        1.0000        0.8889        0.8889          1.0000   \n",
              "1         0.9474        0.9630           NaN        0.9000          1.0000   \n",
              "2         0.3750        0.7885           NaN        0.8333          0.8750   \n",
              "3         1.0000        0.9167        0.9412        0.8667          0.9412   \n",
              "4         0.9459        0.9200        0.9048           NaN          1.0000   \n",
              "\n",
              "   TX_FREQ_CIEN3  TX_FREQ_LP4  TX_FREQ_GEO4  TX_FREQ_HIST4  TX_FREQ_MAT4  \\\n",
              "0         1.0000       1.0000        1.0000         0.9000        1.0000   \n",
              "1            NaN       0.9286        0.9545            NaN        0.8800   \n",
              "2         0.9118       0.6818        0.6875         0.6842        1.0000   \n",
              "3         0.8824       0.9697        1.0000            NaN        0.9825   \n",
              "4         0.9375       0.9322        0.9231            NaN        1.0000   \n",
              "\n",
              "   TX_FREQ_ING4  TX_FREQ_ART4  TX_FREQ_EDFIS4  TX_FREQ_CIEN4  \\\n",
              "0        1.0000        1.0000          1.0000         1.0000   \n",
              "1        1.0000        0.9091          1.0000         0.7895   \n",
              "2        0.9412        0.7273          0.9565         0.7045   \n",
              "3        0.9130        1.0000          0.9500         1.0000   \n",
              "4        0.9130        1.0000          1.0000         1.0000   \n",
              "\n",
              "   ESC_Código_de_situação_do_setor_censitário  \\\n",
              "0                                         1.0   \n",
              "1                                         1.0   \n",
              "2                                         1.0   \n",
              "3                                         1.0   \n",
              "4                                         1.0   \n",
              "\n",
              "  ESC_Setor_é_Aglomerado_subnormal_  ESC_Grupo_do_IPVS  \\\n",
              "0                                 N                2.0   \n",
              "1                                 N                1.0   \n",
              "2                                 N                4.0   \n",
              "3                                 N                2.0   \n",
              "4                                 N                2.0   \n",
              "\n",
              "   ESC_Domicílios_particulares_e_coletivos  \\\n",
              "0                                     89.0   \n",
              "1                                    176.0   \n",
              "2                                    186.0   \n",
              "3                                    197.0   \n",
              "4                                    354.0   \n",
              "\n",
              "   ESC_Média_de_moradores_em_domicílios_particulares_permanentes  \\\n",
              "0                                               3.17               \n",
              "1                                               2.59               \n",
              "2                                               3.17               \n",
              "3                                               2.33               \n",
              "4                                               3.02               \n",
              "\n",
              "   ESC_Proporção_de_crianças_de_0_a_5_anos_na_população  \\\n",
              "0                                           5.673759      \n",
              "1                                           2.197802      \n",
              "2                                           8.319185      \n",
              "3                                           3.267974      \n",
              "4                                           6.378987      \n",
              "\n",
              "   ESC_Rendimento_médio_domiciliar_dos_domicílios  \\\n",
              "0                                     3814.752809   \n",
              "1                                     6775.170455   \n",
              "2                                     1856.000000   \n",
              "3                                     5504.192893   \n",
              "4                                     2416.283286   \n",
              "\n",
              "   ESC_Renda_per_capita_nos_domicílios  \\\n",
              "0                          1203.946809   \n",
              "1                          2620.725275   \n",
              "2                           586.105263   \n",
              "3                          2362.366013   \n",
              "4                           800.138837   \n",
              "\n",
              "   ESC_Proporção_de_Domicílios_sem_Renda_per_Capita  \\\n",
              "0                                          0.000000   \n",
              "1                                          0.568182   \n",
              "2                                          0.537634   \n",
              "3                                          3.045685   \n",
              "4                                          1.694915   \n",
              "\n",
              "   ESC_Idade_média_das_pessoas_responsáveis  \\\n",
              "0                                 49.696629   \n",
              "1                                 58.312500   \n",
              "2                                 48.112903   \n",
              "3                                 60.406091   \n",
              "4                                 47.954802   \n",
              "\n",
              "   ESC_Rendimento_médio_do_responsável_pelo_domicílio  \\\n",
              "0                                        2405.000000    \n",
              "1                                        5577.102273    \n",
              "2                                        1131.784946    \n",
              "3                                        3624.081218    \n",
              "4                                        1400.566572    \n",
              "\n",
              "   ESC_Proporção_de_pessoas_responsáveis_alfabetizadas  \\\n",
              "0                                          98.876404     \n",
              "1                                          99.431818     \n",
              "2                                          96.236559     \n",
              "3                                         100.000000     \n",
              "4                                          96.327684     \n",
              "\n",
              "   ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos  \\\n",
              "0                                           3.370787       \n",
              "1                                           5.113636       \n",
              "2                                          11.827957       \n",
              "3                                           3.553299       \n",
              "4                                          14.971751       \n",
              "\n",
              "   ESC_Participação_da_renda_do_responsável  \\\n",
              "0                                 63.044714   \n",
              "1                                 82.316782   \n",
              "2                                 60.979792   \n",
              "3                                 65.842191   \n",
              "4                                 57.963674   \n",
              "\n",
              "   ESC_Idade_média_mulheres_respon_pelo_domicílio  \\\n",
              "0                                       49.380952   \n",
              "1                                       63.258427   \n",
              "2                                       48.318841   \n",
              "3                                       62.023077   \n",
              "4                                       48.522936   \n",
              "\n",
              "   ESC_Prop_mulheres_respon_domicílio_alfabet  \\\n",
              "0                                   95.238095   \n",
              "1                                   98.876404   \n",
              "2                                   94.202899   \n",
              "3                                  100.000000   \n",
              "4                                   93.577982   \n",
              "\n",
              "   ESC_Prop_mulheres_respon_domicílio_menos_30_anos  \\\n",
              "0                                         14.285714   \n",
              "1                                          6.741573   \n",
              "2                                         11.594203   \n",
              "3                                          1.538462   \n",
              "4                                         16.513761   \n",
              "\n",
              "   ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio  \\\n",
              "0                                        1516.666667     \n",
              "1                                        8402.943820     \n",
              "2                                         728.884058     \n",
              "3                                        2891.076923     \n",
              "4                                         878.568807     \n",
              "\n",
              "   ESC_Prop_abastecimento_de_água  ESC_Prop_banheiro  \\\n",
              "0                           100.0         100.000000   \n",
              "1                           100.0         100.000000   \n",
              "2                           100.0          97.849462   \n",
              "3                           100.0         100.000000   \n",
              "4                           100.0         100.000000   \n",
              "\n",
              "   ESC_Prop_domicílios_pp_lixo_coletado  \\\n",
              "0                                 100.0   \n",
              "1                                 100.0   \n",
              "2                                 100.0   \n",
              "3                                 100.0   \n",
              "4                                 100.0   \n",
              "\n",
              "   ESC_Prop_domicílios_pp_energia_elétrica  ESC_Pop_total_residente_Mun  \\\n",
              "0                                    100.0                      36686.0   \n",
              "1                                    100.0                      41907.0   \n",
              "2                                    100.0                    1221979.0   \n",
              "3                                    100.0                     586625.0   \n",
              "4                                    100.0                      51242.0   \n",
              "\n",
              "   AL_Código_de_situação_do_setor_censitário AL_Setor_é_Aglomerado_subnormal_  \\\n",
              "0                                        2.0                                N   \n",
              "1                                        1.0                                N   \n",
              "2                                        1.0                                N   \n",
              "3                                        1.0                                N   \n",
              "4                                        1.0                                N   \n",
              "\n",
              "   AL_Grupo_do_IPVS  AL_Domicílios_particulares_e_coletivos  \\\n",
              "0               4.0                                   263.0   \n",
              "1               2.0                                   186.0   \n",
              "2               4.0                                    77.0   \n",
              "3               2.0                                   209.0   \n",
              "4               2.0                                   306.0   \n",
              "\n",
              "   AL_Média_de_moradores_em_domicílios_particulares_permanentes  \\\n",
              "0                                               3.07              \n",
              "1                                               3.15              \n",
              "2                                               3.34              \n",
              "3                                               3.20              \n",
              "4                                               2.94              \n",
              "\n",
              "   AL_Proporção_de_crianças_de_0_a_5_anos_na_população  \\\n",
              "0                                           7.673267     \n",
              "1                                           6.153846     \n",
              "2                                           7.003891     \n",
              "3                                           5.829596     \n",
              "4                                           7.119021     \n",
              "\n",
              "   AL_Rendimento_médio_domiciliar_dos_domicílios  \\\n",
              "0                                    1567.311787   \n",
              "1                                    2949.784946   \n",
              "2                                    1608.532468   \n",
              "3                                    3336.818182   \n",
              "4                                    2522.130719   \n",
              "\n",
              "   AL_Renda_per_capita_nos_domicílios  \\\n",
              "0                          510.152228   \n",
              "1                          937.880342   \n",
              "2                          481.933852   \n",
              "3                         1042.443946   \n",
              "4                          858.478309   \n",
              "\n",
              "   AL_Proporção_de_Domicílios_sem_Renda_per_Capita  \\\n",
              "0                                         0.380228   \n",
              "1                                         1.075269   \n",
              "2                                         2.597403   \n",
              "3                                         1.435407   \n",
              "4                                         1.307190   \n",
              "\n",
              "   AL_Idade_média_das_pessoas_responsáveis  \\\n",
              "0                                47.437262   \n",
              "1                                56.016129   \n",
              "2                                44.467532   \n",
              "3                                48.995215   \n",
              "4                                48.300654   \n",
              "\n",
              "   AL_Rendimento_médio_do_responsável_pelo_domicílio  \\\n",
              "0                                         816.015209   \n",
              "1                                        1752.752688   \n",
              "2                                         769.441558   \n",
              "3                                        1939.569378   \n",
              "4                                        1422.614379   \n",
              "\n",
              "   AL_Proporção_de_pessoas_responsáveis_alfabetizadas  \\\n",
              "0                                          93.155894    \n",
              "1                                          94.623656    \n",
              "2                                          93.506494    \n",
              "3                                          97.607656    \n",
              "4                                          96.078431    \n",
              "\n",
              "   AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos  \\\n",
              "0                                          12.547529      \n",
              "1                                           4.838710      \n",
              "2                                          15.584416      \n",
              "3                                          11.004785      \n",
              "4                                          16.666667      \n",
              "\n",
              "   AL_Participação_da_renda_do_responsável  \\\n",
              "0                                52.064638   \n",
              "1                                59.419677   \n",
              "2                                47.835003   \n",
              "3                                58.126313   \n",
              "4                                56.405260   \n",
              "\n",
              "   AL_Idade_média_mulheres_respon_pelo_domicílio  \\\n",
              "0                                      45.604396   \n",
              "1                                      58.760563   \n",
              "2                                      44.217391   \n",
              "3                                      52.276923   \n",
              "4                                      48.654412   \n",
              "\n",
              "   AL_Prop_mulheres_respon_domicílio_alfabet  \\\n",
              "0                                  94.505495   \n",
              "1                                  90.140845   \n",
              "2                                  91.304348   \n",
              "3                                  93.846154   \n",
              "4                                  93.382353   \n",
              "\n",
              "   AL_Prop_mulheres_respon_domicílio_menos_30_anos  \\\n",
              "0                                        15.384615   \n",
              "1                                         8.450704   \n",
              "2                                        13.043478   \n",
              "3                                        13.846154   \n",
              "4                                        16.911765   \n",
              "\n",
              "   AL_Rend_médio_mulheres_responsáveis_pelo_domicílio  \\\n",
              "0                                         578.527472    \n",
              "1                                        1238.521127    \n",
              "2                                         511.847826    \n",
              "3                                        1351.384615    \n",
              "4                                         782.448529    \n",
              "\n",
              "   AL_Prop_abastecimento_de_água  AL_Prop_banheiro  \\\n",
              "0                      97.338403         98.859316   \n",
              "1                      93.548387         99.462366   \n",
              "2                     100.000000        100.000000   \n",
              "3                      93.301435         96.172249   \n",
              "4                     100.000000         99.346405   \n",
              "\n",
              "   AL_Prop_domicílios_pp_lixo_coletado  \\\n",
              "0                            97.718631   \n",
              "1                            99.462366   \n",
              "2                           100.000000   \n",
              "3                            99.043062   \n",
              "4                           100.000000   \n",
              "\n",
              "   AL_Prop_domicílios_pp_energia_elétrica  AL_Pop_total_residente_Mun  \n",
              "0                                   100.0                     17266.0  \n",
              "1                                   100.0                     41907.0  \n",
              "2                                   100.0                   1221979.0  \n",
              "3                                   100.0                     78821.0  \n",
              "4                                   100.0                     51242.0  "
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GUA9JABJgKHO",
        "outputId": "18ac64c8-9cb3-4a55-8069-1b039da054d3"
      },
      "source": [
        "# Fazendo a divisão entre nossas amostras de evadidos/não evadidos (dropout/non-dropout), dados categóricos/numéricos/binários e multi valorados\n",
        "\n",
        "# Separando em evasão/não evasão (dropout/non-dropout), respectivamente (Y=1/Y=0)\n",
        "\n",
        "dropout     = dropout_df[dropout_df[\"Y\"] == \"1\"]\n",
        "non_dropout = dropout_df[dropout_df[\"Y\"] == \"0\"]\n",
        "\n",
        "# Separando entre colunas categóricas e numéricas\n",
        "\n",
        "Id_col     = ['CD_ALUNO'] # Nossa coluna de identificação CD_ALUNO\n",
        "target_col = [\"Y\"] # Nossa coluna alvo (evasão/não evasão)\n",
        "#cat_cols   = dropout_df.nunique()[dropout_df.nunique() < 10].keys().tolist() # Se valores únicos menores que 10 = atributo categórico\n",
        "#cat_cols   = [x for x in cat_cols if x not in target_col] # Excetuando-se target_col\n",
        "#num_cols   = [x for x in dropout_df.columns if x not in cat_cols + target_col + Id_col] # Qualquer outro caso = atributo numérico\n",
        "\n",
        "# Observando nossos atributos numéricos\n",
        "\n",
        "#print (\"Descrição de nossos atributos numéricos\")\n",
        "\n",
        "#print (\"Linhas     : \" ,dropout_df[num_cols].shape[0])\n",
        "#print (\"Colunas  : \" ,dropout_df[num_cols].shape[1])\n",
        "#print (\"\\nAtributos : \\n\" ,dropout_df[num_cols].columns.tolist())\n",
        "#print (\"\\nValores faltantes :  \",dropout_df[num_cols].isnull().sum().values.sum())\n",
        "#print (\"\\nValores únicos :  \\n\",dropout_df[num_cols].nunique())\n",
        "\n",
        "#dropout_df[num_cols].head()\n",
        "\n",
        "# Observando nossos atributos binários\n",
        "\n",
        "bin_cols = dropout_df.nunique()[dropout_df.nunique() == 2].keys().tolist()\n",
        "\n",
        "# Observando em detalhes nossos atributos binários (Atr ex: Y, TP_SEXO, CD_TIPO_ENSINO e NM_TIPO_ENSINO)\n",
        "\n",
        "#print (\"Descrição de nossos atributos binários\")\n",
        "    \n",
        "#print (\"Linhas     : \" ,dropout_df[bin_cols].shape[0])\n",
        "#print (\"Colunas  : \" ,dropout_df[bin_cols].shape[1])\n",
        "#print (\"\\nAtributos : \\n\" ,dropout_df[bin_cols].columns.tolist())\n",
        "#print (\"\\nValores faltantes :  \",dropout_df[bin_cols].isnull().sum().values.sum())\n",
        "#print (\"\\nValores únicos :  \\n\",dropout_df[bin_cols].nunique())\n",
        "\n",
        "#dropout_df[bin_cols].head()\n",
        "\n",
        "# Observando nossos atributos multi valorados (mais de dois valores)\n",
        "\n",
        "#multi_cols = [i for i in cat_cols if i not in bin_cols]\n",
        "\n",
        "# Observando em detalhes nossos atributos multi valorados (mais de dois valores)\n",
        "\n",
        "#print (\"Descrição de nossos atributos multi valorados\")\n",
        "    \n",
        "#print (\"Linhas     : \" ,dropout_df[multi_cols].shape[0])\n",
        "#print (\"Colunas  : \" ,dropout_df[multi_cols].shape[1])\n",
        "#print (\"\\nAtributos : \\n\" ,dropout_df[multi_cols].columns.tolist())\n",
        "#print (\"\\nValores faltantes :  \",dropout_df[multi_cols].isnull().sum().values.sum())\n",
        "#print (\"\\nValores únicos :  \\n\",dropout_df[multi_cols].nunique())\n",
        "\n",
        "#dropout_df[multi_cols].head()\n",
        "\n",
        "# Label encoding de nossos atributos numéricos (se necessário)\n",
        "\n",
        "le = LabelEncoder()\n",
        "\n",
        "#for i in num_cols :\n",
        "#    dropout_df[i] = le.fit_transform(dropout_df[i])\n",
        "\n",
        "# Label encoding de nossos atributos binários\n",
        "\n",
        "for j in bin_cols :\n",
        "    dropout_df[j] = le.fit_transform(dropout_df[j].astype(str))\n",
        "            \n",
        "# Duplicando nossas colunas para atributos multi valorados (se necessário)\n",
        "# Pandas get dummies - Dividindo colunas de dados com vários valores em conjuntos de\n",
        "# colunas booleanas, uma nova coluna para cada valor exclusivo em cada coluna de entrada\n",
        "\n",
        "#dropout_df[:] = np.nan_to_num(dropout_df)\n",
        "#dropout_df = pd.get_dummies(data = dropout_df,columns = multi_cols )\n",
        "\n",
        "# Normalização de nossos atributos numéricos (pode-se testar diferentes tipos de normalização)\n",
        "# Dada uma entrada x, a transformaremos em (x-média) / desvio padrão (onde todas as dimensões e operações estão bem definidas)\n",
        "\n",
        "#std = StandardScaler()\n",
        "#std = MinMaxScaler()\n",
        "#scaled = std.fit_transform(dropout_df[num_cols])\n",
        "#scaled = pd.DataFrame(scaled,columns=num_cols)\n",
        "\n",
        "# Descartando valores originais mesclando valores dimensionados para nossas colunas numéricas\n",
        "\n",
        "#dropout_df_og = dropout_df.copy()\n",
        "#dropout_df = dropout_df.drop(columns = num_cols,axis = 1)\n",
        "#dropout_df = dropout_df.merge(scaled,left_index=True,right_index=True,how = \"left\")\n",
        "\n",
        "# Verificando valores inf e/ou valores NA e alterando-os com seus valores de moda\n",
        "\n",
        "#col_mask=evasao_train_df.isnull().any(axis=0)\n",
        "#row_mask=evasao_train_df.isnull().any(axis=1)\n",
