From 14f19df2981c843ab9c92fceec9d1fbc55a0cc0e Mon Sep 17 00:00:00 2001
From: Igor Marcos Riegel <igor.riegel@gmail.com>
Date: Tue, 22 Feb 2022 23:35:05 -0300
Subject: [PATCH] feito OHE em todas as variaveis categoricas e criado um df
 com id e variaveis relevantes.

---
 tratando_dados.ipynb | 1120 +++++++++++++++++++++++++++++-------------
 1 file changed, 788 insertions(+), 332 deletions(-)

diff --git a/tratando_dados.ipynb b/tratando_dados.ipynb
index 5ca0b26..4c3b3b6 100644
--- a/tratando_dados.ipynb
+++ b/tratando_dados.ipynb
@@ -2,7 +2,7 @@
   "cells": [
     {
       "cell_type": "code",
-      "execution_count": 88,
+      "execution_count": 23,
       "metadata": {
         "id": "jFo1WDS-0_mk"
       },
@@ -24,16 +24,17 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 89,
+      "execution_count": 24,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "DJXXZl9x0_mp",
-        "outputId": "dabd1dfd-5d1c-4d5e-8398-0ee5b1fc4237"
+        "outputId": "c9b7bdd5-243f-4788-b582-289ff8fd3eb5"
       },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "Index(['Unnamed: 0', 'id', 'fl_matriz', 'de_natureza_juridica', 'sg_uf',\n",
@@ -47,9 +48,8 @@
               "      dtype='object', length=182)"
             ]
           },
-          "execution_count": 89,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 24
         }
       ],
       "source": [
@@ -71,16 +71,17 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 90,
+      "execution_count": 25,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "VmDkNMQl0_mq",
-        "outputId": "ccc16e02-1870-4cee-df8a-327a7708cd6a"
+        "outputId": "87168cd3-4dc4-4968-a37e-2deb61357415"
       },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "Unnamed: 0                 0.000000\n",
@@ -97,9 +98,8 @@
               "Length: 182, dtype: float64"
             ]
           },
-          "execution_count": 90,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 25
         }
       ],
       "source": [
@@ -110,7 +110,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 91,
+      "execution_count": 26,
       "metadata": {
         "id": "1OPpS8a20_mr"
       },
@@ -132,27 +132,27 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 92,
+      "execution_count": 27,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 295
         },
         "id": "YMqzHMTi0_mr",
-        "outputId": "273355ba-d56d-4b13-c528-9e11823a72c8"
+        "outputId": "101c3bb6-6874-4602-f518-fa3f8bb6fb20"
       },
       "outputs": [
         {
+          "output_type": "display_data",
           "data": {
-            "image/png": 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",
+            "image/png": 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\n",
             "text/plain": [
               "<Figure size 432x288 with 1 Axes>"
             ]
           },
           "metadata": {
             "needs_background": "light"
-          },
-          "output_type": "display_data"
+          }
         }
       ],
       "source": [
@@ -177,27 +177,225 @@
     },
     {
       "cell_type": "markdown",
-      "metadata": {},
+      "metadata": {
+        "id": "9qMpMt5YWRqA"
+      },
       "source": [
         "Dropamos as rows com nan como value"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 93,
+      "source": [
+        "df_ids = pd.DataFrame(estatisticas_market[['id']])\n",
+        "df_ids"
+      ],
+      "metadata": {
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+        "colab": {
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+          "height": 424
+        },
+        "id": "hTJFTmeGY_39"
+      },
+      "execution_count": 28,
+      "outputs": [
+        {
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+          "data": {
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+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
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+    },
+    {
+      "cell_type": "code",
+      "execution_count": 29,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 956
         },
         "id": "XHos9RG60_mt",
-        "outputId": "aa00c441-b9f7-4ce2-d37b-4c3262749a6d"
+        "outputId": "ccfa4236-7033-4aa0-c0f3-bee2fc3615f7"
       },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
             "text/html": [
-              "<div>\n",
+              "\n",
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               "      <th>idade_empresa_anos</th>\n",
               "      <th>idade_emp_cat</th>\n",
               "      <th>fl_me</th>\n",
-              "      <th>...</th>\n",
+              "      <th>fl_sa</th>\n",
+              "      <th>fl_epp</th>\n",
+              "      <th>fl_mei</th>\n",
+              "      <th>fl_ltda</th>\n",
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+              "      <th>fl_st_especial</th>\n",
+              "      <th>fl_email</th>\n",
+              "      <th>fl_telefone</th>\n",
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+              "      <th>nm_segmento</th>\n",
+              "      <th>fl_spa</th>\n",
+              "      <th>fl_antt</th>\n",
+              "      <th>fl_veiculo</th>\n",