        "\n",
        "#print (col_mask)\n",
        "#print (row_mask)\n",
        "\n",
        "dropout_df[:] = np.nan_to_num(dropout_df)\n",
        "\n",
        "#pd.set_option('display.max_columns', None)\n",
        "#dropout_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/home/administrador/anaconda2/envs/py3/lib/python3.8/site-packages/pandas/core/ops/array_ops.py:253: FutureWarning:\n",
            "\n",
            "elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tIp6Iv_UgKHS"
      },
      "source": [
        "# Usaremos o dataframe no qual foram criados nossas variáveis dummy\n",
        "\n",
        "y = dropout_df['Y'].values # Atributo alvo\n",
        "X = dropout_df.drop(columns = ['Y']) # Demais atributos para classificação\n",
        "\n",
        "# Normalização de todos os nossos atributos para um intervalo de de 0 a 1 (já feito anteriormente, contingência visando qualquer eventual erro)\n",
        "\n",
        "#from sklearn.preprocessing import MinMaxScaler\n",
        "#features = X.columns.values\n",
        "#scaler = MinMaxScaler(feature_range = (0,1))\n",
        "#scaler.fit(X)\n",
        "#X = pd.DataFrame(scaler.transform(X))\n",
        "#X.columns = features"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9JjwFMu2gKHS",
        "outputId": "25a6265a-c6b4-4e45-c98a-782f76fcc9df"
      },
      "source": [
        "# Observação de nosso cabeçalho/primeiras 5 linhas, exibição de todas as colunas\n",
        "\n",
        "pd.set_option('display.max_columns', None)\n",
        "dropout_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "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>CD_ALUNO</th>\n",
              "      <th>Y</th>\n",
              "      <th>TP_SEXO</th>\n",
              "      <th>VL_IDADE</th>\n",
              "      <th>VL_DISTORCAO</th>\n",
              "      <th>CD_TIPO_ENSINO</th>\n",
              "      <th>NR_SERIE</th>\n",
              "      <th>CD_TURNO</th>\n",
              "      <th>VL_IDESP</th>\n",
              "      <th>VL_REPASSE_ALUNO</th>\n",
              "      <th>VL_INSE</th>\n",
              "      <th>QT_ALUNO_ESCOLA</th>\n",
              "      <th>TX_EVASAO</th>\n",
              "      <th>VL_NOTA_LP</th>\n",
              "      <th>VL_NOTA_GEO</th>\n",
              "      <th>VL_NOTA_HIST</th>\n",
              "      <th>VL_NOTA_MAT</th>\n",
              "      <th>VL_NOTA_ING</th>\n",
              "      <th>VL_NOTA_ART</th>\n",
              "      <th>VL_NOTA_EDFIS</th>\n",
              "      <th>VL_NOTA_CIEN</th>\n",
              "      <th>VL_NOTA_LP2</th>\n",
              "      <th>VL_NOTA_GEO2</th>\n",
              "      <th>VL_NOTA_HIST2</th>\n",
              "      <th>VL_NOTA_MAT2</th>\n",
              "      <th>VL_NOTA_ING2</th>\n",
              "      <th>VL_NOTA_ART2</th>\n",
              "      <th>VL_NOTA_EDFIS2</th>\n",
              "      <th>VL_NOTA_CIEN2</th>\n",
              "      <th>VL_NOTA_LP3</th>\n",
              "      <th>VL_NOTA_GEO3</th>\n",
              "      <th>VL_NOTA_HIST3</th>\n",
              "      <th>VL_NOTA_MAT3</th>\n",
              "      <th>VL_NOTA_ING3</th>\n",
              "      <th>VL_NOTA_ART3</th>\n",
              "      <th>VL_NOTA_EDFIS3</th>\n",
              "      <th>VL_NOTA_CIEN3</th>\n",
              "      <th>VL_NOTA_LP4</th>\n",
              "      <th>VL_NOTA_GEO4</th>\n",
              "      <th>VL_NOTA_HIST4</th>\n",
              "      <th>VL_NOTA_MAT4</th>\n",
              "      <th>VL_NOTA_ING4</th>\n",
              "      <th>VL_NOTA_ART4</th>\n",
              "      <th>VL_NOTA_EDFIS4</th>\n",
              "      <th>VL_NOTA_CIEN4</th>\n",
              "      <th>TX_FREQ_LP</th>\n",
              "      <th>TX_FREQ_GEO</th>\n",
              "      <th>TX_FREQ_HIST</th>\n",
              "      <th>TX_FREQ_MAT</th>\n",
              "      <th>TX_FREQ_ING</th>\n",
              "      <th>TX_FREQ_ART</th>\n",
              "      <th>TX_FREQ_EDFIS</th>\n",
              "      <th>TX_FREQ_CIEN</th>\n",
              "      <th>TX_FREQ_LP2</th>\n",
              "      <th>TX_FREQ_GEO2</th>\n",
              "      <th>TX_FREQ_HIST2</th>\n",
              "      <th>TX_FREQ_MAT2</th>\n",
              "      <th>TX_FREQ_ING2</th>\n",
              "      <th>TX_FREQ_ART2</th>\n",
              "      <th>TX_FREQ_EDFIS2</th>\n",
              "      <th>TX_FREQ_CIEN2</th>\n",
              "      <th>TX_FREQ_LP3</th>\n",
              "      <th>TX_FREQ_GEO3</th>\n",
              "      <th>TX_FREQ_HIST3</th>\n",
              "      <th>TX_FREQ_MAT3</th>\n",
              "      <th>TX_FREQ_ING3</th>\n",
              "      <th>TX_FREQ_ART3</th>\n",
              "      <th>TX_FREQ_EDFIS3</th>\n",
              "      <th>TX_FREQ_CIEN3</th>\n",
              "      <th>TX_FREQ_LP4</th>\n",
              "      <th>TX_FREQ_GEO4</th>\n",
              "      <th>TX_FREQ_HIST4</th>\n",
              "      <th>TX_FREQ_MAT4</th>\n",
              "      <th>TX_FREQ_ING4</th>\n",
              "      <th>TX_FREQ_ART4</th>\n",
              "      <th>TX_FREQ_EDFIS4</th>\n",
              "      <th>TX_FREQ_CIEN4</th>\n",
              "      <th>ESC_Código_de_situação_do_setor_censitário</th>\n",
              "      <th>ESC_Setor_é_Aglomerado_subnormal_</th>\n",
              "      <th>ESC_Grupo_do_IPVS</th>\n",
              "      <th>ESC_Domicílios_particulares_e_coletivos</th>\n",
              "      <th>ESC_Média_de_moradores_em_domicílios_particulares_permanentes</th>\n",
              "      <th>ESC_Proporção_de_crianças_de_0_a_5_anos_na_população</th>\n",
              "      <th>ESC_Rendimento_médio_domiciliar_dos_domicílios</th>\n",
              "      <th>ESC_Renda_per_capita_nos_domicílios</th>\n",
              "      <th>ESC_Proporção_de_Domicílios_sem_Renda_per_Capita</th>\n",
              "      <th>ESC_Idade_média_das_pessoas_responsáveis</th>\n",
              "      <th>ESC_Rendimento_médio_do_responsável_pelo_domicílio</th>\n",
              "      <th>ESC_Proporção_de_pessoas_responsáveis_alfabetizadas</th>\n",
              "      <th>ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos</th>\n",
              "      <th>ESC_Participação_da_renda_do_responsável</th>\n",
              "      <th>ESC_Idade_média_mulheres_respon_pelo_domicílio</th>\n",
              "      <th>ESC_Prop_mulheres_respon_domicílio_alfabet</th>\n",
              "      <th>ESC_Prop_mulheres_respon_domicílio_menos_30_anos</th>\n",
              "      <th>ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio</th>\n",
              "      <th>ESC_Prop_abastecimento_de_água</th>\n",
              "      <th>ESC_Prop_banheiro</th>\n",
              "      <th>ESC_Prop_domicílios_pp_lixo_coletado</th>\n",
              "      <th>ESC_Prop_domicílios_pp_energia_elétrica</th>\n",
              "      <th>ESC_Pop_total_residente_Mun</th>\n",
              "      <th>AL_Código_de_situação_do_setor_censitário</th>\n",
              "      <th>AL_Setor_é_Aglomerado_subnormal_</th>\n",
              "      <th>AL_Grupo_do_IPVS</th>\n",
              "      <th>AL_Domicílios_particulares_e_coletivos</th>\n",
              "      <th>AL_Média_de_moradores_em_domicílios_particulares_permanentes</th>\n",
              "      <th>AL_Proporção_de_crianças_de_0_a_5_anos_na_população</th>\n",
              "      <th>AL_Rendimento_médio_domiciliar_dos_domicílios</th>\n",
              "      <th>AL_Renda_per_capita_nos_domicílios</th>\n",
              "      <th>AL_Proporção_de_Domicílios_sem_Renda_per_Capita</th>\n",
              "      <th>AL_Idade_média_das_pessoas_responsáveis</th>\n",
              "      <th>AL_Rendimento_médio_do_responsável_pelo_domicílio</th>\n",
              "      <th>AL_Proporção_de_pessoas_responsáveis_alfabetizadas</th>\n",
              "      <th>AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos</th>\n",
              "      <th>AL_Participação_da_renda_do_responsável</th>\n",
              "      <th>AL_Idade_média_mulheres_respon_pelo_domicílio</th>\n",
              "      <th>AL_Prop_mulheres_respon_domicílio_alfabet</th>\n",
              "      <th>AL_Prop_mulheres_respon_domicílio_menos_30_anos</th>\n",
              "      <th>AL_Rend_médio_mulheres_responsáveis_pelo_domicílio</th>\n",
              "      <th>AL_Prop_abastecimento_de_água</th>\n",
              "      <th>AL_Prop_banheiro</th>\n",
              "      <th>AL_Prop_domicílios_pp_lixo_coletado</th>\n",
              "      <th>AL_Prop_domicílios_pp_energia_elétrica</th>\n",
              "      <th>AL_Pop_total_residente_Mun</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>25340195.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.14</td>\n",
              "      <td>33.7304</td>\n",
              "      <td>5.22</td>\n",
              "      <td>1092.0</td>\n",
              "      <td>0.0440</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>89.0</td>\n",
              "      <td>3.17</td>\n",
              "      <td>5.673759</td>\n",
              "      <td>3814.752809</td>\n",
              "      <td>1203.946809</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>49.696629</td>\n",
              "      <td>2405.000000</td>\n",
              "      <td>98.876404</td>\n",
              "      <td>3.370787</td>\n",
              "      <td>63.044714</td>\n",
              "      <td>49.380952</td>\n",
              "      <td>95.238095</td>\n",
              "      <td>14.285714</td>\n",
              "      <td>1516.666667</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>36686.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>263.0</td>\n",
              "      <td>3.07</td>\n",
              "      <td>7.673267</td>\n",
              "      <td>1567.311787</td>\n",
              "      <td>510.152228</td>\n",
              "      <td>0.380228</td>\n",
              "      <td>47.437262</td>\n",
              "      <td>816.015209</td>\n",
              "      <td>93.155894</td>\n",
              "      <td>12.547529</td>\n",
              "      <td>52.064638</td>\n",
              "      <td>45.604396</td>\n",
              "      <td>94.505495</td>\n",
              "      <td>15.384615</td>\n",
              "      <td>578.527472</td>\n",
              "      <td>97.338403</td>\n",
              "      <td>98.859316</td>\n",
              "      <td>97.718631</td>\n",
              "      <td>100.0</td>\n",
              "      <td>17266.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>28127559.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.17</td>\n",
              "      <td>39.7149</td>\n",
              "      <td>2.35</td>\n",
              "      <td>1221.0</td>\n",
              "      <td>0.0385</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.8214</td>\n",
              "      <td>0.9524</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.8621</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8421</td>\n",
              "      <td>0.8929</td>\n",
              "      <td>0.9444</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8947</td>\n",
              "      <td>0.9259</td>\n",
              "      <td>0.9474</td>\n",
              "      <td>0.9474</td>\n",
              "      <td>0.9630</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9286</td>\n",
              "      <td>0.9545</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9091</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.7895</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>176.0</td>\n",
              "      <td>2.59</td>\n",
              "      <td>2.197802</td>\n",
              "      <td>6775.170455</td>\n",
              "      <td>2620.725275</td>\n",
              "      <td>0.568182</td>\n",
              "      <td>58.312500</td>\n",
              "      <td>5577.102273</td>\n",
              "      <td>99.431818</td>\n",
              "      <td>5.113636</td>\n",
              "      <td>82.316782</td>\n",
              "      <td>63.258427</td>\n",
              "      <td>98.876404</td>\n",
              "      <td>6.741573</td>\n",
              "      <td>8402.943820</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>41907.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>186.0</td>\n",
              "      <td>3.15</td>\n",
              "      <td>6.153846</td>\n",
              "      <td>2949.784946</td>\n",
              "      <td>937.880342</td>\n",
              "      <td>1.075269</td>\n",
              "      <td>56.016129</td>\n",
              "      <td>1752.752688</td>\n",
              "      <td>94.623656</td>\n",
              "      <td>4.838710</td>\n",
              "      <td>59.419677</td>\n",
              "      <td>58.760563</td>\n",
              "      <td>90.140845</td>\n",
              "      <td>8.450704</td>\n",
              "      <td>1238.521127</td>\n",
              "      <td>93.548387</td>\n",
              "      <td>99.462366</td>\n",
              "      <td>99.462366</td>\n",
              "      <td>100.0</td>\n",
              "      <td>41907.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>23470924.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.42</td>\n",
              "      <td>24.4031</td>\n",
              "      <td>5.24</td>\n",
              "      <td>1116.0</td>\n",
              "      <td>0.0645</td>\n",
              "      <td>5.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>0.9143</td>\n",
              "      <td>0.8810</td>\n",
              "      <td>0.7313</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5909</td>\n",
              "      <td>0.9375</td>\n",
              "      <td>0.6667</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.5714</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>0.8667</td>\n",
              "      <td>0.8235</td>\n",
              "      <td>0.7500</td>\n",
              "      <td>0.7576</td>\n",
              "      <td>0.7755</td>\n",
              "      <td>0.8571</td>\n",
              "      <td>0.3750</td>\n",
              "      <td>0.7885</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.8750</td>\n",
              "      <td>0.9118</td>\n",
              "      <td>0.6818</td>\n",
              "      <td>0.6875</td>\n",
              "      <td>0.6842</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.7273</td>\n",
              "      <td>0.9565</td>\n",
              "      <td>0.7045</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>186.0</td>\n",
              "      <td>3.17</td>\n",
              "      <td>8.319185</td>\n",
              "      <td>1856.000000</td>\n",
              "      <td>586.105263</td>\n",
              "      <td>0.537634</td>\n",
              "      <td>48.112903</td>\n",
              "      <td>1131.784946</td>\n",
              "      <td>96.236559</td>\n",
              "      <td>11.827957</td>\n",
              "      <td>60.979792</td>\n",
              "      <td>48.318841</td>\n",
              "      <td>94.202899</td>\n",
              "      <td>11.594203</td>\n",
              "      <td>728.884058</td>\n",
              "      <td>100.0</td>\n",
              "      <td>97.849462</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>1221979.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>77.0</td>\n",
              "      <td>3.34</td>\n",
              "      <td>7.003891</td>\n",
              "      <td>1608.532468</td>\n",
              "      <td>481.933852</td>\n",
              "      <td>2.597403</td>\n",
              "      <td>44.467532</td>\n",
              "      <td>769.441558</td>\n",
              "      <td>93.506494</td>\n",
              "      <td>15.584416</td>\n",
              "      <td>47.835003</td>\n",
              "      <td>44.217391</td>\n",
              "      <td>91.304348</td>\n",
              "      <td>13.043478</td>\n",
              "      <td>511.847826</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>1221979.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23690042.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.35</td>\n",
              "      <td>32.6051</td>\n",
              "      <td>1.83</td>\n",
              "      <td>1897.0</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.9718</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8571</td>\n",
              "      <td>0.9701</td>\n",
              "      <td>0.9524</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9583</td>\n",
              "      <td>0.9592</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9375</td>\n",
              "      <td>0.9744</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8750</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.9583</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.8667</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.8824</td>\n",
              "      <td>0.9697</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9825</td>\n",
              "      <td>0.9130</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9500</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>2.33</td>\n",
              "      <td>3.267974</td>\n",
              "      <td>5504.192893</td>\n",
              "      <td>2362.366013</td>\n",
              "      <td>3.045685</td>\n",
              "      <td>60.406091</td>\n",
              "      <td>3624.081218</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>3.553299</td>\n",
              "      <td>65.842191</td>\n",
              "      <td>62.023077</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>1.538462</td>\n",
              "      <td>2891.076923</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>586625.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>209.0</td>\n",
              "      <td>3.20</td>\n",
              "      <td>5.829596</td>\n",
              "      <td>3336.818182</td>\n",
              "      <td>1042.443946</td>\n",
              "      <td>1.435407</td>\n",
              "      <td>48.995215</td>\n",
              "      <td>1939.569378</td>\n",
              "      <td>97.607656</td>\n",
              "      <td>11.004785</td>\n",
              "      <td>58.126313</td>\n",
              "      <td>52.276923</td>\n",
              "      <td>93.846154</td>\n",
              "      <td>13.846154</td>\n",
              "      <td>1351.384615</td>\n",
              "      <td>93.301435</td>\n",
              "      <td>96.172249</td>\n",
              "      <td>99.043062</td>\n",
              "      <td>100.0</td>\n",
              "      <td>78821.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>27752606.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.60</td>\n",
              "      <td>50.1011</td>\n",
              "      <td>3.18</td>\n",
              "      <td>592.0</td>\n",
              "      <td>0.0017</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.9344</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.8966</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9677</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9545</td>\n",
              "      <td>0.8846</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9459</td>\n",
              "      <td>0.9200</td>\n",
              "      <td>0.9048</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9375</td>\n",
              "      <td>0.9322</td>\n",
              "      <td>0.9231</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9130</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>354.0</td>\n",
              "      <td>3.02</td>\n",
              "      <td>6.378987</td>\n",
              "      <td>2416.283286</td>\n",
              "      <td>800.138837</td>\n",
              "      <td>1.694915</td>\n",
              "      <td>47.954802</td>\n",
              "      <td>1400.566572</td>\n",
              "      <td>96.327684</td>\n",
              "      <td>14.971751</td>\n",
              "      <td>57.963674</td>\n",
              "      <td>48.522936</td>\n",
              "      <td>93.577982</td>\n",
              "      <td>16.513761</td>\n",
              "      <td>878.568807</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>51242.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>306.0</td>\n",
              "      <td>2.94</td>\n",
              "      <td>7.119021</td>\n",
              "      <td>2522.130719</td>\n",
              "      <td>858.478309</td>\n",
              "      <td>1.307190</td>\n",
              "      <td>48.300654</td>\n",
              "      <td>1422.614379</td>\n",
              "      <td>96.078431</td>\n",
              "      <td>16.666667</td>\n",
              "      <td>56.405260</td>\n",
              "      <td>48.654412</td>\n",
              "      <td>93.382353</td>\n",
              "      <td>16.911765</td>\n",
              "      <td>782.448529</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>99.346405</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>51242.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     CD_ALUNO    Y  TP_SEXO  VL_IDADE  VL_DISTORCAO  CD_TIPO_ENSINO  NR_SERIE  \\\n",
              "0  25340195.0  0.0      0.0      14.0           2.0             0.0       7.0   \n",
              "1  28127559.0  0.0      1.0      12.0           1.0             0.0       6.0   \n",
              "2  23470924.0  0.0      0.0      15.0           1.0             0.0       9.0   \n",
              "3  23690042.0  0.0      1.0      12.0           1.0             0.0       6.0   \n",
              "4  27752606.0  0.0      0.0      14.0           2.0             0.0       7.0   \n",
              "\n",
              "   CD_TURNO  VL_IDESP  VL_REPASSE_ALUNO  VL_INSE  QT_ALUNO_ESCOLA  TX_EVASAO  \\\n",
              "0       3.0      3.14           33.7304     5.22           1092.0     0.0440   \n",
              "1       3.0      4.17           39.7149     2.35           1221.0     0.0385   \n",
              "2       3.0      2.42           24.4031     5.24           1116.0     0.0645   \n",
              "3       3.0      4.35           32.6051     1.83           1897.0     0.0148   \n",
              "4       3.0      3.60           50.1011     3.18            592.0     0.0017   \n",
              "\n",
              "   VL_NOTA_LP  VL_NOTA_GEO  VL_NOTA_HIST  VL_NOTA_MAT  VL_NOTA_ING  \\\n",
              "0         5.0          5.0           5.0          5.0          5.0   \n",
              "1         3.0          5.0           3.0          1.0          7.0   \n",
              "2         5.0         10.0           5.0          3.0          4.0   \n",
              "3         7.0          8.0          10.0         10.0          6.0   \n",
              "4         9.0         10.0          10.0          6.0          9.0   \n",
              "\n",
              "   VL_NOTA_ART  VL_NOTA_EDFIS  VL_NOTA_CIEN  VL_NOTA_LP2  VL_NOTA_GEO2  \\\n",
              "0          5.0            8.0           5.0          5.0           5.0   \n",
              "1          5.0            7.0           1.0          4.0           5.0   \n",
              "2          7.0            4.0           7.0          3.0          10.0   \n",
              "3          8.0            8.0           6.0          7.0          10.0   \n",
              "4          9.0           10.0           7.0          9.0          10.0   \n",
              "\n",
              "   VL_NOTA_HIST2  VL_NOTA_MAT2  VL_NOTA_ING2  VL_NOTA_ART2  VL_NOTA_EDFIS2  \\\n",
              "0            5.0           5.0           5.0           5.0             8.0   \n",
              "1            5.0           2.0           3.0           5.0             2.0   \n",
              "2            3.0           7.0           6.0           7.0             8.0   \n",
              "3            7.0           5.0           8.0           9.0             4.0   \n",
              "4           10.0           7.0          10.0           9.0             9.0   \n",
              "\n",
              "   VL_NOTA_CIEN2  VL_NOTA_LP3  VL_NOTA_GEO3  VL_NOTA_HIST3  VL_NOTA_MAT3  \\\n",
              "0            5.0          5.0           5.0            5.0           5.0   \n",
              "1            2.0          4.0           5.0            6.0           2.0   \n",
              "2           10.0          5.0           8.0            2.0           5.0   \n",
              "3            7.0          6.0           8.0            6.0           4.0   \n",
              "4            8.0         10.0           7.0           10.0           7.0   \n",
              "\n",
              "   VL_NOTA_ING3  VL_NOTA_ART3  VL_NOTA_EDFIS3  VL_NOTA_CIEN3  VL_NOTA_LP4  \\\n",
              "0           5.0           5.0             8.0            5.0          5.0   \n",
              "1           6.0           6.0             2.0            6.0          4.0   \n",
              "2           6.0           8.0             7.0            9.0          6.0   \n",