+              "      <th>vl_total_veiculos_pesados_grupo</th>\n",
+              "      <th>vl_total_veiculos_leves_grupo</th>\n",
+              "      <th>sg_uf_matriz</th>\n",
               "      <th>de_saude_tributaria</th>\n",
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               "      <td>5 a 10</td>\n",
               "      <td>False</td>\n",
-              "      <td>...</td>\n",
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+              "      <td>False</td>\n",
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@@ -382,6 +676,22 @@
               "      <td>...</td>\n",
               "      <td>...</td>\n",
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               "      <td>3.254795</td>\n",
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               "      <td>False</td>\n",
-              "      <td>...</td>\n",
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+              "      <td>False</td>\n",
+              "      <td>True</td>\n",
+              "      <td>True</td>\n",
+              "      <td>NAO</td>\n",
+              "      <td>COMERCIO E REPARACAO DE VEICULOS AUTOMOTORES E...</td>\n",
+              "      <td>COMERCIO; REPARACAO DE VEICULOS AUTOMOTORES E ...</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>0.0</td>\n",
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@@ -419,7 +745,23 @@
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               "      <td>False</td>\n",
-              "      <td>...</td>\n",
+              "      <td>False</td>\n",
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+              "      <td>ATIVIDADES ADMINISTRATIVAS E SERVICOS COMPLEME...</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>0.0</td>\n",
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@@ -443,7 +785,23 @@
               "      <td>20.745205</td>\n",
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+              "      <td>False</td>\n",
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+              "      <td>False</td>\n",
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               "      <td>1.909589</td>\n",
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               "      <td>False</td>\n",
-              "      <td>...</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2016-11-30</td>\n",
+              "      <td>False</td>\n",
+              "      <td>True</td>\n",
+              "      <td>False</td>\n",
+              "      <td>NAO</td>\n",
+              "      <td>COMERCIO VAREJISTA</td>\n",
+              "      <td>COMERCIO; REPARACAO DE VEICULOS AUTOMOTORES E ...</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>RO</td>\n",
               "      <td>VERDE</td>\n",
               "      <td>ACIMA DE 1 ANO</td>\n",
               "      <td>ALTA</td>\n",
@@ -491,7 +865,23 @@
               "      <td>0.797260</td>\n",
               "      <td>&lt;= 1</td>\n",
               "      <td>False</td>\n",
-              "      <td>...</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>True</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018-01-10</td>\n",
+              "      <td>False</td>\n",
+              "      <td>True</td>\n",
+              "      <td>True</td>\n",
+              "      <td>NAO</td>\n",
+              "      <td>CORREIO E OUTRAS ATIVIDADES DE ENTREGA</td>\n",
+              "      <td>TRANSPORTE ARMAZENAGEM E CORREIO</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>False</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>RO</td>\n",
               "      <td>CINZA</td>\n",
               "      <td>SEM INFORMACAO</td>\n",
               "      <td>BAIXA</td>\n",
@@ -506,119 +896,103 @@
               "  </tbody>\n",
               "</table>\n",
               "<p>432292 rows × 37 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "                                                       id  fl_matriz  \\\n",
-              "0       a6984c3ae395090e3bee8ad63c3758b110de096d5d8195...       True   \n",
-              "1       6178f41ade1365e44bc2c46654c2c8c0eaae27dcb476c4...       True   \n",
-              "2       4a7e5069a397f12fdd7fd57111d6dc5d3ba558958efc02...       True   \n",
-              "3       3348900fe63216a439d2e5238c79ddd46ede454df7b9d8...       True   \n",
-              "4       1f9bcabc9d3173c1fe769899e4fac14b053037b953a1e4...       True   \n",
-              "...                                                   ...        ...   \n",
-              "462293  469ee5fc984d0bb60aa2f40cda4d003d7c9b963d149ed3...       True   \n",
-              "462294  656f496e7e2fad708f0022d8ad97d2cb9344e839a5f3cb...       True   \n",
-              "462295  9b933a5cf2149d1338f00fb459d34a16b9b0f2e8d3e8e1...       True   \n",
-              "462296  84db0f17467cf4f02439e01ade57150b6ac59d9dae53ed...       True   \n",
-              "462297  3d43e934e150b86be1e67524f5ba1018b27da9ef25566d...       True   \n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7da9c857-5550-4cd4-8606-f2cae01742e3')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
               "\n",
-              "                 de_natureza_juridica sg_uf        natureza_juridica_macro  \\\n",
-              "0       SOCIEDADE EMPRESARIA LIMITADA    RN         ENTIDADES EMPRESARIAIS   \n",
-              "1               EMPRESARIO INDIVIDUAL    PI                         OUTROS   \n",
-              "2               EMPRESARIO INDIVIDUAL    AM                         OUTROS   \n",
-              "3               EMPRESARIO INDIVIDUAL    AM                         OUTROS   \n",
-              "4               EMPRESARIO INDIVIDUAL    RN                         OUTROS   \n",
-              "...                               ...   ...                            ...   \n",
-              "462293          EMPRESARIO INDIVIDUAL    RN                         OUTROS   \n",
-              "462294          EMPRESARIO INDIVIDUAL    PI                         OUTROS   \n",
-              "462295             ASSOCIACAO PRIVADA    MA  ENTIDADES SEM FINS LUCRATIVOS   \n",
-              "462296  SOCIEDADE EMPRESARIA LIMITADA    RO         ENTIDADES EMPRESARIAIS   \n",
-              "462297          EMPRESARIO INDIVIDUAL    RO                         OUTROS   \n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
               "\n",
-              "                                               de_ramo             setor  \\\n",
-              "0                              INDUSTRIA DA CONSTRUCAO  CONSTRUÇÃO CIVIL   \n",
-              "1                   SERVICOS DE ALOJAMENTO/ALIMENTACAO           SERVIÇO   \n",
-              "2                    TRANSPORTE, ARMAZENAGEM E CORREIO           SERVIÇO   \n",
-              "3                                    SERVICOS DIVERSOS           SERVIÇO   \n",
-              "4       SERVICOS PROFISSIONAIS, TECNICOS E CIENTIFICOS           SERVIÇO   \n",
-              "...                                                ...               ...   \n",
-              "462293                COMERCIO E REPARACAO DE VEICULOS          COMERCIO   \n",
-              "462294                        SERVICOS ADMINISTRATIVOS           SERVIÇO   \n",
-              "462295                               SERVICOS DE SAUDE           SERVIÇO   \n",
-              "462296                              COMERCIO VAREJISTA          COMERCIO   \n",
-              "462297               TRANSPORTE, ARMAZENAGEM E CORREIO           SERVIÇO   \n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
               "\n",
-              "        idade_empresa_anos idade_emp_cat  fl_me  ...  de_saude_tributaria  \\\n",
-              "0                14.457534       10 a 15  False  ...                VERDE   \n",
-              "1                 1.463014         1 a 5  False  ...                CINZA   \n",
-              "2                 7.093151        5 a 10  False  ...              AMARELO   \n",
-              "3                 6.512329        5 a 10  False  ...              AMARELO   \n",
-              "4                 3.200000         1 a 5  False  ...                VERDE   \n",
-              "...                    ...           ...    ...  ...                  ...   \n",
-              "462293            3.254795         1 a 5  False  ...                VERDE   \n",
-              "462294            8.953425        5 a 10  False  ...              LARANJA   \n",
-              "462295           20.745205          > 20  False  ...              AMARELO   \n",
-              "462296            1.909589         1 a 5  False  ...                VERDE   \n",
-              "462297            0.797260          <= 1  False  ...                CINZA   \n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
               "\n",
-              "        de_saude_rescencia  de_nivel_atividade  fl_simples_irregular  \\\n",
-              "0           ACIMA DE 1 ANO                ALTA                 False   \n",
-              "1                ATE 1 ANO               BAIXA                 False   \n",
-              "2           ACIMA DE 1 ANO               MEDIA                 False   \n",
-              "3           ACIMA DE 1 ANO               MEDIA                 False   \n",
-              "4           ACIMA DE 1 ANO                ALTA                 False   \n",
-              "...                    ...                 ...                   ...   \n",
-              "462293      ACIMA DE 1 ANO                ALTA                 False   \n",
-              "462294      ACIMA DE 1 ANO         MUITO BAIXA                 False   \n",
-              "462295      ACIMA DE 1 ANO               MEDIA                 False   \n",
-              "462296      ACIMA DE 1 ANO                ALTA                 False   \n",
-              "462297      SEM INFORMACAO               BAIXA                 False   \n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
               "\n",
-              "       fl_passivel_iss         de_faixa_faturamento_estimado  \\\n",
-              "0                 True  DE R$ 1.500.000,01 A R$ 4.800.000,00   \n",
-              "1                 True       DE R$ 81.000,01 A R$ 360.000,00   \n",
-              "2                 True                      ATE R$ 81.000,00   \n",
-              "3                 True       DE R$ 81.000,01 A R$ 360.000,00   \n",