              "3           8.0           6.0             4.0            7.0          6.0   \n",
              "4          10.0           9.0             9.0            8.0          7.0   \n",
              "\n",
              "   VL_NOTA_GEO4  VL_NOTA_HIST4  VL_NOTA_MAT4  VL_NOTA_ING4  VL_NOTA_ART4  \\\n",
              "0           5.0            5.0           5.0           5.0           5.0   \n",
              "1           5.0            7.0           1.0           3.0           5.0   \n",
              "2           8.0            4.0           6.0           6.0           6.0   \n",
              "3           9.0            6.0           5.0           7.0           8.0   \n",
              "4           9.0           10.0           8.0           9.0          10.0   \n",
              "\n",
              "   VL_NOTA_EDFIS4  VL_NOTA_CIEN4  TX_FREQ_LP  TX_FREQ_GEO  TX_FREQ_HIST  \\\n",
              "0             8.0            5.0      1.0000       1.0000        1.0000   \n",
              "1             5.0            4.0      0.8214       0.9524        0.8333   \n",
              "2             7.0            6.0      0.7015       0.9143        0.8810   \n",
              "3             9.0            7.0      0.9718       1.0000        0.8571   \n",
              "4             9.0            8.0      0.9344       1.0000        1.0000   \n",
              "\n",
              "   TX_FREQ_MAT  TX_FREQ_ING  TX_FREQ_ART  TX_FREQ_EDFIS  TX_FREQ_CIEN  \\\n",
              "0       1.0000       1.0000          1.0         1.0000        1.0000   \n",
              "1       0.8621       1.0000          0.9         1.0000        0.8421   \n",
              "2       0.7313       0.8800          1.0         0.5909        0.9375   \n",
              "3       0.9701       0.9524          1.0         1.0000        0.9583   \n",
              "4       1.0000       1.0000          1.0         1.0000        1.0000   \n",
              "\n",
              "   TX_FREQ_LP2  TX_FREQ_GEO2  TX_FREQ_HIST2  TX_FREQ_MAT2  TX_FREQ_ING2  \\\n",
              "0       1.0000        1.0000         1.0000        1.0000        1.0000   \n",
              "1       0.8929        0.9444         1.0000        0.8889        0.8000   \n",
              "2       0.6667        0.8333         0.5714        0.8800        0.8667   \n",
              "3       0.9592        1.0000         0.9375        0.9744        1.0000   \n",
              "4       0.8966        1.0000         1.0000        0.9677        1.0000   \n",
              "\n",
              "   TX_FREQ_ART2  TX_FREQ_EDFIS2  TX_FREQ_CIEN2  TX_FREQ_LP3  TX_FREQ_GEO3  \\\n",
              "0        1.0000          1.0000         1.0000       1.0000        0.8889   \n",
              "1        1.0000          0.8000         0.8947       0.9259        0.9474   \n",
              "2        0.8235          0.7500         0.7576       0.7755        0.8571   \n",
              "3        0.8750          0.9167         0.9412       0.9583        0.0000   \n",
              "4        1.0000          1.0000         0.9545       0.8846        0.0000   \n",
              "\n",
              "   TX_FREQ_HIST3  TX_FREQ_MAT3  TX_FREQ_ING3  TX_FREQ_ART3  TX_FREQ_EDFIS3  \\\n",
              "0         1.0000        1.0000        0.8889        0.8889          1.0000   \n",
              "1         0.9474        0.9630        0.0000        0.9000          1.0000   \n",
              "2         0.3750        0.7885        0.0000        0.8333          0.8750   \n",
              "3         1.0000        0.9167        0.9412        0.8667          0.9412   \n",
              "4         0.9459        0.9200        0.9048        0.0000          1.0000   \n",
              "\n",
              "   TX_FREQ_CIEN3  TX_FREQ_LP4  TX_FREQ_GEO4  TX_FREQ_HIST4  TX_FREQ_MAT4  \\\n",
              "0         1.0000       1.0000        1.0000         0.9000        1.0000   \n",
              "1         0.0000       0.9286        0.9545         0.0000        0.8800   \n",
              "2         0.9118       0.6818        0.6875         0.6842        1.0000   \n",
              "3         0.8824       0.9697        1.0000         0.0000        0.9825   \n",
              "4         0.9375       0.9322        0.9231         0.0000        1.0000   \n",
              "\n",
              "   TX_FREQ_ING4  TX_FREQ_ART4  TX_FREQ_EDFIS4  TX_FREQ_CIEN4  \\\n",
              "0        1.0000        1.0000          1.0000         1.0000   \n",
              "1        1.0000        0.9091          1.0000         0.7895   \n",
              "2        0.9412        0.7273          0.9565         0.7045   \n",
              "3        0.9130        1.0000          0.9500         1.0000   \n",
              "4        0.9130        1.0000          1.0000         1.0000   \n",
              "\n",
              "   ESC_Código_de_situação_do_setor_censitário  \\\n",
              "0                                         1.0   \n",
              "1                                         1.0   \n",
              "2                                         1.0   \n",
              "3                                         1.0   \n",
              "4                                         1.0   \n",
              "\n",
              "   ESC_Setor_é_Aglomerado_subnormal_  ESC_Grupo_do_IPVS  \\\n",
              "0                                0.0                2.0   \n",
              "1                                0.0                1.0   \n",
              "2                                0.0                4.0   \n",
              "3                                0.0                2.0   \n",
              "4                                0.0                2.0   \n",
              "\n",
              "   ESC_Domicílios_particulares_e_coletivos  \\\n",
              "0                                     89.0   \n",
              "1                                    176.0   \n",
              "2                                    186.0   \n",
              "3                                    197.0   \n",
              "4                                    354.0   \n",
              "\n",
              "   ESC_Média_de_moradores_em_domicílios_particulares_permanentes  \\\n",
              "0                                               3.17               \n",
              "1                                               2.59               \n",
              "2                                               3.17               \n",
              "3                                               2.33               \n",
              "4                                               3.02               \n",
              "\n",
              "   ESC_Proporção_de_crianças_de_0_a_5_anos_na_população  \\\n",
              "0                                           5.673759      \n",
              "1                                           2.197802      \n",
              "2                                           8.319185      \n",
              "3                                           3.267974      \n",
              "4                                           6.378987      \n",
              "\n",
              "   ESC_Rendimento_médio_domiciliar_dos_domicílios  \\\n",
              "0                                     3814.752809   \n",
              "1                                     6775.170455   \n",
              "2                                     1856.000000   \n",
              "3                                     5504.192893   \n",
              "4                                     2416.283286   \n",
              "\n",
              "   ESC_Renda_per_capita_nos_domicílios  \\\n",
              "0                          1203.946809   \n",
              "1                          2620.725275   \n",
              "2                           586.105263   \n",
              "3                          2362.366013   \n",
              "4                           800.138837   \n",
              "\n",
              "   ESC_Proporção_de_Domicílios_sem_Renda_per_Capita  \\\n",
              "0                                          0.000000   \n",
              "1                                          0.568182   \n",
              "2                                          0.537634   \n",
              "3                                          3.045685   \n",
              "4                                          1.694915   \n",
              "\n",
              "   ESC_Idade_média_das_pessoas_responsáveis  \\\n",
              "0                                 49.696629   \n",
              "1                                 58.312500   \n",
              "2                                 48.112903   \n",
              "3                                 60.406091   \n",
              "4                                 47.954802   \n",
              "\n",
              "   ESC_Rendimento_médio_do_responsável_pelo_domicílio  \\\n",
              "0                                        2405.000000    \n",
              "1                                        5577.102273    \n",
              "2                                        1131.784946    \n",
              "3                                        3624.081218    \n",
              "4                                        1400.566572    \n",
              "\n",
              "   ESC_Proporção_de_pessoas_responsáveis_alfabetizadas  \\\n",
              "0                                          98.876404     \n",
              "1                                          99.431818     \n",
              "2                                          96.236559     \n",
              "3                                         100.000000     \n",
              "4                                          96.327684     \n",
              "\n",
              "   ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos  \\\n",
              "0                                           3.370787       \n",
              "1                                           5.113636       \n",
              "2                                          11.827957       \n",
              "3                                           3.553299       \n",
              "4                                          14.971751       \n",
              "\n",
              "   ESC_Participação_da_renda_do_responsável  \\\n",
              "0                                 63.044714   \n",
              "1                                 82.316782   \n",
              "2                                 60.979792   \n",
              "3                                 65.842191   \n",
              "4                                 57.963674   \n",
              "\n",
              "   ESC_Idade_média_mulheres_respon_pelo_domicílio  \\\n",
              "0                                       49.380952   \n",
              "1                                       63.258427   \n",
              "2                                       48.318841   \n",
              "3                                       62.023077   \n",
              "4                                       48.522936   \n",
              "\n",
              "   ESC_Prop_mulheres_respon_domicílio_alfabet  \\\n",
              "0                                   95.238095   \n",
              "1                                   98.876404   \n",
              "2                                   94.202899   \n",
              "3                                  100.000000   \n",
              "4                                   93.577982   \n",
              "\n",
              "   ESC_Prop_mulheres_respon_domicílio_menos_30_anos  \\\n",
              "0                                         14.285714   \n",
              "1                                          6.741573   \n",
              "2                                         11.594203   \n",
              "3                                          1.538462   \n",
              "4                                         16.513761   \n",
              "\n",
              "   ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio  \\\n",
              "0                                        1516.666667     \n",
              "1                                        8402.943820     \n",
              "2                                         728.884058     \n",
              "3                                        2891.076923     \n",
              "4                                         878.568807     \n",
              "\n",
              "   ESC_Prop_abastecimento_de_água  ESC_Prop_banheiro  \\\n",
              "0                           100.0         100.000000   \n",
              "1                           100.0         100.000000   \n",
              "2                           100.0          97.849462   \n",
              "3                           100.0         100.000000   \n",
              "4                           100.0         100.000000   \n",
              "\n",
              "   ESC_Prop_domicílios_pp_lixo_coletado  \\\n",
              "0                                 100.0   \n",
              "1                                 100.0   \n",
              "2                                 100.0   \n",
              "3                                 100.0   \n",
              "4                                 100.0   \n",
              "\n",
              "   ESC_Prop_domicílios_pp_energia_elétrica  ESC_Pop_total_residente_Mun  \\\n",
              "0                                    100.0                      36686.0   \n",
              "1                                    100.0                      41907.0   \n",
              "2                                    100.0                    1221979.0   \n",
              "3                                    100.0                     586625.0   \n",
              "4                                    100.0                      51242.0   \n",
              "\n",
              "   AL_Código_de_situação_do_setor_censitário  \\\n",
              "0                                        2.0   \n",
              "1                                        1.0   \n",
              "2                                        1.0   \n",
              "3                                        1.0   \n",
              "4                                        1.0   \n",
              "\n",
              "   AL_Setor_é_Aglomerado_subnormal_  AL_Grupo_do_IPVS  \\\n",
              "0                               0.0               4.0   \n",
              "1                               0.0               2.0   \n",
              "2                               0.0               4.0   \n",
              "3                               0.0               2.0   \n",
              "4                               0.0               2.0   \n",
              "\n",
              "   AL_Domicílios_particulares_e_coletivos  \\\n",
              "0                                   263.0   \n",
              "1                                   186.0   \n",
              "2                                    77.0   \n",
              "3                                   209.0   \n",
              "4                                   306.0   \n",
              "\n",
              "   AL_Média_de_moradores_em_domicílios_particulares_permanentes  \\\n",
              "0                                               3.07              \n",
              "1                                               3.15              \n",
              "2                                               3.34              \n",
              "3                                               3.20              \n",
              "4                                               2.94              \n",
              "\n",
              "   AL_Proporção_de_crianças_de_0_a_5_anos_na_população  \\\n",
              "0                                           7.673267     \n",
              "1                                           6.153846     \n",
              "2                                           7.003891     \n",
              "3                                           5.829596     \n",
              "4                                           7.119021     \n",
              "\n",
              "   AL_Rendimento_médio_domiciliar_dos_domicílios  \\\n",
              "0                                    1567.311787   \n",
              "1                                    2949.784946   \n",
              "2                                    1608.532468   \n",
              "3                                    3336.818182   \n",
              "4                                    2522.130719   \n",
              "\n",
              "   AL_Renda_per_capita_nos_domicílios  \\\n",
              "0                          510.152228   \n",
              "1                          937.880342   \n",
              "2                          481.933852   \n",
              "3                         1042.443946   \n",
              "4                          858.478309   \n",
              "\n",
              "   AL_Proporção_de_Domicílios_sem_Renda_per_Capita  \\\n",
              "0                                         0.380228   \n",
              "1                                         1.075269   \n",
              "2                                         2.597403   \n",
              "3                                         1.435407   \n",
              "4                                         1.307190   \n",
              "\n",
              "   AL_Idade_média_das_pessoas_responsáveis  \\\n",
              "0                                47.437262   \n",
              "1                                56.016129   \n",
              "2                                44.467532   \n",
              "3                                48.995215   \n",
              "4                                48.300654   \n",
              "\n",
              "   AL_Rendimento_médio_do_responsável_pelo_domicílio  \\\n",
              "0                                         816.015209   \n",
              "1                                        1752.752688   \n",
              "2                                         769.441558   \n",
              "3                                        1939.569378   \n",
              "4                                        1422.614379   \n",
              "\n",
              "   AL_Proporção_de_pessoas_responsáveis_alfabetizadas  \\\n",
              "0                                          93.155894    \n",
              "1                                          94.623656    \n",
              "2                                          93.506494    \n",
              "3                                          97.607656    \n",
              "4                                          96.078431    \n",
              "\n",
              "   AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos  \\\n",
              "0                                          12.547529      \n",
              "1                                           4.838710      \n",
              "2                                          15.584416      \n",
              "3                                          11.004785      \n",
              "4                                          16.666667      \n",
              "\n",
              "   AL_Participação_da_renda_do_responsável  \\\n",
              "0                                52.064638   \n",
              "1                                59.419677   \n",
              "2                                47.835003   \n",
              "3                                58.126313   \n",
              "4                                56.405260   \n",
              "\n",
              "   AL_Idade_média_mulheres_respon_pelo_domicílio  \\\n",
              "0                                      45.604396   \n",
              "1                                      58.760563   \n",
              "2                                      44.217391   \n",
              "3                                      52.276923   \n",
              "4                                      48.654412   \n",
              "\n",
              "   AL_Prop_mulheres_respon_domicílio_alfabet  \\\n",
              "0                                  94.505495   \n",
              "1                                  90.140845   \n",
              "2                                  91.304348   \n",
              "3                                  93.846154   \n",
              "4                                  93.382353   \n",
              "\n",
              "   AL_Prop_mulheres_respon_domicílio_menos_30_anos  \\\n",
              "0                                        15.384615   \n",
              "1                                         8.450704   \n",
              "2                                        13.043478   \n",
              "3                                        13.846154   \n",
              "4                                        16.911765   \n",
              "\n",
              "   AL_Rend_médio_mulheres_responsáveis_pelo_domicílio  \\\n",
              "0                                         578.527472    \n",
              "1                                        1238.521127    \n",
              "2                                         511.847826    \n",
              "3                                        1351.384615    \n",
              "4                                         782.448529    \n",
              "\n",
              "   AL_Prop_abastecimento_de_água  AL_Prop_banheiro  \\\n",
              "0                      97.338403         98.859316   \n",
              "1                      93.548387         99.462366   \n",
              "2                     100.000000        100.000000   \n",
              "3                      93.301435         96.172249   \n",
              "4                     100.000000         99.346405   \n",
              "\n",
              "   AL_Prop_domicílios_pp_lixo_coletado  \\\n",
              "0                            97.718631   \n",
              "1                            99.462366   \n",
              "2                           100.000000   \n",
              "3                            99.043062   \n",
              "4                           100.000000   \n",
              "\n",
              "   AL_Prop_domicílios_pp_energia_elétrica  AL_Pop_total_residente_Mun  \n",
              "0                                   100.0                     17266.0  \n",
              "1                                   100.0                     41907.0  \n",
              "2                                   100.0                   1221979.0  \n",
              "3                                   100.0                     78821.0  \n",
              "4                                   100.0                     51242.0  "
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "teHV82C7gKHS"
      },
      "source": [
        "# Criando nossos datasets de treino e teste (já basedos em y e X)\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=55) # Aplicando pareto (80/20) e semente 55"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "444odckMgKHT"
      },
      "source": [
        "# Teste 1 - Regressão Logística\n",
        "\n",
        "#from sklearn.linear_model import LogisticRegression\n",
        "\n",
        "#model = LogisticRegression() # % de acurácia (implementação convencional)\n",
        "\n",
        "#model = LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
        "#          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
        "#          penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
        "#          verbose=0, warm_start=False) # 98.735% de acurácia (implementação detalhada)\n",
        "\n",
        "#result = model.fit(X_train, y_train)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ytOYADWUgKHT"
      },
      "source": [
        "from sklearn import metrics\n",
        "#prediction_test = model.predict(X_test)\n",
        "\n",
        "# Predição quanto a acurácia para nosso algoritmo de Regressão Logística\n",
        "\n",
        "#print (metrics.accuracy_score(y_test, prediction_test))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GDNv2ZxSgKHT"
      },
      "source": [
        "# Matriz de confusão simples para nosso algoritmo de Regressão Logística (Teste 1)\n",
        "\n",
        "#from sklearn.metrics import classification_report, confusion_matrix  \n",
        "#print(confusion_matrix(y_test,prediction_test)) "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9mpVhDVrgKHU"
      },
      "source": [
        "# Obtendo pesos/significância para os atributos neste resultado de classificação (mais significativos)\n",
        "\n",
        "#weights = pd.Series(model.coef_[0],\n",
        "#                 index=X.columns.values)\n",
        "#print (weights.sort_values(ascending = False)[:10].plot(kind='bar'))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Btmx7epJgKHU"