-              "4                 True       DE R$ 81.000,01 A R$ 360.000,00   \n",
-              "...                ...                                   ...   \n",
-              "462293           False                      ATE R$ 81.000,00   \n",
-              "462294            True       DE R$ 81.000,01 A R$ 360.000,00   \n",
-              "462295            True       DE R$ 81.000,01 A R$ 360.000,00   \n",
-              "462296           False    DE R$ 360.000,01 A R$ 1.500.000,00   \n",
-              "462297            True       DE R$ 81.000,01 A R$ 360.000,00   \n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-7da9c857-5550-4cd4-8606-f2cae01742e3 button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
-              "         de_faixa_faturamento_estimado_grupo  vl_faturamento_estimado_aux  \\\n",
-              "0       DE R$ 1.500.000,01 A R$ 4.800.000,00                    3132172.8   \n",
-              "1            DE R$ 81.000,01 A R$ 360.000,00                     210000.0   \n",
-              "2                           ATE R$ 81.000,00                      50000.0   \n",
-              "3            DE R$ 81.000,01 A R$ 360.000,00                     210000.0   \n",
-              "4            DE R$ 81.000,01 A R$ 360.000,00                     210000.0   \n",
-              "...                                      ...                          ...   \n",
-              "462293                      ATE R$ 81.000,00                      50000.0   \n",
-              "462294       DE R$ 81.000,01 A R$ 360.000,00                     210000.0   \n",
-              "462295       DE R$ 81.000,01 A R$ 360.000,00                     210000.0   \n",
-              "462296    DE R$ 360.000,01 A R$ 1.500.000,00                     432734.4   \n",
-              "462297       DE R$ 81.000,01 A R$ 360.000,00                     210000.0   \n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-7da9c857-5550-4cd4-8606-f2cae01742e3');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
               "\n",
-              "       vl_faturamento_estimado_grupo_aux qt_filiais  \n",
-              "0                              3132172.8          0  \n",
-              "1                               210000.0          0  \n",
-              "2                                50000.0          0  \n",
-              "3                               210000.0          0  \n",
-              "4                               210000.0          0  \n",
-              "...                                  ...        ...  \n",
-              "462293                           50000.0          0  \n",
-              "462294                          210000.0          0  \n",
-              "462295                          210000.0          0  \n",
-              "462296                          432734.4          0  \n",
-              "462297                          210000.0          0  \n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n",
+              "  "
+            ],
+            "text/plain": [
+              "                                                       id  ...  qt_filiais\n",
+              "0       a6984c3ae395090e3bee8ad63c3758b110de096d5d8195...  ...           0\n",
+              "1       6178f41ade1365e44bc2c46654c2c8c0eaae27dcb476c4...  ...           0\n",
+              "2       4a7e5069a397f12fdd7fd57111d6dc5d3ba558958efc02...  ...           0\n",
+              "3       3348900fe63216a439d2e5238c79ddd46ede454df7b9d8...  ...           0\n",
+              "4       1f9bcabc9d3173c1fe769899e4fac14b053037b953a1e4...  ...           0\n",
+              "...                                                   ...  ...         ...\n",
+              "462293  469ee5fc984d0bb60aa2f40cda4d003d7c9b963d149ed3...  ...           0\n",
+              "462294  656f496e7e2fad708f0022d8ad97d2cb9344e839a5f3cb...  ...           0\n",
+              "462295  9b933a5cf2149d1338f00fb459d34a16b9b0f2e8d3e8e1...  ...           0\n",
+              "462296  84db0f17467cf4f02439e01ade57150b6ac59d9dae53ed...  ...           0\n",
+              "462297  3d43e934e150b86be1e67524f5ba1018b27da9ef25566d...  ...           0\n",
               "\n",
               "[432292 rows x 37 columns]"
             ]
           },
-          "execution_count": 93,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 29
         }
       ],
       "source": [
@@ -630,20 +1004,24 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 94,
+      "execution_count": 30,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 302
         },
         "id": "2SoNxOc_2w9q",
-        "outputId": "f5d5a148-3782-4ccb-95e9-a6f27e8462c5"
+        "outputId": "37ea474e-efab-469b-f7ec-40dbfe9b40a3"
       },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
             "text/html": [
-              "<div>\n",
+              "\n",
+              "  <div id=\"df-4588e5f8-6363-413a-9f50-a13c8e742fef\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
               "        vertical-align: middle;\n",
@@ -726,37 +1104,98 @@
               "    </tr>\n",
               "  </tbody>\n",
               "</table>\n",
-              "</div>"
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4588e5f8-6363-413a-9f50-a13c8e742fef')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-4588e5f8-6363-413a-9f50-a13c8e742fef button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-4588e5f8-6363-413a-9f50-a13c8e742fef');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n",
+              "  "
             ],
             "text/plain": [
-              "   idade_empresa_anos  vl_total_veiculos_pesados_grupo  \\\n",
-              "0           14.457534                              0.0   \n",
-              "1            1.463014                              0.0   \n",
-              "2            7.093151                              0.0   \n",
-              "3            6.512329                              0.0   \n",
-              "4            3.200000                              0.0   \n",
-              "5           38.079452                              0.0   \n",
-              "\n",
-              "   vl_total_veiculos_leves_grupo  vl_faturamento_estimado_aux  \\\n",
-              "0                            0.0                    3132172.8   \n",
-              "1                            0.0                     210000.0   \n",
-              "2                            0.0                      50000.0   \n",
-              "3                            0.0                     210000.0   \n",
-              "4                            0.0                     210000.0   \n",
-              "5                            0.0                     210000.0   \n",
+              "   idade_empresa_anos  ...  qt_filiais\n",
+              "0           14.457534  ...           0\n",
+              "1            1.463014  ...           0\n",
+              "2            7.093151  ...           0\n",
+              "3            6.512329  ...           0\n",
+              "4            3.200000  ...           0\n",
+              "5           38.079452  ...           0\n",
               "\n",
-              "   vl_faturamento_estimado_grupo_aux  qt_filiais  \n",
-              "0                          3132172.8           0  \n",
-              "1                           210000.0           0  \n",
-              "2                            50000.0           0  \n",
-              "3                           210000.0           0  \n",
-              "4                           210000.0           0  \n",
-              "5                           210000.0           0  "
+              "[6 rows x 6 columns]"
             ]
           },
-          "execution_count": 94,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 30
         }
       ],
       "source": [
@@ -766,37 +1205,37 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 95,
+      "execution_count": 31,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 461
         },
         "id": "AnCW6eGz3C9_",
-        "outputId": "3c3cd431-5274-4ce8-fc5f-29d3453801d3"
+        "outputId": "3d5b0ba0-b54f-4242-aa2e-4a6b97056446"
       },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "<AxesSubplot:>"
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f354bc99050>"
             ]
           },
-          "execution_count": 95,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 31
         },
         {
+          "output_type": "display_data",
           "data": {
-            "image/png": 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",
+            "image/png": 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\n",
             "text/plain": [
               "<Figure size 432x288 with 2 Axes>"
             ]
           },
           "metadata": {
             "needs_background": "light"
-          },
-          "output_type": "display_data"
+          }
         }
       ],
       "source": [
@@ -805,19 +1244,24 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 96,
+      "execution_count": 32,
       "metadata": {
         "colab": {
-          "base_uri": "https://localhost:8080/"
+          "base_uri": "https://localhost:8080/",
+          "height": 488
         },
         "id": "I7TwRpba3GCI",
-        "outputId": "fe2a96a0-0842-422e-9ae3-f0a8f85b6f84"
+        "outputId": "0cafa706-42f4-403e-aeaa-3fd4f4ada970"
       },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
             "text/html": [
-              "<div>\n",
+              "\n",
+              "  <div id=\"df-904107f3-cda3-48d3-96ae-0e5614686caa\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
               "        vertical-align: middle;\n",
@@ -1054,80 +1498,103 @@
               "  </tbody>\n",
               "</table>\n",
               "<p>432292 rows × 15 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "        fl_matriz  idade_empresa_anos  fl_me  fl_sa  fl_epp  fl_mei  fl_ltda  \\\n",
-              "0            True           14.457534  False  False   False   False    False   \n",
-              "1            True            1.463014  False  False   False    True    False   \n",
-              "2            True            7.093151  False  False   False    True    False   \n",