      },
      "source": [
        "# Obtendo pesos/significância para os atributos neste resultado de classificação (menos significativos)\n",
        "\n",
        "#print(weights.sort_values(ascending = False)[-10:].plot(kind='bar'))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lKXXnl6AgKHU",
        "outputId": "0fbd07d2-cddf-4a11-f991-59b02706880c"
      },
      "source": [
        "# Teste 2 - Random Forest Algorithm (Floresta Randômica ou Aleatória)\n",
        "\n",
        "# Criando nossos datasets de treino e teste (já basedos em y e X)\n",
        "\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=55)\n",
        "\n",
        "#model_rf = RandomForestClassifier() # % de acurácia (implementação convencional)\n",
        "\n",
        "model_rf = RandomForestClassifier(n_estimators=1000 , oob_score = True, n_jobs = -1,\n",
        "                                  random_state =55, max_features = \"auto\",\n",
        "                                  max_leaf_nodes = 30) # 98.73% de acurácia (RF - implementação detalhada)\n",
        "model_rf.fit(X_train, y_train)\n",
        "\n",
        "# Predição quanto a acurácia para nosso algoritmo de Floresta Randômica\n",
        "\n",
        "prediction_test = model_rf.predict(X_test)\n",
        "print (metrics.accuracy_score(y_test, prediction_test))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "0.9865786068787054\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "627JYDEUgKHV",
        "outputId": "7bc1776c-4c45-4a07-9687-999a282ae23e"
      },
      "source": [
        "# Matriz de confusão simples para nosso algoritmo de Floresta Randômica (Teste 2)\n",
        "\n",
        "from sklearn.metrics import classification_report, confusion_matrix  \n",
        "print(confusion_matrix(y_test,prediction_test)) "
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[[510566     50]\n",
            " [  6900    314]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iR-RoIuegKHV",
        "outputId": "d5b866b8-331d-4ace-e345-f63ef8ee2e4e"
      },
      "source": [
        "# Obtendo pesos/significância para os atributos neste resultado de classificação (mais significativos)\n",
        "\n",
        "importances = model_rf.feature_importances_\n",
        "weights = pd.Series(importances,\n",
        "                 index=X.columns.values)\n",
        "\n",
        "print (weights.sort_values(ascending = False)[:10].plot(kind='bar'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "AxesSubplot(0.125,0.125;0.775x0.755)\n"
          ]
        },
        {
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 576x396 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "do_F453-gKHV",
        "outputId": "1a651e3e-dd6e-45c4-e206-9b3c6807106a"
      },
      "source": [
        "# Obtendo pesos/significância para os atributos neste resultado de classificação (menos significativos)\n",
        "\n",
        "print(weights.sort_values(ascending = False)[-10:].plot(kind='bar'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "AxesSubplot(0.125,0.125;0.775x0.755)\n"
          ]
        },
        {
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 576x396 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z9NevSFzgKHW"
      },
      "source": [
        "# Teste 3 - Algoritmo Support Vector Classifier (SVM like)\n",
        "\n",
        "#from sklearn.svm import SVC\n",
        "\n",
        "#model_svm = SVC(kernel='linear') # 98.61% de acurácia (implementação convencional)\n",
        "\n",
        "#model_svm = SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
        "#               decision_function_shape='ovr', degree=3, gamma=1.0, kernel='linear',\n",
        "#               max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
        "#               tol=0.001, verbose=False) # 98.53% de acurácia (SVC - implementação detalhada)\n",
        "\n",
        "#model_svm.fit(X_train,y_train)\n",
        "#preds = model_svm.predict(X_test)\n",
        "#metrics.accuracy_score(y_test, preds)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G5loJ5PdgKHW"
      },
      "source": [
        "# Matriz de confusão simples para nosso algoritmo SVC (Teste 3)\n",
        "\n",
        "#from sklearn.metrics import classification_report, confusion_matrix  \n",
        "#print(confusion_matrix(y_test,preds))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_XKdX5kIgKHX"
      },
      "source": [
        "# Obtendo pesos/significância para os atributos neste resultado de classificação (mais significativos)\n",
        "\n",
        "#weights = pd.Series(model_svm.coef_[0],\n",
        "#                 index=X.columns.values)\n",
        "#print (weights.sort_values(ascending = False)[:10].plot(kind='bar'))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MU9bIxkRgKHX"
      },
      "source": [
        "# Obtendo pesos/significância para os atributos neste resultado de classificação (menos significativos)\n",
        "\n",
        "#print(weights.sort_values(ascending = False)[-10:].plot(kind='bar'))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hRenmKzagKHX"
      },
      "source": [
        "# Teste 4 - Algoritmo AdaBoost\n",
        "\n",
        "from sklearn.ensemble import AdaBoostClassifier\n",
        "\n",
        "model_ab = AdaBoostClassifier() # 98.885% de acurácia (Adaboost - implementação detalhada)\n",
        "# n_estimators = 50 (default) \n",
        "# base_estimator = DecisionTreeClassifier (default)\n",
        "\n",
        "model_ab.fit(X_train,y_train)\n",
        "preds = model_ab.predict(X_test)\n",
        "metrics.accuracy_score(y_test, preds)\n",
        "\n",
        "print(metrics.accuracy_score(y_test, preds))\n",
        "\n",
        "from sklearn.metrics import classification_report, confusion_matrix  \n",
        "\n",
        "print(confusion_matrix(y_test,preds))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SjaMa5BlgKHY"
      },
      "source": [
        "# Obtendo pesos/significância para os atributos neste resultado de classificação (mais significativos)\n",
        "\n",
        "importances = model_ab.feature_importances_\n",
        "weights = pd.Series(importances,\n",
        "                 index=X.columns.values)\n",
        "\n",
        "print (weights.sort_values(ascending = False)[:10].plot(kind='bar'))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-LgQAcErgKHY"
      },
      "source": [
        "# Obtendo pesos/significância para os atributos neste resultado de classificação (menos significativos)\n",
        "\n",
        "print(weights.sort_values(ascending = False)[-10:].plot(kind='bar'))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "upanMUqQgKHY"
      },
      "source": [
        "# Teste 5 - Algoritmo XGBoost\n",
        "\n",
        "from xgboost import XGBClassifier\n",
        "\n",
        "model_xgb = XGBClassifier() # 99.135% de acurácia (XGBoost - implementação detalhada)\n",
        "\n",
        "model_xgb.fit(X_train, y_train)\n",
        "preds = model_xgb.predict(X_test)\n",
        "metrics.accuracy_score(y_test, preds)\n",
        "print(metrics.accuracy_score(y_test, preds))\n",
        "\n",
        "from sklearn.metrics import classification_report, confusion_matrix  \n",
        "print(confusion_matrix(y_test,preds))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jSxUmMEZgKHY"
      },
      "source": [
        "# Obtendo pesos/significância para os atributos neste resultado de classificação (mais significativos)\n",
        "\n",
        "importances = model_xgb.feature_importances_\n",
        "weights = pd.Series(importances,\n",
        "                 index=X.columns.values)\n",
        "\n",
        "print (weights.sort_values(ascending = False)[:10].plot(kind='bar'))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ws-qM-BlgKHZ"
      },
      "source": [
        "# Obtendo pesos/significância para os atributos neste resultado de classificação (menos significativos)\n",
        "\n",
        "print(weights.sort_values(ascending = False)[-10:].plot(kind='bar'))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WYKZyNpVgKHZ"
      },
      "source": [
        "# Teste 6 - Algoritmo Naive Bayes\n",
        "\n",
        "from sklearn.naive_bayes import GaussianNB\n",
        "\n",
        "model_nb = GaussianNB() # 88.395% de acurácia (Naive Bayes Gaussiano - implementação detalhada)\n",
        "\n",
        "model_nb.fit(X_train, y_train)\n",
        "preds = model_nb.predict(X_test)\n",
        "metrics.accuracy_score(y_test, preds)\n",
        "print(metrics.accuracy_score(y_test, preds))\n",
        "\n",
        "from sklearn.metrics import classification_report, confusion_matrix  \n",
        "print(confusion_matrix(y_test,preds))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JtJ3B6YwgKHZ"
      },
      "source": [
        "# Observação de nosso X_train para verificação quanto a nosso input para classificação\n",
        "\n",
        "#pd.set_option('display.max_columns', None)\n",
        "#X_train.head()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uus3XOh-gKHZ"
      },
      "source": [
        "# Verificação de nossos resultados com oversampling (ex: SMOTE)\n",
        "# Melhores resultados até agora: Regressão Logística, Floresta Randômica e SVC (Atualização: 02/03/2020)\n",
        "\n",
        "#from imblearn.over_sampling import SMOTE\n",
        "\n",
        "#cols    = [i for i in dropout_df.columns if i not in Id_col+target_col]\n",
        "\n",
        "#smote_X = dropout_df[cols]\n",
        "#smote_Y = dropout_df[target_col]\n",
        "\n",
        "# Divisão em dados de treino e teste\n",
        "\n",
        "#smote_train_X,smote_test_X,smote_train_Y,smote_test_Y = train_test_split(smote_X,smote_Y,\n",
        "#                                                                         test_size = .20 ,\n",
        "#                                                                         random_state = 55)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lVPnUS97gKHZ"
      },
      "source": [
        "# Observação de nosso smote_train_X\n",
        "\n",
        "#pd.set_option('display.max_columns', None)\n",
        "#smote_train_X.head()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yY49SdxYgKHa"
      },
      "source": [
        "# Observação de nosso smote_test_X\n",
        "\n",
        "#pd.set_option('display.max_columns', None)\n",
        "#smote_train_X.head()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5RLB42otgKHa"
      },
      "source": [
        "# Oversampling da nossa classe minoritária (evadidos) usando o SMOTE\n",
        "\n",
        "#os = SMOTE(random_state = 0)\n",
        "#os_smote_X,os_smote_Y = os.fit_sample(smote_train_X,smote_train_Y)\n",
        "#os_smote_X = pd.DataFrame(data = os_smote_X,columns=cols)\n",
        "#os_smote_Y = pd.DataFrame(data = os_smote_Y,columns=target_col)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yzkc_ggzgKHa"
      },
      "source": [
        "# Observação de nosso os_smote_X\n",
        "\n",
        "#pd.set_option('display.max_columns', None)\n",
        "#os_smote_X.head()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_oH4y_rxgKHa"
      },
      "source": [
        "# Observação de nosso os_smote_Y\n",
        "\n",
        "#pd.set_option('display.max_columns', None)\n",
        "#os_smote_Y.head()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5Gaqj35qgKHa"
      },
      "source": [
        "# Teste 7 - SMOTE + Regressão Logística\n",
        "\n",
        "'''\n",
        "model_logit_smote = LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
        "          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
        "          penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
        "          verbose=0, warm_start=False) # 94.13% de acurácia (RL + SMOTE - implementação detalhada)\n",
        "\n",
        "result = model_logit_smote.fit(os_smote_X,os_smote_Y.values.ravel())\n",
        "preds = model_logit_smote.predict(smote_test_X)\n",
        "metrics.accuracy_score(smote_test_Y, preds)\n",
        "print(metrics.accuracy_score(smote_test_Y, preds))\n",
        "\n",
        "from sklearn.metrics import classification_report, confusion_matrix   \n",
        "\n",
        "print(\"Report de classificação %s:\\n%s\\n\"\n",
        "      % (result, metrics.classification_report(smote_test_Y,preds)))\n",
        "disp = metrics.plot_confusion_matrix(result, smote_test_X, smote_test_Y)\n",
        "disp.figure_.suptitle(\"Matriz de Confusão\")\n",
        "print(\"Matriz de Confusão:\\n%s\" % disp.confusion_matrix)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0uH6WiJYgKHa"
      },
      "source": [
        "# Teste 8 - SMOTE + Floresta Randômica\n",
        "\n",
        "'''\n",
        "model_rf_smote = RandomForestClassifier(n_estimators=1000 , oob_score = True, n_jobs = -1,\n",
        "                                  random_state =50, max_features = \"auto\",\n",
        "                                  max_leaf_nodes = 30) # 95.775% de acurácia (RF + SMOTE - implementação detalhada)\n",
        "\n",
        "result = model_rf_smote.fit(os_smote_X, os_smote_Y.values.ravel())\n",
        "preds = model_rf_smote.predict(smote_test_X)\n",
        "metrics.accuracy_score(smote_test_Y, preds)\n",
        "print(metrics.accuracy_score(smote_test_Y, preds))\n",
        "\n",
        "from sklearn.metrics import classification_report, confusion_matrix   \n",
        "\n",
        "print(\"Report de classificação %s:\\n%s\\n\"\n",
        "      % (result, metrics.classification_report(smote_test_Y,preds)))\n",
        "disp = metrics.plot_confusion_matrix(result, smote_test_X, smote_test_Y)\n",
        "disp.figure_.suptitle(\"Matriz de Confusão\")\n",
        "print(\"Matriz de Confusão:\\n%s\" % disp.confusion_matrix)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hbIuQG6IgKHb"
      },
      "source": [
        "# Teste 9 - SMOTE + SVC\n",
        "\n",
        "'''\n",
        "model_svm_smote = SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
        "               decision_function_shape='ovr', degree=3, gamma=1.0, kernel='linear',\n",
        "               max_iter=-1, probability=True, random_state=None, shrinking=True,\n",
        "               tol=0.001, verbose=False) # 98.54% de acurácia ( RF + SVC - implementação detalhada)\n",
        "\n",
        "result = model_svm_smote.fit(os_smote_X, os_smote_Y.values.ravel())\n",
        "preds = model_svm_smote.predict(smote_test_X)\n",
        "metrics.accuracy_score(smote_test_Y, preds)\n",
        "print(metrics.accuracy_score(smote_test_Y, preds))\n",
        "\n",
        "from sklearn.metrics import classification_report, confusion_matrix  \n",
        "\n",
        "print(\"Report de classificação %s:\\n%s\\n\"\n",
        "      % (result, metrics.classification_report(smote_test_Y,preds)))\n",
        "disp = metrics.plot_confusion_matrix(result, smote_test_X, smote_test_Y)\n",
        "disp.figure_.suptitle(\"Matriz de Confusão\")\n",
        "print(\"Matriz de Confusão:\\n%s\" % disp.confusion_matrix)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5uo3UWKLgKHb"
      },
      "source": [
        "# Observação de nosso cabeçalho/primeiras 5 linhas, exibição de todas as colunas\n",
        "\n",
        "#pd.set_option('display.max_columns', None)\n",
        "#dropout_df.head()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QlhC6_tBgKHb"
      },
      "source": [
        "# Salvando nossos melhores modelos previamente treinados (via ´Pickle' Ref. https://machinelearningmastery.com/save-load-machine-learning-models-python-scikit-learn/)\n",
        "\n",
        "# Usando o pickle para salvar nosso modelo de Floresta Randômica (Teste 2) para uso posterior\n",
        "\n",
        "import pickle\n",
        "\n",
        "filename = 'dados_evasao/rf_dropout_model.sav'\n",
        "pickle.dump(model_rf, open(filename, 'wb'))\n",
        "\n",
        "# Usando o pickle para salvar nosso modelo de SVC (Teste 3) para uso posterior\n",
        "\n",
        "#filename = 'dados_evasao/svc_dropout_model.sav'\n",
        "#pickle.dump(model_svm, open(filename, 'wb'))\n",
        "\n",
        "# Usando o pickle para salvar nosso modelo SMOTE + Floresta Randômica (Teste 8) para uso posterior\n",
        "\n",
        "#filename = 'dados_evasao/smote_rf_dropout_model.sav'\n",
        "#pickle.dump(model_rf_smote, open(filename, 'wb'))\n",
        "\n",
        "# Usando o pickle para salvar nosso modelo SMOTE + SVC (Teste 9) para uso posterior\n",
        "\n",
        "#filename = 'svm_smote_dropout_model.sav'\n",
        "#pickle.dump(model_svm_smote, open(filename, 'wb'))\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SEFmxqjdgKHb",
        "outputId": "0a4c594d-84b4-4366-b40c-a0d1afecc91d"
      },
      "source": [
        "# Abrindo modelo Floresta Randômica salvo e realizando predição com dados de teste (Ex: X_test, y_test)\n",
        "\n",
        "filename = 'dados_evasao/rf_dropout_model.sav'\n",
        "loaded_model = pickle.load(open(filename, 'rb')) # 98.73% de acurácia\n",
        "result = loaded_model.score(X_test, y_test)\n",
        "print(result)\n",
        "\n",
        "# Abrindo modelo SVC salvo e realizando predição com dados de teste (Ex: X_test, y_test)\n",
        "\n",
        "#filename = 'dados_evasao/svc_dropout_model.sav'\n",
        "#loaded_model = pickle.load(open(filename, 'rb')) # 98.535% de acurácia\n",
        "#result = loaded_model.score(X_test, y_test)\n",
        "#print(result)\n",
        "\n",
        "# Abrindo modelo SMOTE + Floresta Randômica salvo e realizando predição com dados de teste (Ex: smote_test_X, smote_test_Y)\n",
        "\n",
        "#filename = 'dados_evasao/smote_rf_dropout_model.sav'\n",
        "#loaded_model = pickle.load(open(filename, 'rb'))\n",
        "#result = loaded_model.score(smote_test_X, smote_test_Y)\n",
        "#print(result)\n",
        "\n",
        "# Abrindo modelo SMOTE + SVC salvo e realizando predição com dados de teste (Ex: smote_test_X, smote_test_Y)\n",
        "\n",
        "#filename = 'dados_evasao/svm_smote_dropout_model.sav'\n",
        "#loaded_model = pickle.load(open(filename, 'rb'))\n",
        "#result = loaded_model.score(smote_test_X, smote_test_Y)\n",
        "#print(result)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "0.9865786068787054\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d0iycNS9gKHc",
        "outputId": "763c25aa-0fcc-4c5e-88a0-ccaa7d5e9bf9"
      },
      "source": [
        "# Pré processamento de nossa massa de dados de testes (Ex:. dados 2019)\n",
        "\n",
        "dropout_df2 = pd.read_csv(\"dados_evasao/dados_ml_teste_2019_4bimestres.csv\", sep=',', na_values=\" \") # dataset treino - teste completo (+2.500.000 linhas)\n",
        "\n",
        "# Pré-processamento/limpeza de nossos dados (se houver - usando a moda Ref. https://pt.wikipedia.org/wiki/Moda_(estat%C3%ADstica))\n",
        "\n",
        "dropout_df2.fillna(dropout_df2.mode(), inplace=True)\n",
        "\n",
        "# \"Dropando\" CD_MATRICULA_ALUNO, CD_TURMA e CD_ESCOLA\n",
        "\n",
        "dropout_df2.drop(['CD_MATRICULA_ALUNO'],axis=1,inplace=True)\n",
        "dropout_df2.drop(['CD_TURMA'],axis=1,inplace=True)\n",
        "dropout_df2.drop(['CD_ESCOLA'],axis=1,inplace=True)\n",
        "\n",
        "# Fazendo a divisão entre nossas amostras de evadidos/não evadidos (dropout/non-dropout), dados categóricos/numéricos/binários e multi valorados\n",
        "\n",
        "# Separando em evasão/não evasão ((dropout/non-dropout), respectivamente Y=1/Y=0)\n",
        "\n",
        "dropout     = dropout_df2[dropout_df2[\"Y\"] == \"1\"]\n",
        "non_dropout = dropout_df2[dropout_df2[\"Y\"] == \"0\"]\n",
        "\n",
        "# Separando entre colunas categóricas e numéricas\n",
        "\n",
        "Id_col     = ['CD_ALUNO'] # Nossa coluna de identificação CD_ALUNO\n",
        "target_col = [\"Y\"] # Nossa coluna alvo (evasão/não evasão)\n",
        "#cat_cols   = dropout_df2.nunique()[dropout_df2.nunique() < 10].keys().tolist() # Se valores únicos menores que 10 = atributo categórico\n",
        "#cat_cols   = [x for x in cat_cols if x not in target_col] # Excetuando-se target_col\n",
        "#num_cols   = [x for x in dropout_df2.columns if x not in cat_cols + target_col + Id_col] # Qualquer outro caso = atributo numérico\n",
        "\n",
        "# Observando nossos atributos numéricos\n",
        "\n",
        "#print (\"Descrição de nossos atributos numéricos\")\n",
        "\n",
        "#print (\"Rows     : \" ,dropout_df3[num_cols].shape[0])\n",
        "#print (\"Columns  : \" ,dropout_df3[num_cols].shape[1])\n",
        "#print (\"\\nFeatures : \\n\" ,dropout_df3[num_cols].columns.tolist())\n",
        "#print (\"\\nMissing values :  \",dropout_df3[num_cols].isnull().sum().values.sum())\n",
        "#print (\"\\nUnique values :  \\n\",dropout_df3[num_cols].nunique())\n",
        "\n",
        "#dropout_df3[num_cols].head()\n",
        "\n",
        "# Observando nossos atributos binários\n",
        "\n",
        "bin_cols = dropout_df2.nunique()[dropout_df2.nunique() == 2].keys().tolist()\n",
        "\n",
        "# Observando em detalhes nossos atributos binários (Atr ex: Y, TP_SEXO, CD_TIPO_ENSINO e NM_TIPO_ENSINO)\n",
        "\n",
        "#print (\"Descrição de nossos atributos binários\")\n",
        "    \n",
        "#print (\"Rows     : \" ,dropout_df3[bin_cols].shape[0])\n",
        "#print (\"Columns  : \" ,dropout_df3[bin_cols].shape[1])\n",
        "#print (\"\\nFeatures : \\n\" ,dropout_df3[bin_cols].columns.tolist())\n",
        "#print (\"\\nMissing values :  \",dropout_df3[bin_cols].isnull().sum().values.sum())\n",
        "#print (\"\\nUnique values :  \\n\",dropout_df3[bin_cols].nunique())\n",
        "\n",
        "dropout_df2[bin_cols].head()\n",
        "\n",
        "# Observando nossos atributos multi valorados (mais de dois valores)\n",
        "\n",
        "#multi_cols = [i for i in cat_cols if i not in bin_cols]\n",
        "\n",
        "# Observando em detalhes nossos atributos multi valorados (mais de dois valores)\n",
        "\n",
        "#print (\"Descrição de nossos atributos multi valorados\")\n",
        "    \n",
        "#print (\"Rows     : \" ,dropout_df3[multi_cols].shape[0])\n",
        "#print (\"Columns  : \" ,dropout_df3[multi_cols].shape[1])\n",
        "#print (\"\\nFeatures : \\n\" ,dropout_df3[multi_cols].columns.tolist())\n",
        "#print (\"\\nMissing values :  \",dropout_df3[multi_cols].isnull().sum().values.sum())\n",
        "#print (\"\\nUnique values :  \\n\",dropout_df3[multi_cols].nunique())\n",
        "\n",
        "#dropout_df2[multi_cols].head()\n",
        "\n",
        "# Label encoding de nossos atributos numéricos (se necessário)\n",
        "\n",
        "le = LabelEncoder()\n",
        "\n",
        "#for i in num_cols :\n",
        "#    dropout_df2[i] = le.fit_transform(dropout_df2[i])\n",
        "\n",
        "# Label encoding de nossos atributos binários\n",
        "\n",
        "for j in bin_cols :\n",
        "    dropout_df2[j] = le.fit_transform(dropout_df2[j].astype(str))\n",
        "            \n",
        "# Duplicando nossas colunas para atributos multi valorados\n",
        "# Pandas get dummies - Dividindo colunas de dados com vários valores em conjuntos de\n",
        "# colunas booleanas, uma nova coluna para cada valor exclusivo em cada coluna de entrada\n",
        "\n",
        "#dropout_df2[:] = np.nan_to_num(dropout_df2)\n",
        "#dropout_df2 = pd.get_dummies(data = dropout_df2,columns = multi_cols )\n",
        "\n",
        "# Normalização de nossos atributos numéricos (pode-s etestar diferentes tipos de normalização)\n",
        "# Dada uma entrada x, a transformaremos em (x-média) / desvio padrão (onde todas as dimensões e operações estão bem definidas)\n",
        "\n",
        "#std = StandardScaler()\n",
        "#std = MinMaxScaler()\n",
        "#scaled = std.fit_transform(dropout_df2[num_cols])\n",
        "#scaled = pd.DataFrame(scaled,columns=num_cols)\n",
        "\n",
        "# Descartando valores originais mesclando valores dimensionados para nossas colunas numéricas\n",
        "\n",
        "#dropout_df_og2 = dropout_df2.copy()\n",
        "#dropout_df2 = dropout_df2.drop(columns = num_cols,axis = 1)\n",
        "#dropout_df2 = dropout_df2.merge(scaled,left_index=True,right_index=True,how = \"left\")\n",
        "\n",
        "# Verificando valores inf e/ou valores NA e alterando-os com seus valores de moda\n",
        "\n",
        "#col_mask=evasao_train_df2.isnull().any(axis=0)\n",
        "#row_mask=evasao_train_df2.isnull().any(axis=1)\n",
        "\n",
        "#print (col_mask)\n",
        "#print (row_mask)\n",
        "\n",
        "dropout_df2[:] = np.nan_to_num(dropout_df2)\n",
        "\n",
        "#pd.set_option('display.max_columns', None)\n",