-              "3            True            6.512329  False  False   False   False    False   \n",
-              "4            True            3.200000  False  False   False   False    False   \n",
-              "...           ...                 ...    ...    ...     ...     ...      ...   \n",
-              "462293       True            3.254795  False  False   False    True    False   \n",
-              "462294       True            8.953425  False  False   False   False    False   \n",
-              "462295       True           20.745205  False  False   False   False    False   \n",
-              "462296       True            1.909589  False  False   False   False    False   \n",
-              "462297       True            0.797260  False  False   False    True    False   \n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-904107f3-cda3-48d3-96ae-0e5614686caa')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
               "\n",
-              "        fl_st_especial  fl_email  fl_telefone  \\\n",
-              "0                False      True         True   \n",
-              "1                False      True         True   \n",
-              "2                False     False         True   \n",
-              "3                False      True         True   \n",
-              "4                False      True         True   \n",
-              "...                ...       ...          ...   \n",
-              "462293           False      True         True   \n",
-              "462294           False     False        False   \n",
-              "462295           False     False        False   \n",
-              "462296           False      True        False   \n",
-              "462297           False      True         True   \n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
               "\n",
-              "        vl_total_veiculos_pesados_grupo  vl_total_veiculos_leves_grupo  \\\n",
-              "0                                   0.0                            0.0   \n",
-              "1                                   0.0                            0.0   \n",
-              "2                                   0.0                            0.0   \n",
-              "3                                   0.0                            0.0   \n",
-              "4                                   0.0                            0.0   \n",
-              "...                                 ...                            ...   \n",
-              "462293                              0.0                            0.0   \n",
-              "462294                              0.0                            0.0   \n",
-              "462295                              0.0                            0.0   \n",
-              "462296                              0.0                            0.0   \n",
-              "462297                              0.0                            0.0   \n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-904107f3-cda3-48d3-96ae-0e5614686caa button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
-              "        vl_faturamento_estimado_aux  vl_faturamento_estimado_grupo_aux  \\\n",
-              "0                         3132172.8                          3132172.8   \n",
-              "1                          210000.0                           210000.0   \n",
-              "2                           50000.0                            50000.0   \n",
-              "3                          210000.0                           210000.0   \n",
-              "4                          210000.0                           210000.0   \n",
-              "...                             ...                                ...   \n",
-              "462293                      50000.0                            50000.0   \n",
-              "462294                     210000.0                           210000.0   \n",
-              "462295                     210000.0                           210000.0   \n",
-              "462296                     432734.4                           432734.4   \n",
-              "462297                     210000.0                           210000.0   \n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-904107f3-cda3-48d3-96ae-0e5614686caa');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
               "\n",
-              "        qt_filiais  \n",
-              "0                0  \n",
-              "1                0  \n",
-              "2                0  \n",
-              "3                0  \n",
-              "4                0  \n",
-              "...            ...  \n",
-              "462293           0  \n",
-              "462294           0  \n",
-              "462295           0  \n",
-              "462296           0  \n",
-              "462297           0  \n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n",
+              "  "
+            ],
+            "text/plain": [
+              "        fl_matriz  ...  qt_filiais\n",
+              "0            True  ...           0\n",
+              "1            True  ...           0\n",
+              "2            True  ...           0\n",