        "#dropout_df2.head()\n",
        "\n",
        "# Usaremos o dataframe no qual foram criados nossas variáveis dummy\n",
        "\n",
        "#y = dropout_df2['Y'].values # Atributo alvo\n",
        "#X = dropout_df2.drop(columns = ['Y']) #Demais atributos para classificação"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/home/administrador/anaconda2/envs/py3/lib/python3.8/site-packages/pandas/core/ops/array_ops.py:253: FutureWarning:\n",
            "\n",
            "elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uJWNXuUXgKHc"
      },
      "source": [
        "# Normalização de todos os nossos atributos para um intervalo de de 0 a 1 (já feito anteriormente, contingência visando qualquer eventual erro)\n",
        "\n",
        "#from sklearn.preprocessing import MinMaxScaler\n",
        "#features = X.columns.values\n",
        "#scaler = MinMaxScaler(feature_range = (0,1))\n",
        "#scaler.fit(X)\n",
        "#X = pd.DataFrame(scaler.transform(X))\n",
        "#X.columns = features"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mzvyGLM3gKHc",
        "outputId": "129f0ce8-d3bd-4a0c-b420-610aea36696b"
      },
      "source": [
        "# Observação de nosso cabeçalho/primeiras 5 linhas, exibição de todas as colunas\n",
        "\n",
        "pd.set_option('display.max_columns', None)\n",
        "dropout_df2.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "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>CD_ALUNO</th>\n",
              "      <th>Y</th>\n",
              "      <th>TP_SEXO</th>\n",
              "      <th>VL_IDADE</th>\n",
              "      <th>VL_DISTORCAO</th>\n",
              "      <th>CD_TIPO_ENSINO</th>\n",
              "      <th>NR_SERIE</th>\n",
              "      <th>CD_TURNO</th>\n",
              "      <th>VL_IDESP</th>\n",
              "      <th>VL_REPASSE_ALUNO</th>\n",
              "      <th>VL_INSE</th>\n",
              "      <th>QT_ALUNO_ESCOLA</th>\n",
              "      <th>TX_EVASAO</th>\n",
              "      <th>VL_NOTA_LP</th>\n",
              "      <th>VL_NOTA_GEO</th>\n",
              "      <th>VL_NOTA_HIST</th>\n",
              "      <th>VL_NOTA_MAT</th>\n",
              "      <th>VL_NOTA_ING</th>\n",
              "      <th>VL_NOTA_ART</th>\n",
              "      <th>VL_NOTA_EDFIS</th>\n",
              "      <th>VL_NOTA_CIEN</th>\n",
              "      <th>VL_NOTA_LP2</th>\n",
              "      <th>VL_NOTA_GEO2</th>\n",
              "      <th>VL_NOTA_HIST2</th>\n",
              "      <th>VL_NOTA_MAT2</th>\n",
              "      <th>VL_NOTA_ING2</th>\n",
              "      <th>VL_NOTA_ART2</th>\n",
              "      <th>VL_NOTA_EDFIS2</th>\n",
              "      <th>VL_NOTA_CIEN2</th>\n",
              "      <th>VL_NOTA_LP3</th>\n",
              "      <th>VL_NOTA_GEO3</th>\n",
              "      <th>VL_NOTA_HIST3</th>\n",
              "      <th>VL_NOTA_MAT3</th>\n",
              "      <th>VL_NOTA_ING3</th>\n",
              "      <th>VL_NOTA_ART3</th>\n",
              "      <th>VL_NOTA_EDFIS3</th>\n",
              "      <th>VL_NOTA_CIEN3</th>\n",
              "      <th>VL_NOTA_LP4</th>\n",
              "      <th>VL_NOTA_GEO4</th>\n",
              "      <th>VL_NOTA_HIST4</th>\n",
              "      <th>VL_NOTA_MAT4</th>\n",
              "      <th>VL_NOTA_ING4</th>\n",
              "      <th>VL_NOTA_ART4</th>\n",
              "      <th>VL_NOTA_EDFIS4</th>\n",
              "      <th>VL_NOTA_CIEN4</th>\n",
              "      <th>TX_FREQ_LP</th>\n",
              "      <th>TX_FREQ_GEO</th>\n",
              "      <th>TX_FREQ_HIST</th>\n",
              "      <th>TX_FREQ_MAT</th>\n",
              "      <th>TX_FREQ_ING</th>\n",
              "      <th>TX_FREQ_ART</th>\n",
              "      <th>TX_FREQ_EDFIS</th>\n",
              "      <th>TX_FREQ_CIEN</th>\n",
              "      <th>TX_FREQ_LP2</th>\n",
              "      <th>TX_FREQ_GEO2</th>\n",
              "      <th>TX_FREQ_HIST2</th>\n",
              "      <th>TX_FREQ_MAT2</th>\n",
              "      <th>TX_FREQ_ING2</th>\n",
              "      <th>TX_FREQ_ART2</th>\n",
              "      <th>TX_FREQ_EDFIS2</th>\n",
              "      <th>TX_FREQ_CIEN2</th>\n",
              "      <th>TX_FREQ_LP3</th>\n",
              "      <th>TX_FREQ_GEO3</th>\n",
              "      <th>TX_FREQ_HIST3</th>\n",
              "      <th>TX_FREQ_MAT3</th>\n",
              "      <th>TX_FREQ_ING3</th>\n",
              "      <th>TX_FREQ_ART3</th>\n",
              "      <th>TX_FREQ_EDFIS3</th>\n",
              "      <th>TX_FREQ_CIEN3</th>\n",
              "      <th>TX_FREQ_LP4</th>\n",
              "      <th>TX_FREQ_GEO4</th>\n",
              "      <th>TX_FREQ_HIST4</th>\n",
              "      <th>TX_FREQ_MAT4</th>\n",
              "      <th>TX_FREQ_ING4</th>\n",
              "      <th>TX_FREQ_ART4</th>\n",
              "      <th>TX_FREQ_EDFIS4</th>\n",
              "      <th>TX_FREQ_CIEN4</th>\n",
              "      <th>ESC_Código_de_situação_do_setor_censitário</th>\n",
              "      <th>ESC_Setor_é_Aglomerado_subnormal_</th>\n",
              "      <th>ESC_Grupo_do_IPVS</th>\n",
              "      <th>ESC_Domicílios_particulares_e_coletivos</th>\n",
              "      <th>ESC_Média_de_moradores_em_domicílios_particulares_permanentes</th>\n",
              "      <th>ESC_Proporção_de_crianças_de_0_a_5_anos_na_população</th>\n",
              "      <th>ESC_Rendimento_médio_domiciliar_dos_domicílios</th>\n",
              "      <th>ESC_Renda_per_capita_nos_domicílios</th>\n",
              "      <th>ESC_Proporção_de_Domicílios_sem_Renda_per_Capita</th>\n",
              "      <th>ESC_Idade_média_das_pessoas_responsáveis</th>\n",
              "      <th>ESC_Rendimento_médio_do_responsável_pelo_domicílio</th>\n",
              "      <th>ESC_Proporção_de_pessoas_responsáveis_alfabetizadas</th>\n",
              "      <th>ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos</th>\n",
              "      <th>ESC_Participação_da_renda_do_responsável</th>\n",
              "      <th>ESC_Idade_média_mulheres_respon_pelo_domicílio</th>\n",
              "      <th>ESC_Prop_mulheres_respon_domicílio_alfabet</th>\n",
              "      <th>ESC_Prop_mulheres_respon_domicílio_menos_30_anos</th>\n",
              "      <th>ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio</th>\n",
              "      <th>ESC_Prop_abastecimento_de_água</th>\n",
              "      <th>ESC_Prop_banheiro</th>\n",
              "      <th>ESC_Prop_domicílios_pp_lixo_coletado</th>\n",
              "      <th>ESC_Prop_domicílios_pp_energia_elétrica</th>\n",
              "      <th>ESC_Pop_total_residente_Mun</th>\n",
              "      <th>AL_Código_de_situação_do_setor_censitário</th>\n",
              "      <th>AL_Setor_é_Aglomerado_subnormal_</th>\n",
              "      <th>AL_Grupo_do_IPVS</th>\n",
              "      <th>AL_Domicílios_particulares_e_coletivos</th>\n",
              "      <th>AL_Média_de_moradores_em_domicílios_particulares_permanentes</th>\n",
              "      <th>AL_Proporção_de_crianças_de_0_a_5_anos_na_população</th>\n",
              "      <th>AL_Rendimento_médio_domiciliar_dos_domicílios</th>\n",
              "      <th>AL_Renda_per_capita_nos_domicílios</th>\n",
              "      <th>AL_Proporção_de_Domicílios_sem_Renda_per_Capita</th>\n",
              "      <th>AL_Idade_média_das_pessoas_responsáveis</th>\n",
              "      <th>AL_Rendimento_médio_do_responsável_pelo_domicílio</th>\n",
              "      <th>AL_Proporção_de_pessoas_responsáveis_alfabetizadas</th>\n",
              "      <th>AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos</th>\n",
              "      <th>AL_Participação_da_renda_do_responsável</th>\n",
              "      <th>AL_Idade_média_mulheres_respon_pelo_domicílio</th>\n",
              "      <th>AL_Prop_mulheres_respon_domicílio_alfabet</th>\n",
              "      <th>AL_Prop_mulheres_respon_domicílio_menos_30_anos</th>\n",
              "      <th>AL_Rend_médio_mulheres_responsáveis_pelo_domicílio</th>\n",
              "      <th>AL_Prop_abastecimento_de_água</th>\n",
              "      <th>AL_Prop_banheiro</th>\n",
              "      <th>AL_Prop_domicílios_pp_lixo_coletado</th>\n",
              "      <th>AL_Prop_domicílios_pp_energia_elétrica</th>\n",
              "      <th>AL_Pop_total_residente_Mun</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>21935885.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>19.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.06</td>\n",
              "      <td>40.2806</td>\n",
              "      <td>5.97</td>\n",
              "      <td>926.0</td>\n",
              "      <td>0.0400</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.7000</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.7778</td>\n",
              "      <td>0.8378</td>\n",
              "      <td>0.5556</td>\n",
              "      <td>0.7000</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.6271</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.900</td>\n",
              "      <td>0.0833</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.90</td>\n",
              "      <td>0.8750</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.9500</td>\n",
              "      <td>0.900</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.9500</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>276.0</td>\n",
              "      <td>3.485507</td>\n",
              "      <td>12.058212</td>\n",
              "      <td>945.713768</td>\n",
              "      <td>271.327443</td>\n",
              "      <td>24.637681</td>\n",
              "      <td>38.510870</td>\n",
              "      <td>361.898551</td>\n",
              "      <td>90.579710</td>\n",
              "      <td>33.695652</td>\n",
              "      <td>38.267239</td>\n",
              "      <td>37.396739</td>\n",
              "      <td>91.304348</td>\n",
              "      <td>35.869565</td>\n",
              "      <td>268.777174</td>\n",
              "      <td>89.855072</td>\n",
              "      <td>62.681159</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>11253503.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>276.0</td>\n",
              "      <td>3.485507</td>\n",
              "      <td>12.058212</td>\n",
              "      <td>945.713768</td>\n",
              "      <td>271.327443</td>\n",
              "      <td>24.637681</td>\n",
              "      <td>38.510870</td>\n",
              "      <td>361.898551</td>\n",
              "      <td>90.579710</td>\n",
              "      <td>33.695652</td>\n",
              "      <td>38.267239</td>\n",
              "      <td>37.396739</td>\n",
              "      <td>91.304348</td>\n",
              "      <td>35.869565</td>\n",
              "      <td>268.777174</td>\n",
              "      <td>89.855072</td>\n",
              "      <td>62.681159</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>11253503.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>22472255.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.85</td>\n",
              "      <td>53.4927</td>\n",
              "      <td>4.54</td>\n",
              "      <td>995.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.9250</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8500</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.9355</td>\n",
              "      <td>0.9250</td>\n",
              "      <td>0.100</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9250</td>\n",
              "      <td>0.8947</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.8730</td>\n",
              "      <td>0.9250</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8500</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9310</td>\n",
              "      <td>0.925</td>\n",
              "      <td>0.4</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9048</td>\n",
              "      <td>0.8571</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.9355</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>204.0</td>\n",
              "      <td>2.520000</td>\n",
              "      <td>5.048544</td>\n",
              "      <td>2548.593137</td>\n",
              "      <td>1009.539806</td>\n",
              "      <td>12.745098</td>\n",
              "      <td>57.828431</td>\n",
              "      <td>1703.789216</td>\n",
              "      <td>97.549020</td>\n",
              "      <td>5.392157</td>\n",
              "      <td>66.852146</td>\n",
              "      <td>62.148148</td>\n",
              "      <td>95.061728</td>\n",
              "      <td>3.703704</td>\n",
              "      <td>1178.395062</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>99.509804</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>53158.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>154.0</td>\n",
              "      <td>3.730000</td>\n",
              "      <td>11.846690</td>\n",
              "      <td>892.311688</td>\n",
              "      <td>239.400697</td>\n",
              "      <td>16.233766</td>\n",
              "      <td>40.428571</td>\n",
              "      <td>482.487013</td>\n",
              "      <td>79.220779</td>\n",
              "      <td>22.727273</td>\n",
              "      <td>54.071578</td>\n",
              "      <td>43.375000</td>\n",
              "      <td>77.083333</td>\n",
              "      <td>18.750000</td>\n",
              "      <td>355.291667</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>53158.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>17568090.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.96</td>\n",
              "      <td>42.4715</td>\n",
              "      <td>2.67</td>\n",
              "      <td>1199.0</td>\n",
              "      <td>0.0467</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.9524</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>0.7826</td>\n",
              "      <td>0.9130</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.7273</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.7429</td>\n",
              "      <td>0.8485</td>\n",
              "      <td>0.875</td>\n",
              "      <td>0.6667</td>\n",
              "      <td>0.8182</td>\n",
              "      <td>0.6250</td>\n",
              "      <td>0.6875</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.7447</td>\n",
              "      <td>0.9773</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8235</td>\n",
              "      <td>0.8788</td>\n",
              "      <td>0.7778</td>\n",
              "      <td>0.7778</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.975</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.9565</td>\n",
              "      <td>0.8864</td>\n",
              "      <td>0.8636</td>\n",
              "      <td>0.8500</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.8788</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>121.0</td>\n",
              "      <td>2.290000</td>\n",
              "      <td>2.941176</td>\n",
              "      <td>3303.680672</td>\n",
              "      <td>1445.360294</td>\n",
              "      <td>0.840336</td>\n",
              "      <td>58.932773</td>\n",
              "      <td>2452.731092</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>2.521008</td>\n",
              "      <td>74.242378</td>\n",
              "      <td>61.093750</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>1.562500</td>\n",
              "      <td>1768.093750</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>87057.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>210.0</td>\n",
              "      <td>3.530000</td>\n",
              "      <td>10.931174</td>\n",
              "      <td>1217.385714</td>\n",
              "      <td>345.008097</td>\n",
              "      <td>3.809524</td>\n",
              "      <td>48.623810</td>\n",
              "      <td>704.842857</td>\n",
              "      <td>90.952381</td>\n",
              "      <td>11.904762</td>\n",
              "      <td>57.898072</td>\n",
              "      <td>51.082474</td>\n",
              "      <td>85.567010</td>\n",
              "      <td>8.247423</td>\n",
              "      <td>501.494845</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>85.714286</td>\n",
              "      <td>99.52381</td>\n",
              "      <td>99.52381</td>\n",
              "      <td>87057.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>35284840.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.49</td>\n",
              "      <td>35.0169</td>\n",
              "      <td>4.60</td>\n",
              "      <td>1005.0</td>\n",
              "      <td>0.0826</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>392.0</td>\n",
              "      <td>2.843750</td>\n",
              "      <td>17.582418</td>\n",
              "      <td>3009.544643</td>\n",
              "      <td>1058.301413</td>\n",
              "      <td>4.824561</td>\n",
              "      <td>41.707692</td>\n",
              "      <td>1801.187500</td>\n",
              "      <td>93.538462</td>\n",
              "      <td>25.846154</td>\n",
              "      <td>59.849170</td>\n",
              "      <td>41.047945</td>\n",
              "      <td>94.520548</td>\n",
              "      <td>23.972603</td>\n",
              "      <td>1324.573034</td>\n",
              "      <td>96.428571</td>\n",
              "      <td>99.553571</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>11253503.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>167.0</td>\n",
              "      <td>3.167665</td>\n",
              "      <td>7.372401</td>\n",
              "      <td>2338.550898</td>\n",
              "      <td>738.257089</td>\n",
              "      <td>3.592814</td>\n",
              "      <td>42.281437</td>\n",
              "      <td>1184.562874</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>22.155689</td>\n",
              "      <td>50.653714</td>\n",
              "      <td>43.471429</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>18.571429</td>\n",
              "      <td>892.257143</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>11253503.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>21792155.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.50</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>2.90</td>\n",
              "      <td>1653.0</td>\n",
              "      <td>0.0175</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.9400</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8913</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.9667</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8077</td>\n",
              "      <td>0.6000</td>\n",
              "      <td>0.8182</td>\n",
              "      <td>0.85</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.8400</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9500</td>\n",
              "      <td>0.8667</td>\n",
              "      <td>0.860</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.8627</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.9091</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.8667</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>3.124542</td>\n",
              "      <td>6.447831</td>\n",
              "      <td>2182.307692</td>\n",
              "      <td>698.440797</td>\n",
              "      <td>1.465201</td>\n",
              "      <td>49.307692</td>\n",
              "      <td>1163.509158</td>\n",
              "      <td>97.802198</td>\n",
              "      <td>10.989011</td>\n",
              "      <td>53.315541</td>\n",
              "      <td>52.267327</td>\n",
              "      <td>96.039604</td>\n",
              "      <td>7.920792</td>\n",
              "      <td>948.554455</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>99.633700</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>11253503.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>184.0</td>\n",
              "      <td>3.448087</td>\n",
              "      <td>6.339144</td>\n",
              "      <td>1846.639344</td>\n",
              "      <td>535.554675</td>\n",
              "      <td>3.260870</td>\n",
              "      <td>48.081522</td>\n",
              "      <td>963.153005</td>\n",
              "      <td>92.391304</td>\n",
              "      <td>13.043478</td>\n",
              "      <td>52.157072</td>\n",
              "      <td>52.309859</td>\n",
              "      <td>90.140845</td>\n",
              "      <td>7.042254</td>\n",
              "      <td>650.112676</td>\n",
              "      <td>99.453552</td>\n",
              "      <td>95.081967</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>11253503.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     CD_ALUNO    Y  TP_SEXO  VL_IDADE  VL_DISTORCAO  CD_TIPO_ENSINO  NR_SERIE  \\\n",
              "0  21935885.0  1.0      1.0      19.0           4.0             1.0       1.0   \n",
              "1  22472255.0  0.0      1.0      16.0           0.0             1.0       2.0   \n",
              "2  17568090.0  0.0      0.0      18.0           2.0             1.0       2.0   \n",
              "3  35284840.0  0.0      1.0      17.0           6.0             0.0       6.0   \n",
              "4  21792155.0  0.0      1.0      16.0           0.0             1.0       2.0   \n",
              "\n",
              "   CD_TURNO  VL_IDESP  VL_REPASSE_ALUNO  VL_INSE  QT_ALUNO_ESCOLA  TX_EVASAO  \\\n",
              "0       5.0      2.06           40.2806     5.97            926.0     0.0400   \n",
              "1       5.0      2.85           53.4927     4.54            995.0     0.0000   \n",
              "2       5.0      1.96           42.4715     2.67           1199.0     0.0467   \n",
              "3       3.0      2.49           35.0169     4.60           1005.0     0.0826   \n",
              "4       1.0      2.50            0.0000     2.90           1653.0     0.0175   \n",
              "\n",
              "   VL_NOTA_LP  VL_NOTA_GEO  VL_NOTA_HIST  VL_NOTA_MAT  VL_NOTA_ING  \\\n",
              "0         2.0          2.0           1.0          2.0          1.0   \n",
              "1         7.0          7.0           7.0          6.0          9.0   \n",
              "2         4.0          5.0           4.0          5.0         10.0   \n",
              "3         0.0          0.0           0.0          0.0          0.0   \n",
              "4         4.0          8.0           6.0          7.0          7.0   \n",
              "\n",
              "   VL_NOTA_ART  VL_NOTA_EDFIS  VL_NOTA_CIEN  VL_NOTA_LP2  VL_NOTA_GEO2  \\\n",
              "0          3.0            8.0           2.0          0.0           0.0   \n",
              "1         10.0            0.0           7.0          7.0           3.0   \n",
              "2          4.0            0.0           4.0          2.0           6.0   \n",
              "3          0.0            0.0           0.0          0.0           0.0   \n",
              "4          6.0            9.0           7.0          5.0           5.0   \n",
              "\n",
              "   VL_NOTA_HIST2  VL_NOTA_MAT2  VL_NOTA_ING2  VL_NOTA_ART2  VL_NOTA_EDFIS2  \\\n",
              "0            0.0           5.0           0.0           5.0             8.0   \n",
              "1            8.0           7.0           7.0           8.0             0.0   \n",
              "2            5.0           5.0           3.0           5.0             0.0   \n",
              "3            0.0           0.0           0.0           0.0             0.0   \n",
              "4            7.0           5.0           3.0           5.0             6.0   \n",
              "\n",
              "   VL_NOTA_CIEN2  VL_NOTA_LP3  VL_NOTA_GEO3  VL_NOTA_HIST3  VL_NOTA_MAT3  \\\n",
              "0            5.0          5.0           0.0            0.0           5.0   \n",
              "1            6.0          8.0           5.0            8.0           9.0   \n",
              "2            4.0          5.0           7.0            6.0           5.0   \n",
              "3            0.0          0.0           0.0            0.0           0.0   \n",
              "4            5.0          5.0           8.0            8.0           7.0   \n",
              "\n",
              "   VL_NOTA_ING3  VL_NOTA_ART3  VL_NOTA_EDFIS3  VL_NOTA_CIEN3  VL_NOTA_LP4  \\\n",
              "0           0.0           5.0             8.0            5.0          5.0   \n",
              "1          10.0           8.0             0.0            7.0          7.0   \n",
              "2           7.0           7.0             0.0            6.0          8.0   \n",
              "3           0.0           0.0             0.0            0.0          0.0   \n",
              "4           7.0           7.0             7.0            6.0          6.0   \n",
              "\n",
              "   VL_NOTA_GEO4  VL_NOTA_HIST4  VL_NOTA_MAT4  VL_NOTA_ING4  VL_NOTA_ART4  \\\n",
              "0           0.0            0.0           5.0           5.0           5.0   \n",
              "1           4.0           10.0          10.0           7.0          10.0   \n",
              "2           0.0            6.0           6.0           7.0           7.0   \n",
              "3           0.0            0.0           0.0           0.0           0.0   \n",
              "4           8.0            8.0           6.0           5.0           7.0   \n",
              "\n",
              "   VL_NOTA_EDFIS4  VL_NOTA_CIEN4  TX_FREQ_LP  TX_FREQ_GEO  TX_FREQ_HIST  \\\n",
              "0             8.0            5.0      0.7000       0.8333        0.7778   \n",
              "1             0.0            7.0      0.9250       0.0000        0.8500   \n",
              "2             0.0            5.0      0.9524       0.8800        0.7826   \n",
              "3             0.0            0.0      0.0000       0.0000        0.0000   \n",
              "4             9.0            6.0      0.9400       0.0000        0.8000   \n",
              "\n",
              "   TX_FREQ_MAT  TX_FREQ_ING  TX_FREQ_ART  TX_FREQ_EDFIS  TX_FREQ_CIEN  \\\n",
              "0       0.8378       0.5556       0.7000            0.9        0.6271   \n",
              "1       0.0000       0.0000       0.0000            0.0        0.9355   \n",
              "2       0.9130       0.0000       0.7273            0.0        0.7429   \n",
              "3       0.0000       0.0000       0.0000            0.0        0.0000   \n",
              "4       0.8913       0.8000       0.8000            0.0        0.9667   \n",
              "\n",
              "   TX_FREQ_LP2  TX_FREQ_GEO2  TX_FREQ_HIST2  TX_FREQ_MAT2  TX_FREQ_ING2  \\\n",
              "0       0.0000         0.900         0.0833        0.9000        0.0000   \n",
              "1       0.9250         0.100         0.9000        0.9250        0.8947   \n",
              "2       0.8485         0.875         0.6667        0.8182        0.6250   \n",
              "3       0.0000         0.000         0.0000        0.0000        0.0000   \n",
              "4       0.9000         0.000         0.8000        0.8077        0.6000   \n",
              "\n",
              "   TX_FREQ_ART2  TX_FREQ_EDFIS2  TX_FREQ_CIEN2  TX_FREQ_LP3  TX_FREQ_GEO3  \\\n",
              "0        0.9000            0.90         0.8750       0.9000        0.8889   \n",
              "1        0.0000            0.00         0.8730       0.9250        0.8000   \n",
              "2        0.6875            0.00         0.7447       0.9773        0.0000   \n",
              "3        0.0000            0.00         0.0000       0.0000        0.0000   \n",
              "4        0.8182            0.85         0.8333       0.8400        0.8000   \n",
              "\n",
              "   TX_FREQ_HIST3  TX_FREQ_MAT3  TX_FREQ_ING3  TX_FREQ_ART3  TX_FREQ_EDFIS3  \\\n",
              "0         0.8889        0.9000        0.0000        0.8889          0.8889   \n",
              "1         0.8500        0.9167        0.0000        0.9412          0.0000   \n",
              "2         0.8235        0.8788        0.7778        0.7778          0.0000   \n",
              "3         0.0000        0.0000        0.0000        0.0000          0.0000   \n",
              "4         0.0000        0.8800        0.8000        0.0000          0.9500   \n",
              "\n",
              "   TX_FREQ_CIEN3  TX_FREQ_LP4  TX_FREQ_GEO4  TX_FREQ_HIST4  TX_FREQ_MAT4  \\\n",
              "0         0.9500        0.900           0.9         0.9000        0.9000   \n",
              "1         0.9310        0.925           0.4         0.9000        0.9048   \n",
              "2         0.9000        0.975           0.0         0.9565        0.8864   \n",
              "3         0.0000        0.000           0.0         0.0000        0.0000   \n",
              "4         0.8667        0.860           0.9         0.9000        0.8627   \n",
              "\n",
              "   TX_FREQ_ING4  TX_FREQ_ART4  TX_FREQ_EDFIS4  TX_FREQ_CIEN4  \\\n",
              "0        0.9000        0.9000             0.9         0.9500   \n",
              "1        0.8571        0.0000             0.0         0.9355   \n",
              "2        0.8636        0.8500             0.0         0.8788   \n",
              "3        0.0000        0.0000             0.0         0.0000   \n",
              "4        0.8000        0.9091             0.9         0.8667   \n",
              "\n",
              "   ESC_Código_de_situação_do_setor_censitário  \\\n",
              "0                                         3.0   \n",
              "1                                         1.0   \n",
              "2                                         1.0   \n",
              "3                                         1.0   \n",
              "4                                         1.0   \n",
              "\n",
              "   ESC_Setor_é_Aglomerado_subnormal_  ESC_Grupo_do_IPVS  \\\n",
              "0                                0.0                5.0   \n",
              "1                                0.0                2.0   \n",
              "2                                0.0                2.0   \n",
              "3                                0.0                3.0   \n",
              "4                                0.0                2.0   \n",
              "\n",
              "   ESC_Domicílios_particulares_e_coletivos  \\\n",
              "0                                    276.0   \n",
              "1                                    204.0   \n",
              "2                                    121.0   \n",
              "3                                    392.0   \n",
              "4                                    273.0   \n",
              "\n",
              "   ESC_Média_de_moradores_em_domicílios_particulares_permanentes  \\\n",
              "0                                           3.485507               \n",
              "1                                           2.520000               \n",
              "2                                           2.290000               \n",
              "3                                           2.843750               \n",
              "4                                           3.124542               \n",
              "\n",
              "   ESC_Proporção_de_crianças_de_0_a_5_anos_na_população  \\\n",
              "0                                          12.058212      \n",
              "1                                           5.048544      \n",
              "2                                           2.941176      \n",
              "3                                          17.582418      \n",
              "4                                           6.447831      \n",
              "\n",
              "   ESC_Rendimento_médio_domiciliar_dos_domicílios  \\\n",
              "0                                      945.713768   \n",
              "1                                     2548.593137   \n",
              "2                                     3303.680672   \n",
              "3                                     3009.544643   \n",
              "4                                     2182.307692   \n",
              "\n",
              "   ESC_Renda_per_capita_nos_domicílios  \\\n",
              "0                           271.327443   \n",
              "1                          1009.539806   \n",
              "2                          1445.360294   \n",
              "3                          1058.301413   \n",
              "4                           698.440797   \n",
              "\n",
              "   ESC_Proporção_de_Domicílios_sem_Renda_per_Capita  \\\n",
              "0                                         24.637681   \n",
              "1                                         12.745098   \n",
              "2                                          0.840336   \n",
              "3                                          4.824561   \n",
              "4                                          1.465201   \n",
              "\n",
              "   ESC_Idade_média_das_pessoas_responsáveis  \\\n",
              "0                                 38.510870   \n",
              "1                                 57.828431   \n",
              "2                                 58.932773   \n",
              "3                                 41.707692   \n",
              "4                                 49.307692   \n",
              "\n",
              "   ESC_Rendimento_médio_do_responsável_pelo_domicílio  \\\n",
              "0                                         361.898551    \n",
              "1                                        1703.789216    \n",
              "2                                        2452.731092    \n",
              "3                                        1801.187500    \n",
              "4                                        1163.509158    \n",
              "\n",
              "   ESC_Proporção_de_pessoas_responsáveis_alfabetizadas  \\\n",
              "0                                          90.579710     \n",
              "1                                          97.549020     \n",
              "2                                         100.000000     \n",
              "3                                          93.538462     \n",
              "4                                          97.802198     \n",
              "\n",
              "   ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos  \\\n",
              "0                                          33.695652       \n",
              "1                                           5.392157       \n",
              "2                                           2.521008       \n",
              "3                                          25.846154       \n",
              "4                                          10.989011       \n",
              "\n",
              "   ESC_Participação_da_renda_do_responsável  \\\n",
              "0                                 38.267239   \n",
              "1                                 66.852146   \n",
              "2                                 74.242378   \n",
              "3                                 59.849170   \n",
              "4                                 53.315541   \n",
              "\n",
              "   ESC_Idade_média_mulheres_respon_pelo_domicílio  \\\n",
              "0                                       37.396739   \n",
              "1                                       62.148148   \n",
              "2                                       61.093750   \n",
              "3                                       41.047945   \n",
              "4                                       52.267327   \n",
              "\n",
              "   ESC_Prop_mulheres_respon_domicílio_alfabet  \\\n",
              "0                                   91.304348   \n",
              "1                                   95.061728   \n",
              "2                                  100.000000   \n",
              "3                                   94.520548   \n",
              "4                                   96.039604   \n",
              "\n",
              "   ESC_Prop_mulheres_respon_domicílio_menos_30_anos  \\\n",
              "0                                         35.869565   \n",
              "1                                          3.703704   \n",
              "2                                          1.562500   \n",
              "3                                         23.972603   \n",
              "4                                          7.920792   \n",
              "\n",
              "   ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio  \\\n",
              "0                                         268.777174     \n",
              "1                                        1178.395062     \n",
              "2                                        1768.093750     \n",
              "3                                        1324.573034     \n",
              "4                                         948.554455     \n",
              "\n",
              "   ESC_Prop_abastecimento_de_água  ESC_Prop_banheiro  \\\n",
              "0                       89.855072          62.681159   \n",
              "1                      100.000000          99.509804   \n",
              "2                      100.000000         100.000000   \n",
              "3                       96.428571          99.553571   \n",
              "4                      100.000000          99.633700   \n",
              "\n",
              "   ESC_Prop_domicílios_pp_lixo_coletado  \\\n",
              "0                                 100.0   \n",
              "1                                 100.0   \n",
              "2                                 100.0   \n",
              "3                                 100.0   \n",
              "4                                 100.0   \n",
              "\n",
              "   ESC_Prop_domicílios_pp_energia_elétrica  ESC_Pop_total_residente_Mun  \\\n",
              "0                                    100.0                   11253503.0   \n",
              "1                                    100.0                      53158.0   \n",
              "2                                    100.0                      87057.0   \n",
              "3                                    100.0                   11253503.0   \n",
              "4                                    100.0                   11253503.0   \n",
              "\n",
              "   AL_Código_de_situação_do_setor_censitário  \\\n",
              "0                                        3.0   \n",
              "1                                        1.0   \n",
              "2                                        1.0   \n",
              "3                                        1.0   \n",
              "4                                        1.0   \n",
              "\n",
              "   AL_Setor_é_Aglomerado_subnormal_  AL_Grupo_do_IPVS  \\\n",
              "0                               0.0               5.0   \n",
              "1                               0.0               5.0   \n",
              "2                               0.0               4.0   \n",
              "3                               0.0               3.0   \n",
              "4                               0.0               4.0   \n",
              "\n",
              "   AL_Domicílios_particulares_e_coletivos  \\\n",
              "0                                   276.0   \n",
              "1                                   154.0   \n",
              "2                                   210.0   \n",
              "3                                   167.0   \n",
              "4                                   184.0   \n",
              "\n",
              "   AL_Média_de_moradores_em_domicílios_particulares_permanentes  \\\n",
              "0                                           3.485507              \n",
              "1                                           3.730000              \n",
              "2                                           3.530000              \n",
              "3                                           3.167665              \n",
              "4                                           3.448087              \n",
              "\n",
              "   AL_Proporção_de_crianças_de_0_a_5_anos_na_população  \\\n",
              "0                                          12.058212     \n",
              "1                                          11.846690     \n",
              "2                                          10.931174     \n",
              "3                                           7.372401     \n",
              "4                                           6.339144     \n",
              "\n",
              "   AL_Rendimento_médio_domiciliar_dos_domicílios  \\\n",
              "0                                     945.713768   \n",
              "1                                     892.311688   \n",
              "2                                    1217.385714   \n",
              "3                                    2338.550898   \n",
              "4                                    1846.639344   \n",
              "\n",
              "   AL_Renda_per_capita_nos_domicílios  \\\n",
              "0                          271.327443   \n",
              "1                          239.400697   \n",
              "2                          345.008097   \n",
              "3                          738.257089   \n",
              "4                          535.554675   \n",
              "\n",
              "   AL_Proporção_de_Domicílios_sem_Renda_per_Capita  \\\n",
              "0                                        24.637681   \n",
              "1                                        16.233766   \n",
              "2                                         3.809524   \n",
              "3                                         3.592814   \n",
              "4                                         3.260870   \n",
              "\n",
              "   AL_Idade_média_das_pessoas_responsáveis  \\\n",
              "0                                38.510870   \n",
              "1                                40.428571   \n",
              "2                                48.623810   \n",
              "3                                42.281437   \n",
              "4                                48.081522   \n",
              "\n",
              "   AL_Rendimento_médio_do_responsável_pelo_domicílio  \\\n",
              "0                                         361.898551   \n",
              "1                                         482.487013   \n",
              "2                                         704.842857   \n",
              "3                                        1184.562874   \n",
              "4                                         963.153005   \n",
              "\n",
              "   AL_Proporção_de_pessoas_responsáveis_alfabetizadas  \\\n",
              "0                                          90.579710    \n",
              "1                                          79.220779    \n",
              "2                                          90.952381    \n",
              "3                                         100.000000    \n",
              "4                                          92.391304    \n",
              "\n",
              "   AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos  \\\n",
              "0                                          33.695652      \n",
              "1                                          22.727273      \n",
              "2                                          11.904762      \n",
              "3                                          22.155689      \n",
              "4                                          13.043478      \n",
              "\n",
              "   AL_Participação_da_renda_do_responsável  \\\n",
              "0                                38.267239   \n",
              "1                                54.071578   \n",
              "2                                57.898072   \n",
              "3                                50.653714   \n",
              "4                                52.157072   \n",
              "\n",
              "   AL_Idade_média_mulheres_respon_pelo_domicílio  \\\n",
              "0                                      37.396739   \n",
              "1                                      43.375000   \n",
              "2                                      51.082474   \n",
              "3                                      43.471429   \n",
              "4                                      52.309859   \n",
              "\n",
              "   AL_Prop_mulheres_respon_domicílio_alfabet  \\\n",
              "0                                  91.304348   \n",
              "1                                  77.083333   \n",
              "2                                  85.567010   \n",
              "3                                 100.000000   \n",
              "4                                  90.140845   \n",
              "\n",
              "   AL_Prop_mulheres_respon_domicílio_menos_30_anos  \\\n",
              "0                                        35.869565   \n",
              "1                                        18.750000   \n",
              "2                                         8.247423   \n",
              "3                                        18.571429   \n",
              "4                                         7.042254   \n",
              "\n",
              "   AL_Rend_médio_mulheres_responsáveis_pelo_domicílio  \\\n",
              "0                                         268.777174    \n",
              "1                                         355.291667    \n",
              "2                                         501.494845    \n",
              "3                                         892.257143    \n",
              "4                                         650.112676    \n",
              "\n",
              "   AL_Prop_abastecimento_de_água  AL_Prop_banheiro  \\\n",
              "0                      89.855072         62.681159   \n",
              "1                     100.000000        100.000000   \n",
              "2                     100.000000         85.714286   \n",
              "3                     100.000000        100.000000   \n",
              "4                      99.453552         95.081967   \n",
              "\n",
              "   AL_Prop_domicílios_pp_lixo_coletado  \\\n",
              "0                            100.00000   \n",
              "1                            100.00000   \n",
              "2                             99.52381   \n",
              "3                            100.00000   \n",
              "4                            100.00000   \n",
              "\n",
              "   AL_Prop_domicílios_pp_energia_elétrica  AL_Pop_total_residente_Mun  \n",
              "0                               100.00000                  11253503.0  \n",
              "1                               100.00000                     53158.0  \n",
              "2                                99.52381                     87057.0  \n",
              "3                               100.00000                  11253503.0  \n",
              "4                               100.00000                  11253503.0  "
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ybCNjGRjgKHc"
      },
      "source": [
        "# \"Dropando\" nosso atributo quanto a evasão (Y)\n",
        "\n",
        "dropout_df2.drop(['Y'],axis=1,inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2mmTlgHEgKHd",
        "outputId": "8226f791-6c4d-4366-e4e9-5ccf290b57e7"
      },
      "source": [
        "# Observação de nosso cabeçalho/primeiras 5 linhas, exibição de todas as colunas\n",
        "\n",
        "pd.set_option('display.max_columns', None)\n",
        "dropout_df2.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "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>CD_ALUNO</th>\n",
              "      <th>TP_SEXO</th>\n",
              "      <th>VL_IDADE</th>\n",
              "      <th>VL_DISTORCAO</th>\n",
              "      <th>CD_TIPO_ENSINO</th>\n",
              "      <th>NR_SERIE</th>\n",
              "      <th>CD_TURNO</th>\n",
              "      <th>VL_IDESP</th>\n",
              "      <th>VL_REPASSE_ALUNO</th>\n",
              "      <th>VL_INSE</th>\n",
              "      <th>QT_ALUNO_ESCOLA</th>\n",
              "      <th>TX_EVASAO</th>\n",
              "      <th>VL_NOTA_LP</th>\n",
              "      <th>VL_NOTA_GEO</th>\n",
              "      <th>VL_NOTA_HIST</th>\n",
              "      <th>VL_NOTA_MAT</th>\n",
              "      <th>VL_NOTA_ING</th>\n",
              "      <th>VL_NOTA_ART</th>\n",
              "      <th>VL_NOTA_EDFIS</th>\n",
              "      <th>VL_NOTA_CIEN</th>\n",
              "      <th>VL_NOTA_LP2</th>\n",
              "      <th>VL_NOTA_GEO2</th>\n",
              "      <th>VL_NOTA_HIST2</th>\n",
              "      <th>VL_NOTA_MAT2</th>\n",
              "      <th>VL_NOTA_ING2</th>\n",
              "      <th>VL_NOTA_ART2</th>\n",
              "      <th>VL_NOTA_EDFIS2</th>\n",
              "      <th>VL_NOTA_CIEN2</th>\n",
              "      <th>VL_NOTA_LP3</th>\n",
              "      <th>VL_NOTA_GEO3</th>\n",
              "      <th>VL_NOTA_HIST3</th>\n",
              "      <th>VL_NOTA_MAT3</th>\n",
              "      <th>VL_NOTA_ING3</th>\n",
              "      <th>VL_NOTA_ART3</th>\n",