+              "3            True  ...           0\n",
+              "4            True  ...           0\n",
+              "...           ...  ...         ...\n",
+              "462293       True  ...           0\n",
+              "462294       True  ...           0\n",
+              "462295       True  ...           0\n",
+              "462296       True  ...           0\n",
+              "462297       True  ...           0\n",
               "\n",
               "[432292 rows x 15 columns]"
             ]
           },
-          "execution_count": 96,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 32
         }
       ],
       "source": [
@@ -1138,129 +1605,118 @@
     },
     {
       "cell_type": "markdown",
-      "metadata": {},
+      "metadata": {
+        "id": "4136zjJ0WRqE"
+      },
       "source": [
         "### Aplicando one hot encoding"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 97,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "from sklearn.preprocessing import OneHotEncoder\n",
-        "from sklearn.preprocessing import LabelEncoder"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 111,
+      "execution_count": 35,
       "metadata": {
         "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 461
+          "base_uri": "https://localhost:8080/"
         },
         "id": "loeqBgNZ3KL-",
-        "outputId": "2270fd68-1dfd-4f03-a4a5-e36e9cd9302a"
+        "outputId": "73aa7ef1-2fd2-4392-c1b2-0ec0ed2600bd"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Index(['id', 'sg_uf_AC', 'sg_uf_AM', 'sg_uf_MA', 'sg_uf_PI', 'sg_uf_RN',\n",
+              "       'sg_uf_RO', 'natureza_juridica_macro_ADMINISTRACAO PUBLICA',\n",
+              "       'natureza_juridica_macro_CARGO POLITICO',\n",
+              "       'natureza_juridica_macro_ENTIDADES EMPRESARIAIS',\n",
+              "       'natureza_juridica_macro_ENTIDADES SEM FINS LUCRATIVOS',\n",
+              "       'natureza_juridica_macro_INSTITUICOES EXTRATERRITORIAIS',\n",
+              "       'natureza_juridica_macro_OUTROS',\n",
+              "       'natureza_juridica_macro_PESSOAS FISICAS', 'fl_rm_NAO', 'fl_rm_SIM',\n",
+              "       'nm_segmento_ADMINISTRACAO PUBLICA DEFESA E SEGURIDADE SOCIAL',\n",
+              "       'nm_segmento_AGRICULTURA PECUARIA PRODUCAO FLORESTAL PESCA E AQUICULTURA',\n",
+              "       'nm_segmento_AGUA ESGOTO ATIVIDADES DE GESTAO DE RESIDUOS E DESCONTAMINACAO',\n",
+              "       'nm_segmento_ALOJAMENTO E ALIMENTACAO',\n",
+              "       'nm_segmento_ARTES CULTURA ESPORTE E RECREACAO',\n",
+              "       'nm_segmento_ATIVIDADES ADMINISTRATIVAS E SERVICOS COMPLEMENTARES',\n",
+              "       'nm_segmento_ATIVIDADES FINANCEIRAS DE SEGUROS E SERVICOS RELACIONADOS',\n",
+              "       'nm_segmento_ATIVIDADES IMOBILIARIAS',\n",
+              "       'nm_segmento_ATIVIDADES PROFISSIONAIS CIENTIFICAS E TECNICAS',\n",
+              "       'nm_segmento_COMERCIO; REPARACAO DE VEICULOS AUTOMOTORES E MOTOCICLETAS',\n",
+              "       'nm_segmento_CONSTRUCAO', 'nm_segmento_EDUCACAO',\n",
+              "       'nm_segmento_ELETRICIDADE E GAS',\n",
+              "       'nm_segmento_INDUSTRIAS DE TRANSFORMACAO',\n",
+              "       'nm_segmento_INDUSTRIAS EXTRATIVAS',\n",
+              "       'nm_segmento_INFORMACAO E COMUNICACAO',\n",
+              "       'nm_segmento_ORGANISMOS INTERNACIONAIS E OUTRAS INSTITUICOES EXTRATERRITORIAIS',\n",
+              "       'nm_segmento_OUTRAS ATIVIDADES DE SERVICOS',\n",
+              "       'nm_segmento_SAUDE HUMANA E SERVICOS SOCIAIS',\n",
+              "       'nm_segmento_SERVICOS DOMESTICOS',\n",
+              "       'nm_segmento_TRANSPORTE ARMAZENAGEM E CORREIO', 'fl_spa_False',\n",
+              "       'fl_spa_True', 'fl_antt_False', 'fl_antt_True', 'fl_veiculo_False',\n",
+              "       'fl_veiculo_True', 'sg_uf_matriz_AC', 'sg_uf_matriz_AL',\n",
+              "       'sg_uf_matriz_AM', 'sg_uf_matriz_AP', 'sg_uf_matriz_BA',\n",
+              "       'sg_uf_matriz_CE', 'sg_uf_matriz_DF', 'sg_uf_matriz_ES',\n",
+              "       'sg_uf_matriz_GO', 'sg_uf_matriz_MA', 'sg_uf_matriz_MG',\n",
+              "       'sg_uf_matriz_MS', 'sg_uf_matriz_MT', 'sg_uf_matriz_PA',\n",
+              "       'sg_uf_matriz_PB', 'sg_uf_matriz_PE', 'sg_uf_matriz_PI',\n",
+              "       'sg_uf_matriz_PR', 'sg_uf_matriz_RJ', 'sg_uf_matriz_RN',\n",
+              "       'sg_uf_matriz_RO', 'sg_uf_matriz_RR', 'sg_uf_matriz_RS',\n",
+              "       'sg_uf_matriz_SC', 'sg_uf_matriz_SE', 'sg_uf_matriz_SP',\n",
+              "       'sg_uf_matriz_TO', 'de_saude_tributaria_AMARELO',\n",
+              "       'de_saude_tributaria_AZUL', 'de_saude_tributaria_CINZA',\n",
+              "       'de_saude_tributaria_LARANJA', 'de_saude_tributaria_VERDE',\n",
+              "       'de_saude_tributaria_VERMELHO', 'de_nivel_atividade_ALTA',\n",
+              "       'de_nivel_atividade_BAIXA', 'de_nivel_atividade_MEDIA',\n",
+              "       'de_nivel_atividade_MUITO BAIXA', 'fl_matriz', 'idade_empresa_anos',\n",