              "      <th>VL_NOTA_EDFIS3</th>\n",
              "      <th>VL_NOTA_CIEN3</th>\n",
              "      <th>VL_NOTA_LP4</th>\n",
              "      <th>VL_NOTA_GEO4</th>\n",
              "      <th>VL_NOTA_HIST4</th>\n",
              "      <th>VL_NOTA_MAT4</th>\n",
              "      <th>VL_NOTA_ING4</th>\n",
              "      <th>VL_NOTA_ART4</th>\n",
              "      <th>VL_NOTA_EDFIS4</th>\n",
              "      <th>VL_NOTA_CIEN4</th>\n",
              "      <th>TX_FREQ_LP</th>\n",
              "      <th>TX_FREQ_GEO</th>\n",
              "      <th>TX_FREQ_HIST</th>\n",
              "      <th>TX_FREQ_MAT</th>\n",
              "      <th>TX_FREQ_ING</th>\n",
              "      <th>TX_FREQ_ART</th>\n",
              "      <th>TX_FREQ_EDFIS</th>\n",
              "      <th>TX_FREQ_CIEN</th>\n",
              "      <th>TX_FREQ_LP2</th>\n",
              "      <th>TX_FREQ_GEO2</th>\n",
              "      <th>TX_FREQ_HIST2</th>\n",
              "      <th>TX_FREQ_MAT2</th>\n",
              "      <th>TX_FREQ_ING2</th>\n",
              "      <th>TX_FREQ_ART2</th>\n",
              "      <th>TX_FREQ_EDFIS2</th>\n",
              "      <th>TX_FREQ_CIEN2</th>\n",
              "      <th>TX_FREQ_LP3</th>\n",
              "      <th>TX_FREQ_GEO3</th>\n",
              "      <th>TX_FREQ_HIST3</th>\n",
              "      <th>TX_FREQ_MAT3</th>\n",
              "      <th>TX_FREQ_ING3</th>\n",
              "      <th>TX_FREQ_ART3</th>\n",
              "      <th>TX_FREQ_EDFIS3</th>\n",
              "      <th>TX_FREQ_CIEN3</th>\n",
              "      <th>TX_FREQ_LP4</th>\n",
              "      <th>TX_FREQ_GEO4</th>\n",
              "      <th>TX_FREQ_HIST4</th>\n",
              "      <th>TX_FREQ_MAT4</th>\n",
              "      <th>TX_FREQ_ING4</th>\n",
              "      <th>TX_FREQ_ART4</th>\n",
              "      <th>TX_FREQ_EDFIS4</th>\n",
              "      <th>TX_FREQ_CIEN4</th>\n",
              "      <th>ESC_Código_de_situação_do_setor_censitário</th>\n",
              "      <th>ESC_Setor_é_Aglomerado_subnormal_</th>\n",
              "      <th>ESC_Grupo_do_IPVS</th>\n",
              "      <th>ESC_Domicílios_particulares_e_coletivos</th>\n",
              "      <th>ESC_Média_de_moradores_em_domicílios_particulares_permanentes</th>\n",
              "      <th>ESC_Proporção_de_crianças_de_0_a_5_anos_na_população</th>\n",
              "      <th>ESC_Rendimento_médio_domiciliar_dos_domicílios</th>\n",
              "      <th>ESC_Renda_per_capita_nos_domicílios</th>\n",
              "      <th>ESC_Proporção_de_Domicílios_sem_Renda_per_Capita</th>\n",
              "      <th>ESC_Idade_média_das_pessoas_responsáveis</th>\n",
              "      <th>ESC_Rendimento_médio_do_responsável_pelo_domicílio</th>\n",
              "      <th>ESC_Proporção_de_pessoas_responsáveis_alfabetizadas</th>\n",
              "      <th>ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos</th>\n",
              "      <th>ESC_Participação_da_renda_do_responsável</th>\n",
              "      <th>ESC_Idade_média_mulheres_respon_pelo_domicílio</th>\n",
              "      <th>ESC_Prop_mulheres_respon_domicílio_alfabet</th>\n",
              "      <th>ESC_Prop_mulheres_respon_domicílio_menos_30_anos</th>\n",
              "      <th>ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio</th>\n",
              "      <th>ESC_Prop_abastecimento_de_água</th>\n",
              "      <th>ESC_Prop_banheiro</th>\n",
              "      <th>ESC_Prop_domicílios_pp_lixo_coletado</th>\n",
              "      <th>ESC_Prop_domicílios_pp_energia_elétrica</th>\n",
              "      <th>ESC_Pop_total_residente_Mun</th>\n",
              "      <th>AL_Código_de_situação_do_setor_censitário</th>\n",
              "      <th>AL_Setor_é_Aglomerado_subnormal_</th>\n",
              "      <th>AL_Grupo_do_IPVS</th>\n",
              "      <th>AL_Domicílios_particulares_e_coletivos</th>\n",
              "      <th>AL_Média_de_moradores_em_domicílios_particulares_permanentes</th>\n",
              "      <th>AL_Proporção_de_crianças_de_0_a_5_anos_na_população</th>\n",
              "      <th>AL_Rendimento_médio_domiciliar_dos_domicílios</th>\n",
              "      <th>AL_Renda_per_capita_nos_domicílios</th>\n",
              "      <th>AL_Proporção_de_Domicílios_sem_Renda_per_Capita</th>\n",
              "      <th>AL_Idade_média_das_pessoas_responsáveis</th>\n",
              "      <th>AL_Rendimento_médio_do_responsável_pelo_domicílio</th>\n",
              "      <th>AL_Proporção_de_pessoas_responsáveis_alfabetizadas</th>\n",
              "      <th>AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos</th>\n",
              "      <th>AL_Participação_da_renda_do_responsável</th>\n",
              "      <th>AL_Idade_média_mulheres_respon_pelo_domicílio</th>\n",
              "      <th>AL_Prop_mulheres_respon_domicílio_alfabet</th>\n",
              "      <th>AL_Prop_mulheres_respon_domicílio_menos_30_anos</th>\n",
              "      <th>AL_Rend_médio_mulheres_responsáveis_pelo_domicílio</th>\n",
              "      <th>AL_Prop_abastecimento_de_água</th>\n",
              "      <th>AL_Prop_banheiro</th>\n",
              "      <th>AL_Prop_domicílios_pp_lixo_coletado</th>\n",
              "      <th>AL_Prop_domicílios_pp_energia_elétrica</th>\n",
              "      <th>AL_Pop_total_residente_Mun</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>21935885.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>19.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.06</td>\n",
              "      <td>40.2806</td>\n",
              "      <td>5.97</td>\n",
              "      <td>926.0</td>\n",
              "      <td>0.0400</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.7000</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.7778</td>\n",
              "      <td>0.8378</td>\n",
              "      <td>0.5556</td>\n",
              "      <td>0.7000</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.6271</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.900</td>\n",
              "      <td>0.0833</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.90</td>\n",
              "      <td>0.8750</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.8889</td>\n",
              "      <td>0.9500</td>\n",
              "      <td>0.900</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.9500</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>276.0</td>\n",
              "      <td>3.485507</td>\n",
              "      <td>12.058212</td>\n",
              "      <td>945.713768</td>\n",
              "      <td>271.327443</td>\n",
              "      <td>24.637681</td>\n",
              "      <td>38.510870</td>\n",
              "      <td>361.898551</td>\n",
              "      <td>90.579710</td>\n",
              "      <td>33.695652</td>\n",
              "      <td>38.267239</td>\n",
              "      <td>37.396739</td>\n",
              "      <td>91.304348</td>\n",
              "      <td>35.869565</td>\n",
              "      <td>268.777174</td>\n",
              "      <td>89.855072</td>\n",
              "      <td>62.681159</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>11253503.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>276.0</td>\n",
              "      <td>3.485507</td>\n",
              "      <td>12.058212</td>\n",
              "      <td>945.713768</td>\n",
              "      <td>271.327443</td>\n",
              "      <td>24.637681</td>\n",
              "      <td>38.510870</td>\n",
              "      <td>361.898551</td>\n",
              "      <td>90.579710</td>\n",
              "      <td>33.695652</td>\n",
              "      <td>38.267239</td>\n",
              "      <td>37.396739</td>\n",
              "      <td>91.304348</td>\n",
              "      <td>35.869565</td>\n",
              "      <td>268.777174</td>\n",
              "      <td>89.855072</td>\n",
              "      <td>62.681159</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>11253503.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>22472255.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.85</td>\n",
              "      <td>53.4927</td>\n",
              "      <td>4.54</td>\n",
              "      <td>995.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.9250</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8500</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.9355</td>\n",
              "      <td>0.9250</td>\n",
              "      <td>0.100</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9250</td>\n",
              "      <td>0.8947</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.8730</td>\n",
              "      <td>0.9250</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8500</td>\n",
              "      <td>0.9167</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9412</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9310</td>\n",
              "      <td>0.925</td>\n",
              "      <td>0.4</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.9048</td>\n",
              "      <td>0.8571</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.9355</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>204.0</td>\n",
              "      <td>2.520000</td>\n",
              "      <td>5.048544</td>\n",
              "      <td>2548.593137</td>\n",
              "      <td>1009.539806</td>\n",
              "      <td>12.745098</td>\n",
              "      <td>57.828431</td>\n",
              "      <td>1703.789216</td>\n",
              "      <td>97.549020</td>\n",
              "      <td>5.392157</td>\n",
              "      <td>66.852146</td>\n",
              "      <td>62.148148</td>\n",
              "      <td>95.061728</td>\n",
              "      <td>3.703704</td>\n",
              "      <td>1178.395062</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>99.509804</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>53158.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>154.0</td>\n",
              "      <td>3.730000</td>\n",
              "      <td>11.846690</td>\n",
              "      <td>892.311688</td>\n",
              "      <td>239.400697</td>\n",
              "      <td>16.233766</td>\n",
              "      <td>40.428571</td>\n",
              "      <td>482.487013</td>\n",
              "      <td>79.220779</td>\n",
              "      <td>22.727273</td>\n",
              "      <td>54.071578</td>\n",
              "      <td>43.375000</td>\n",
              "      <td>77.083333</td>\n",
              "      <td>18.750000</td>\n",
              "      <td>355.291667</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>53158.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>17568090.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.96</td>\n",
              "      <td>42.4715</td>\n",
              "      <td>2.67</td>\n",
              "      <td>1199.0</td>\n",
              "      <td>0.0467</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.9524</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>0.7826</td>\n",
              "      <td>0.9130</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.7273</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.7429</td>\n",
              "      <td>0.8485</td>\n",
              "      <td>0.875</td>\n",
              "      <td>0.6667</td>\n",
              "      <td>0.8182</td>\n",
              "      <td>0.6250</td>\n",
              "      <td>0.6875</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.7447</td>\n",
              "      <td>0.9773</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8235</td>\n",
              "      <td>0.8788</td>\n",
              "      <td>0.7778</td>\n",
              "      <td>0.7778</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.975</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.9565</td>\n",
              "      <td>0.8864</td>\n",
              "      <td>0.8636</td>\n",
              "      <td>0.8500</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.8788</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>121.0</td>\n",
              "      <td>2.290000</td>\n",
              "      <td>2.941176</td>\n",
              "      <td>3303.680672</td>\n",
              "      <td>1445.360294</td>\n",
              "      <td>0.840336</td>\n",
              "      <td>58.932773</td>\n",
              "      <td>2452.731092</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>2.521008</td>\n",
              "      <td>74.242378</td>\n",
              "      <td>61.093750</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>1.562500</td>\n",
              "      <td>1768.093750</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>87057.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>210.0</td>\n",
              "      <td>3.530000</td>\n",
              "      <td>10.931174</td>\n",
              "      <td>1217.385714</td>\n",
              "      <td>345.008097</td>\n",
              "      <td>3.809524</td>\n",
              "      <td>48.623810</td>\n",
              "      <td>704.842857</td>\n",
              "      <td>90.952381</td>\n",
              "      <td>11.904762</td>\n",
              "      <td>57.898072</td>\n",
              "      <td>51.082474</td>\n",
              "      <td>85.567010</td>\n",
              "      <td>8.247423</td>\n",
              "      <td>501.494845</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>85.714286</td>\n",
              "      <td>99.52381</td>\n",
              "      <td>99.52381</td>\n",
              "      <td>87057.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>35284840.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.49</td>\n",
              "      <td>35.0169</td>\n",
              "      <td>4.60</td>\n",
              "      <td>1005.0</td>\n",
              "      <td>0.0826</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>392.0</td>\n",
              "      <td>2.843750</td>\n",
              "      <td>17.582418</td>\n",
              "      <td>3009.544643</td>\n",
              "      <td>1058.301413</td>\n",
              "      <td>4.824561</td>\n",
              "      <td>41.707692</td>\n",
              "      <td>1801.187500</td>\n",
              "      <td>93.538462</td>\n",
              "      <td>25.846154</td>\n",
              "      <td>59.849170</td>\n",
              "      <td>41.047945</td>\n",
              "      <td>94.520548</td>\n",
              "      <td>23.972603</td>\n",
              "      <td>1324.573034</td>\n",
              "      <td>96.428571</td>\n",
              "      <td>99.553571</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>11253503.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>167.0</td>\n",
              "      <td>3.167665</td>\n",
              "      <td>7.372401</td>\n",
              "      <td>2338.550898</td>\n",
              "      <td>738.257089</td>\n",
              "      <td>3.592814</td>\n",
              "      <td>42.281437</td>\n",
              "      <td>1184.562874</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>22.155689</td>\n",
              "      <td>50.653714</td>\n",
              "      <td>43.471429</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>18.571429</td>\n",
              "      <td>892.257143</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>11253503.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>21792155.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.50</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>2.90</td>\n",
              "      <td>1653.0</td>\n",
              "      <td>0.0175</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.9400</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8913</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.9667</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.8077</td>\n",
              "      <td>0.6000</td>\n",
              "      <td>0.8182</td>\n",
              "      <td>0.85</td>\n",
              "      <td>0.8333</td>\n",
              "      <td>0.8400</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9500</td>\n",
              "      <td>0.8667</td>\n",
              "      <td>0.860</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.9000</td>\n",
              "      <td>0.8627</td>\n",
              "      <td>0.8000</td>\n",
              "      <td>0.9091</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.8667</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>3.124542</td>\n",
              "      <td>6.447831</td>\n",
              "      <td>2182.307692</td>\n",
              "      <td>698.440797</td>\n",
              "      <td>1.465201</td>\n",
              "      <td>49.307692</td>\n",
              "      <td>1163.509158</td>\n",
              "      <td>97.802198</td>\n",
              "      <td>10.989011</td>\n",
              "      <td>53.315541</td>\n",
              "      <td>52.267327</td>\n",
              "      <td>96.039604</td>\n",
              "      <td>7.920792</td>\n",
              "      <td>948.554455</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>99.633700</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>11253503.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>184.0</td>\n",
              "      <td>3.448087</td>\n",
              "      <td>6.339144</td>\n",
              "      <td>1846.639344</td>\n",
              "      <td>535.554675</td>\n",
              "      <td>3.260870</td>\n",
              "      <td>48.081522</td>\n",
              "      <td>963.153005</td>\n",
              "      <td>92.391304</td>\n",
              "      <td>13.043478</td>\n",
              "      <td>52.157072</td>\n",
              "      <td>52.309859</td>\n",
              "      <td>90.140845</td>\n",
              "      <td>7.042254</td>\n",
              "      <td>650.112676</td>\n",
              "      <td>99.453552</td>\n",
              "      <td>95.081967</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>100.00000</td>\n",
              "      <td>11253503.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     CD_ALUNO  TP_SEXO  VL_IDADE  VL_DISTORCAO  CD_TIPO_ENSINO  NR_SERIE  \\\n",
              "0  21935885.0      1.0      19.0           4.0             1.0       1.0   \n",
              "1  22472255.0      1.0      16.0           0.0             1.0       2.0   \n",
              "2  17568090.0      0.0      18.0           2.0             1.0       2.0   \n",
              "3  35284840.0      1.0      17.0           6.0             0.0       6.0   \n",
              "4  21792155.0      1.0      16.0           0.0             1.0       2.0   \n",
              "\n",
              "   CD_TURNO  VL_IDESP  VL_REPASSE_ALUNO  VL_INSE  QT_ALUNO_ESCOLA  TX_EVASAO  \\\n",
              "0       5.0      2.06           40.2806     5.97            926.0     0.0400   \n",
              "1       5.0      2.85           53.4927     4.54            995.0     0.0000   \n",
              "2       5.0      1.96           42.4715     2.67           1199.0     0.0467   \n",
              "3       3.0      2.49           35.0169     4.60           1005.0     0.0826   \n",
              "4       1.0      2.50            0.0000     2.90           1653.0     0.0175   \n",
              "\n",
              "   VL_NOTA_LP  VL_NOTA_GEO  VL_NOTA_HIST  VL_NOTA_MAT  VL_NOTA_ING  \\\n",
              "0         2.0          2.0           1.0          2.0          1.0   \n",
              "1         7.0          7.0           7.0          6.0          9.0   \n",
              "2         4.0          5.0           4.0          5.0         10.0   \n",
              "3         0.0          0.0           0.0          0.0          0.0   \n",
              "4         4.0          8.0           6.0          7.0          7.0   \n",
              "\n",
              "   VL_NOTA_ART  VL_NOTA_EDFIS  VL_NOTA_CIEN  VL_NOTA_LP2  VL_NOTA_GEO2  \\\n",
              "0          3.0            8.0           2.0          0.0           0.0   \n",
              "1         10.0            0.0           7.0          7.0           3.0   \n",
              "2          4.0            0.0           4.0          2.0           6.0   \n",
              "3          0.0            0.0           0.0          0.0           0.0   \n",
              "4          6.0            9.0           7.0          5.0           5.0   \n",
              "\n",
              "   VL_NOTA_HIST2  VL_NOTA_MAT2  VL_NOTA_ING2  VL_NOTA_ART2  VL_NOTA_EDFIS2  \\\n",
              "0            0.0           5.0           0.0           5.0             8.0   \n",
              "1            8.0           7.0           7.0           8.0             0.0   \n",
              "2            5.0           5.0           3.0           5.0             0.0   \n",
              "3            0.0           0.0           0.0           0.0             0.0   \n",
              "4            7.0           5.0           3.0           5.0             6.0   \n",
              "\n",
              "   VL_NOTA_CIEN2  VL_NOTA_LP3  VL_NOTA_GEO3  VL_NOTA_HIST3  VL_NOTA_MAT3  \\\n",
              "0            5.0          5.0           0.0            0.0           5.0   \n",
              "1            6.0          8.0           5.0            8.0           9.0   \n",
              "2            4.0          5.0           7.0            6.0           5.0   \n",
              "3            0.0          0.0           0.0            0.0           0.0   \n",
              "4            5.0          5.0           8.0            8.0           7.0   \n",
              "\n",
              "   VL_NOTA_ING3  VL_NOTA_ART3  VL_NOTA_EDFIS3  VL_NOTA_CIEN3  VL_NOTA_LP4  \\\n",
              "0           0.0           5.0             8.0            5.0          5.0   \n",
              "1          10.0           8.0             0.0            7.0          7.0   \n",
              "2           7.0           7.0             0.0            6.0          8.0   \n",
              "3           0.0           0.0             0.0            0.0          0.0   \n",
              "4           7.0           7.0             7.0            6.0          6.0   \n",
              "\n",
              "   VL_NOTA_GEO4  VL_NOTA_HIST4  VL_NOTA_MAT4  VL_NOTA_ING4  VL_NOTA_ART4  \\\n",
              "0           0.0            0.0           5.0           5.0           5.0   \n",
              "1           4.0           10.0          10.0           7.0          10.0   \n",
              "2           0.0            6.0           6.0           7.0           7.0   \n",
              "3           0.0            0.0           0.0           0.0           0.0   \n",
              "4           8.0            8.0           6.0           5.0           7.0   \n",
              "\n",
              "   VL_NOTA_EDFIS4  VL_NOTA_CIEN4  TX_FREQ_LP  TX_FREQ_GEO  TX_FREQ_HIST  \\\n",
              "0             8.0            5.0      0.7000       0.8333        0.7778   \n",
              "1             0.0            7.0      0.9250       0.0000        0.8500   \n",
              "2             0.0            5.0      0.9524       0.8800        0.7826   \n",
              "3             0.0            0.0      0.0000       0.0000        0.0000   \n",
              "4             9.0            6.0      0.9400       0.0000        0.8000   \n",
              "\n",
              "   TX_FREQ_MAT  TX_FREQ_ING  TX_FREQ_ART  TX_FREQ_EDFIS  TX_FREQ_CIEN  \\\n",
              "0       0.8378       0.5556       0.7000            0.9        0.6271   \n",
              "1       0.0000       0.0000       0.0000            0.0        0.9355   \n",
              "2       0.9130       0.0000       0.7273            0.0        0.7429   \n",
              "3       0.0000       0.0000       0.0000            0.0        0.0000   \n",
              "4       0.8913       0.8000       0.8000            0.0        0.9667   \n",
              "\n",
              "   TX_FREQ_LP2  TX_FREQ_GEO2  TX_FREQ_HIST2  TX_FREQ_MAT2  TX_FREQ_ING2  \\\n",
              "0       0.0000         0.900         0.0833        0.9000        0.0000   \n",
              "1       0.9250         0.100         0.9000        0.9250        0.8947   \n",
              "2       0.8485         0.875         0.6667        0.8182        0.6250   \n",
              "3       0.0000         0.000         0.0000        0.0000        0.0000   \n",
              "4       0.9000         0.000         0.8000        0.8077        0.6000   \n",
              "\n",
              "   TX_FREQ_ART2  TX_FREQ_EDFIS2  TX_FREQ_CIEN2  TX_FREQ_LP3  TX_FREQ_GEO3  \\\n",
              "0        0.9000            0.90         0.8750       0.9000        0.8889   \n",
              "1        0.0000            0.00         0.8730       0.9250        0.8000   \n",
              "2        0.6875            0.00         0.7447       0.9773        0.0000   \n",
              "3        0.0000            0.00         0.0000       0.0000        0.0000   \n",
              "4        0.8182            0.85         0.8333       0.8400        0.8000   \n",
              "\n",
              "   TX_FREQ_HIST3  TX_FREQ_MAT3  TX_FREQ_ING3  TX_FREQ_ART3  TX_FREQ_EDFIS3  \\\n",
              "0         0.8889        0.9000        0.0000        0.8889          0.8889   \n",
              "1         0.8500        0.9167        0.0000        0.9412          0.0000   \n",
              "2         0.8235        0.8788        0.7778        0.7778          0.0000   \n",
              "3         0.0000        0.0000        0.0000        0.0000          0.0000   \n",
              "4         0.0000        0.8800        0.8000        0.0000          0.9500   \n",
              "\n",
              "   TX_FREQ_CIEN3  TX_FREQ_LP4  TX_FREQ_GEO4  TX_FREQ_HIST4  TX_FREQ_MAT4  \\\n",
              "0         0.9500        0.900           0.9         0.9000        0.9000   \n",
              "1         0.9310        0.925           0.4         0.9000        0.9048   \n",
              "2         0.9000        0.975           0.0         0.9565        0.8864   \n",
              "3         0.0000        0.000           0.0         0.0000        0.0000   \n",
              "4         0.8667        0.860           0.9         0.9000        0.8627   \n",
              "\n",
              "   TX_FREQ_ING4  TX_FREQ_ART4  TX_FREQ_EDFIS4  TX_FREQ_CIEN4  \\\n",
              "0        0.9000        0.9000             0.9         0.9500   \n",
              "1        0.8571        0.0000             0.0         0.9355   \n",
              "2        0.8636        0.8500             0.0         0.8788   \n",
              "3        0.0000        0.0000             0.0         0.0000   \n",
              "4        0.8000        0.9091             0.9         0.8667   \n",
              "\n",
              "   ESC_Código_de_situação_do_setor_censitário  \\\n",
              "0                                         3.0   \n",
              "1                                         1.0   \n",
              "2                                         1.0   \n",
              "3                                         1.0   \n",
              "4                                         1.0   \n",
              "\n",
              "   ESC_Setor_é_Aglomerado_subnormal_  ESC_Grupo_do_IPVS  \\\n",
              "0                                0.0                5.0   \n",
              "1                                0.0                2.0   \n",
              "2                                0.0                2.0   \n",
              "3                                0.0                3.0   \n",
              "4                                0.0                2.0   \n",
              "\n",
              "   ESC_Domicílios_particulares_e_coletivos  \\\n",
              "0                                    276.0   \n",
              "1                                    204.0   \n",
              "2                                    121.0   \n",
              "3                                    392.0   \n",
              "4                                    273.0   \n",
              "\n",
              "   ESC_Média_de_moradores_em_domicílios_particulares_permanentes  \\\n",
              "0                                           3.485507               \n",
              "1                                           2.520000               \n",
              "2                                           2.290000               \n",
              "3                                           2.843750               \n",
              "4                                           3.124542               \n",
              "\n",
              "   ESC_Proporção_de_crianças_de_0_a_5_anos_na_população  \\\n",
              "0                                          12.058212      \n",
              "1                                           5.048544      \n",
              "2                                           2.941176      \n",
              "3                                          17.582418      \n",
              "4                                           6.447831      \n",
              "\n",
              "   ESC_Rendimento_médio_domiciliar_dos_domicílios  \\\n",
              "0                                      945.713768   \n",
              "1                                     2548.593137   \n",
              "2                                     3303.680672   \n",
              "3                                     3009.544643   \n",
              "4                                     2182.307692   \n",
              "\n",
              "   ESC_Renda_per_capita_nos_domicílios  \\\n",
              "0                           271.327443   \n",
              "1                          1009.539806   \n",
              "2                          1445.360294   \n",
              "3                          1058.301413   \n",
              "4                           698.440797   \n",
              "\n",
              "   ESC_Proporção_de_Domicílios_sem_Renda_per_Capita  \\\n",
              "0                                         24.637681   \n",
              "1                                         12.745098   \n",
              "2                                          0.840336   \n",
              "3                                          4.824561   \n",
              "4                                          1.465201   \n",
              "\n",
              "   ESC_Idade_média_das_pessoas_responsáveis  \\\n",
              "0                                 38.510870   \n",
              "1                                 57.828431   \n",
              "2                                 58.932773   \n",
              "3                                 41.707692   \n",
              "4                                 49.307692   \n",
              "\n",
              "   ESC_Rendimento_médio_do_responsável_pelo_domicílio  \\\n",
              "0                                         361.898551    \n",
              "1                                        1703.789216    \n",
              "2                                        2452.731092    \n",
              "3                                        1801.187500    \n",
              "4                                        1163.509158    \n",
              "\n",
              "   ESC_Proporção_de_pessoas_responsáveis_alfabetizadas  \\\n",
              "0                                          90.579710     \n",
              "1                                          97.549020     \n",
              "2                                         100.000000     \n",
              "3                                          93.538462     \n",
              "4                                          97.802198     \n",
              "\n",
              "   ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos  \\\n",
              "0                                          33.695652       \n",
              "1                                           5.392157       \n",
              "2                                           2.521008       \n",
              "3                                          25.846154       \n",
              "4                                          10.989011       \n",
              "\n",
              "   ESC_Participação_da_renda_do_responsável  \\\n",
              "0                                 38.267239   \n",
              "1                                 66.852146   \n",
              "2                                 74.242378   \n",
              "3                                 59.849170   \n",
              "4                                 53.315541   \n",
              "\n",
              "   ESC_Idade_média_mulheres_respon_pelo_domicílio  \\\n",
              "0                                       37.396739   \n",
              "1                                       62.148148   \n",
              "2                                       61.093750   \n",
              "3                                       41.047945   \n",
              "4                                       52.267327   \n",
              "\n",
              "   ESC_Prop_mulheres_respon_domicílio_alfabet  \\\n",
              "0                                   91.304348   \n",
              "1                                   95.061728   \n",
              "2                                  100.000000   \n",
              "3                                   94.520548   \n",
              "4                                   96.039604   \n",
              "\n",
              "   ESC_Prop_mulheres_respon_domicílio_menos_30_anos  \\\n",
              "0                                         35.869565   \n",
              "1                                          3.703704   \n",
              "2                                          1.562500   \n",
              "3                                         23.972603   \n",
              "4                                          7.920792   \n",
              "\n",
              "   ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio  \\\n",
              "0                                         268.777174     \n",
              "1                                        1178.395062     \n",
              "2                                        1768.093750     \n",
              "3                                        1324.573034     \n",
              "4                                         948.554455     \n",
              "\n",
              "   ESC_Prop_abastecimento_de_água  ESC_Prop_banheiro  \\\n",
              "0                       89.855072          62.681159   \n",
              "1                      100.000000          99.509804   \n",
              "2                      100.000000         100.000000   \n",
              "3                       96.428571          99.553571   \n",
              "4                      100.000000          99.633700   \n",
              "\n",
              "   ESC_Prop_domicílios_pp_lixo_coletado  \\\n",
              "0                                 100.0   \n",
              "1                                 100.0   \n",
              "2                                 100.0   \n",
              "3                                 100.0   \n",
              "4                                 100.0   \n",
              "\n",
              "   ESC_Prop_domicílios_pp_energia_elétrica  ESC_Pop_total_residente_Mun  \\\n",
              "0                                    100.0                   11253503.0   \n",
              "1                                    100.0                      53158.0   \n",
              "2                                    100.0                      87057.0   \n",
              "3                                    100.0                   11253503.0   \n",
              "4                                    100.0                   11253503.0   \n",
              "\n",
              "   AL_Código_de_situação_do_setor_censitário  \\\n",
              "0                                        3.0   \n",
              "1                                        1.0   \n",
              "2                                        1.0   \n",
              "3                                        1.0   \n",
              "4                                        1.0   \n",
              "\n",
              "   AL_Setor_é_Aglomerado_subnormal_  AL_Grupo_do_IPVS  \\\n",
              "0                               0.0               5.0   \n",
              "1                               0.0               5.0   \n",
              "2                               0.0               4.0   \n",
              "3                               0.0               3.0   \n",
              "4                               0.0               4.0   \n",
              "\n",
              "   AL_Domicílios_particulares_e_coletivos  \\\n",
              "0                                   276.0   \n",
              "1                                   154.0   \n",
              "2                                   210.0   \n",
              "3                                   167.0   \n",
              "4                                   184.0   \n",
              "\n",
              "   AL_Média_de_moradores_em_domicílios_particulares_permanentes  \\\n",
              "0                                           3.485507              \n",
              "1                                           3.730000              \n",
              "2                                           3.530000              \n",
              "3                                           3.167665              \n",
              "4                                           3.448087              \n",
              "\n",
              "   AL_Proporção_de_crianças_de_0_a_5_anos_na_população  \\\n",
              "0                                          12.058212     \n",
              "1                                          11.846690     \n",
              "2                                          10.931174     \n",
              "3                                           7.372401     \n",
              "4                                           6.339144     \n",
              "\n",
              "   AL_Rendimento_médio_domiciliar_dos_domicílios  \\\n",
              "0                                     945.713768   \n",
              "1                                     892.311688   \n",
              "2                                    1217.385714   \n",
              "3                                    2338.550898   \n",
              "4                                    1846.639344   \n",
              "\n",
              "   AL_Renda_per_capita_nos_domicílios  \\\n",
              "0                          271.327443   \n",
              "1                          239.400697   \n",
              "2                          345.008097   \n",
              "3                          738.257089   \n",
              "4                          535.554675   \n",
              "\n",
              "   AL_Proporção_de_Domicílios_sem_Renda_per_Capita  \\\n",
              "0                                        24.637681   \n",
              "1                                        16.233766   \n",
              "2                                         3.809524   \n",
              "3                                         3.592814   \n",
              "4                                         3.260870   \n",
              "\n",
              "   AL_Idade_média_das_pessoas_responsáveis  \\\n",
              "0                                38.510870   \n",
              "1                                40.428571   \n",
              "2                                48.623810   \n",
              "3                                42.281437   \n",
              "4                                48.081522   \n",
              "\n",
              "   AL_Rendimento_médio_do_responsável_pelo_domicílio  \\\n",
              "0                                         361.898551   \n",
              "1                                         482.487013   \n",
              "2                                         704.842857   \n",
              "3                                        1184.562874   \n",
              "4                                         963.153005   \n",
              "\n",
              "   AL_Proporção_de_pessoas_responsáveis_alfabetizadas  \\\n",
              "0                                          90.579710    \n",
              "1                                          79.220779    \n",
              "2                                          90.952381    \n",
              "3                                         100.000000    \n",
              "4                                          92.391304    \n",
              "\n",
              "   AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos  \\\n",
              "0                                          33.695652      \n",
              "1                                          22.727273      \n",
              "2                                          11.904762      \n",
              "3                                          22.155689      \n",
              "4                                          13.043478      \n",
              "\n",
              "   AL_Participação_da_renda_do_responsável  \\\n",
              "0                                38.267239   \n",
              "1                                54.071578   \n",
              "2                                57.898072   \n",
              "3                                50.653714   \n",
              "4                                52.157072   \n",
              "\n",
              "   AL_Idade_média_mulheres_respon_pelo_domicílio  \\\n",
              "0                                      37.396739   \n",
              "1                                      43.375000   \n",
              "2                                      51.082474   \n",
              "3                                      43.471429   \n",
              "4                                      52.309859   \n",
              "\n",
              "   AL_Prop_mulheres_respon_domicílio_alfabet  \\\n",
              "0                                  91.304348   \n",
              "1                                  77.083333   \n",
              "2                                  85.567010   \n",
              "3                                 100.000000   \n",
              "4                                  90.140845   \n",
              "\n",
              "   AL_Prop_mulheres_respon_domicílio_menos_30_anos  \\\n",
              "0                                        35.869565   \n",
              "1                                        18.750000   \n",
              "2                                         8.247423   \n",
              "3                                        18.571429   \n",
              "4                                         7.042254   \n",
              "\n",
              "   AL_Rend_médio_mulheres_responsáveis_pelo_domicílio  \\\n",
              "0                                         268.777174    \n",
              "1                                         355.291667    \n",
              "2                                         501.494845    \n",
              "3                                         892.257143    \n",
              "4                                         650.112676    \n",
              "\n",
              "   AL_Prop_abastecimento_de_água  AL_Prop_banheiro  \\\n",
              "0                      89.855072         62.681159   \n",
              "1                     100.000000        100.000000   \n",
              "2                     100.000000         85.714286   \n",
              "3                     100.000000        100.000000   \n",
              "4                      99.453552         95.081967   \n",
              "\n",
              "   AL_Prop_domicílios_pp_lixo_coletado  \\\n",
              "0                            100.00000   \n",
              "1                            100.00000   \n",
              "2                             99.52381   \n",
              "3                            100.00000   \n",
              "4                            100.00000   \n",
              "\n",
              "   AL_Prop_domicílios_pp_energia_elétrica  AL_Pop_total_residente_Mun  \n",
              "0                               100.00000                  11253503.0  \n",
              "1                               100.00000                     53158.0  \n",
              "2                                99.52381                     87057.0  \n",
              "3                               100.00000                  11253503.0  \n",
              "4                               100.00000                  11253503.0  "
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jA3HaqRbgKHd"
      },
      "source": [
        "# Fazendo predições com novos dados e score de probabilidade (Ref. https://machinelearningmastery.com/make-predictions-scikit-learn/)\n",
        "\n",
        "# Importando modelo salvo Floresta Randômica\n",
        "\n",
        "import pickle\n",
        "\n",
        "rf_filename = 'dados_evasao/rf_dropout_model.sav'\n",
        "rf_loaded_model = pickle.load(open(rf_filename, 'rb'))\n",
        "\n",
        "# Importando modelo salvo SVC\n",
        "\n",
        "#svm_filename = 'dados_evasao/svc_dropout_model.sav'\n",
        "#svm_loaded_model = pickle.load(open(svm_filename, 'rb'))\n",
        "\n",
        "# Expondo features usadas no treinamento/teste\n",
        "\n",
        "features = ['CD_ALUNO','TP_SEXO','CD_TIPO_ENSINO','NR_SERIE','CD_TURNO','ESC_Código_de_situação_do_setor_censitário','ESC_Setor_é_Aglomerado_subnormal_','ESC_Grupo_do_IPVS','AL_Código_de_situação_do_setor_censitário','AL_Setor_é_Aglomerado_subnormal_','AL_Grupo_do_IPVS','VL_IDADE','VL_DISTORCAO','VL_IDESP','VL_REPASSE_ALUNO','VL_INSE','QT_ALUNO_ESCOLA','TX_EVASAO','VL_NOTA_LP','VL_NOTA_GEO','VL_NOTA_HIST','VL_NOTA_MAT','VL_NOTA_ING','VL_NOTA_ART','VL_NOTA_EDFIS','VL_NOTA_CIEN','VL_NOTA_LP2','VL_NOTA_GEO2','VL_NOTA_HIST2','VL_NOTA_MAT2','VL_NOTA_ING2','VL_NOTA_ART2','VL_NOTA_EDFIS2','VL_NOTA_CIEN2','VL_NOTA_LP3','VL_NOTA_GEO3','VL_NOTA_HIST3','VL_NOTA_MAT3','VL_NOTA_ING3','VL_NOTA_ART3','VL_NOTA_EDFIS3','VL_NOTA_CIEN3','VL_NOTA_LP4','VL_NOTA_GEO4','VL_NOTA_HIST4','VL_NOTA_MAT4','VL_NOTA_ING4','VL_NOTA_ART4','VL_NOTA_EDFIS4','VL_NOTA_CIEN4','TX_FREQ_LP','TX_FREQ_GEO','TX_FREQ_HIST','TX_FREQ_MAT','TX_FREQ_ING','TX_FREQ_ART','TX_FREQ_EDFIS','TX_FREQ_CIEN','TX_FREQ_LP2','TX_FREQ_GEO2','TX_FREQ_HIST2','TX_FREQ_MAT2','TX_FREQ_ING2','TX_FREQ_ART2','TX_FREQ_EDFIS2','TX_FREQ_CIEN2','TX_FREQ_LP3','TX_FREQ_GEO3','TX_FREQ_HIST3','TX_FREQ_MAT3','TX_FREQ_ING3','TX_FREQ_ART3','TX_FREQ_EDFIS3','TX_FREQ_CIEN3','TX_FREQ_LP4','TX_FREQ_GEO4','TX_FREQ_HIST4','TX_FREQ_MAT4','TX_FREQ_ING4','TX_FREQ_ART4','TX_FREQ_EDFIS4','TX_FREQ_CIEN4','ESC_Domicílios_particulares_e_coletivos','ESC_Média_de_moradores_em_domicílios_particulares_permanentes','ESC_Proporção_de_crianças_de_0_a_5_anos_na_população','ESC_Rendimento_médio_domiciliar_dos_domicílios','ESC_Renda_per_capita_nos_domicílios','ESC_Proporção_de_Domicílios_sem_Renda_per_Capita','ESC_Idade_média_das_pessoas_responsáveis','ESC_Rendimento_médio_do_responsável_pelo_domicílio','ESC_Proporção_de_pessoas_responsáveis_alfabetizadas','ESC_Proporção_de_pessoas_responsáveis_de_10_a_29_anos','ESC_Participação_da_renda_do_responsável','ESC_Idade_média_mulheres_respon_pelo_domicílio','ESC_Prop_mulheres_respon_domicílio_alfabet','ESC_Prop_mulheres_respon_domicílio_menos_30_anos','ESC_Rend_médio_mulheres_responsáveis_pelo_domicílio','ESC_Prop_abastecimento_de_água','ESC_Prop_banheiro','ESC_Prop_domicílios_pp_lixo_coletado','ESC_Prop_domicílios_pp_energia_elétrica','ESC_Pop_total_residente_Mun','AL_Domicílios_particulares_e_coletivos','AL_Média_de_moradores_em_domicílios_particulares_permanentes','AL_Proporção_de_crianças_de_0_a_5_anos_na_população','AL_Rendimento_médio_domiciliar_dos_domicílios','AL_Renda_per_capita_nos_domicílios','AL_Proporção_de_Domicílios_sem_Renda_per_Capita','AL_Idade_média_das_pessoas_responsáveis','AL_Rendimento_médio_do_responsável_pelo_domicílio','AL_Proporção_de_pessoas_responsáveis_alfabetizadas','AL_Proporção_de_pessoas_responsáveis_de_10_a_29_anos','AL_Participação_da_renda_do_responsável','AL_Idade_média_mulheres_respon_pelo_domicílio','AL_Prop_mulheres_respon_domicílio_alfabet','AL_Prop_mulheres_respon_domicílio_menos_30_anos','AL_Rend_médio_mulheres_responsáveis_pelo_domicílio','AL_Prop_abastecimento_de_água','AL_Prop_banheiro','AL_Prop_domicílios_pp_lixo_coletado','AL_Prop_domicílios_pp_energia_elétrica','AL_Pop_total_residente_Mun']\n",
        "\n",
        "# Pred/Prob com base em nosso modelo salvo Floresta Randômica\n",
        "\n",
        "#dropout_pred = rf_loaded_model.predict(dropout_df2[features])\n",
        "dropout_prob = rf_loaded_model.predict_proba(dropout_df2[features])[:, 1]\n",
        "\n",
        "# Pred/Prob com base em nosso modelo salvo SVC\n",
        "\n",
        "#dropout_pred = svm_loaded_model.predict(dropout_df2[features])\n",
        "#dropout_prob = svm_loaded_model.predict_proba(dropout_df2[features])[:, 1]\n",
        "\n",
        "#dropout_dataframe = pd.DataFrame({'CD_ALUNO': dropout_df2['CD_ALUNO'],'Risco de Evasão':dropout_pred})\n",
        "dropout_dataframe = pd.DataFrame({'CD_ALUNO': dropout_df2['CD_ALUNO'],'Risco de Evasão':dropout_prob})\n",
        "\n",
        "# Gerando lista quanto a risco de evasão para os alunos do dataset de teste\n",
        "\n",
        "dropout_dataframe.to_csv(\"dados_evasao/risco_evasao.csv\",index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dhopNvtqgKHd"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}