+              "       'fl_me', 'fl_sa', 'fl_epp', 'fl_mei', 'fl_ltda', 'fl_st_especial',\n",
+              "       'fl_email', 'fl_telefone', 'vl_total_veiculos_pesados_grupo',\n",
+              "       'vl_total_veiculos_leves_grupo', 'vl_faturamento_estimado_aux',\n",
+              "       'vl_faturamento_estimado_grupo_aux', 'qt_filiais'],\n",
+              "      dtype='object')"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 35
+        }
+      ],
       "source": [
-        "df_cat_copy = df_to_work_categorical\n",
+        "df_cat_copy = df_to_work_categorical.copy()\n",
         "df_to_work_categorical_without_id = df_cat_copy.drop(columns=[\"id\", \"de_natureza_juridica\", \"de_ramo\", \"dt_situacao\", \"fl_simples_irregular\", \"fl_passivel_iss\", \"de_saude_rescencia\", \"nm_divisao\", \"setor\", \"de_faixa_faturamento_estimado_grupo\", \"de_faixa_faturamento_estimado\", \"idade_emp_cat\"])\n",
         "\n",
-        "def get_encoder_labels(df):\n",
-        "    le = LabelEncoder()\n",
-        "    return df.apply(le.fit_transform)\n",
-        "\n",
-        "\n",
-        "\n",
-        "\n",
-        "def use_one_hot_encoder(df, head_number=100):\n",
+        "def use_one_hot_encoder(df):\n",
         "    encoder_df = pd.DataFrame(df)\n",
         "    return pd.get_dummies(encoder_df)\n",
         "\n",
-        "use_labelEncoder = get_encoder_labels(df_to_work_categorical_without_id)\n",
-        "df_with_one_hot = use_one_hot_encoder(df_to_work_categorical_without_id, 400000)\n",
-        "df_to_render = pd.merge\n",
-        "df_with_one_hot.to_csv(\"OHE_df.csv\")"
+        "df_with_one_hot = use_one_hot_encoder(df_to_work_categorical_without_id)\n",
+        "df_final_with_all_feat = pd.merge(df_with_one_hot, df_to_work_nums, left_index=True, right_index=True)\n",
+        "df_final_with_all_feat_id = pd.merge(df_ids, df_final_with_all_feat, left_index=True, right_index=True)\n",
+        "df_final_with_all_feat_id.columns"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 99,
+      "source": [
+        "df_final_with_all_feat_id.to_csv(\"OHE_df.csv\")"
+      ],
       "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "AqErUx5A60b6",
-        "outputId": "eef44767-353c-4385-980e-9b710a696795"
+        "id": "fNTpUxFHagyv"
       },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "['sg_uf', 6, array(['RN', 'PI', 'AM', 'MA', 'RO', 'AC'], dtype=object)]\n",
-            "['natureza_juridica_macro', 7, array(['ENTIDADES EMPRESARIAIS', 'OUTROS',\n",
-            "       'ENTIDADES SEM FINS LUCRATIVOS', 'ADMINISTRACAO PUBLICA',\n",
-            "       'PESSOAS FISICAS', 'CARGO POLITICO',\n",
-            "       'INSTITUICOES EXTRATERRITORIAIS'], dtype=object)]\n",
-            "['fl_rm', 2, array(['SIM', 'NAO'], dtype=object)]\n",
-            "['nm_segmento', 21, array(['CONSTRUCAO', 'ALOJAMENTO E ALIMENTACAO',\n",
-            "       'TRANSPORTE ARMAZENAGEM E CORREIO',\n",
-            "       'OUTRAS ATIVIDADES DE SERVICOS',\n",
-            "       'ATIVIDADES PROFISSIONAIS CIENTIFICAS E TECNICAS',\n",
-            "       'INDUSTRIAS DE TRANSFORMACAO',\n",
-            "       'COMERCIO; REPARACAO DE VEICULOS AUTOMOTORES E MOTOCICLETAS',\n",
-            "       'ATIVIDADES ADMINISTRATIVAS E SERVICOS COMPLEMENTARES',\n",
-            "       'INFORMACAO E COMUNICACAO', 'SAUDE HUMANA E SERVICOS SOCIAIS',\n",
-            "       'ARTES CULTURA ESPORTE E RECREACAO',\n",
-            "       'ATIVIDADES FINANCEIRAS DE SEGUROS E SERVICOS RELACIONADOS',\n",
-            "       'AGRICULTURA PECUARIA PRODUCAO FLORESTAL PESCA E AQUICULTURA',\n",
-            "       'ADMINISTRACAO PUBLICA DEFESA E SEGURIDADE SOCIAL',\n",
-            "       'SERVICOS DOMESTICOS', 'EDUCACAO', 'ELETRICIDADE E GAS',\n",
-            "       'INDUSTRIAS EXTRATIVAS',\n",
-            "       'AGUA ESGOTO ATIVIDADES DE GESTAO DE RESIDUOS E DESCONTAMINACAO',\n",
-            "       'ATIVIDADES IMOBILIARIAS',\n",
-            "       'ORGANISMOS INTERNACIONAIS E OUTRAS INSTITUICOES EXTRATERRITORIAIS'],\n",
-            "      dtype=object)]\n",
-            "['fl_spa', 2, array([False, True], dtype=object)]\n",
-            "['fl_antt', 2, array([False, True], dtype=object)]\n",
-            "['fl_veiculo', 2, array([False, True], dtype=object)]\n",
-            "['sg_uf_matriz', 27, array(['RN', 'PI', 'AM', 'MA', 'RO', 'AC', 'DF', 'CE', 'PB', 'SP', 'PR',\n",
-            "       'ES', 'PE', 'MG', 'RJ', 'RS', 'GO', 'SC', 'BA', 'MT', 'MS', 'PA',\n",
-            "       'RR', 'TO', 'AP', 'SE', 'AL'], dtype=object)]\n",
-            "['de_saude_tributaria', 6, array(['VERDE', 'CINZA', 'AMARELO', 'LARANJA', 'AZUL', 'VERMELHO'],\n",
-            "      dtype=object)]\n",
-            "['de_nivel_atividade', 4, array(['ALTA', 'BAIXA', 'MEDIA', 'MUITO BAIXA'], dtype=object)]\n",
-            "79\n"
-          ]
-        }
-      ],
-      "source": [
-        "df_copy_2 = df_to_work_categorical.copy()\n",
-        "df_droped = df_copy_2.drop(columns=[\"id\", \"de_natureza_juridica\", \"de_ramo\", \"dt_situacao\", \"fl_simples_irregular\", \"fl_passivel_iss\", \"de_saude_rescencia\", \"nm_divisao\", \"setor\", \"de_faixa_faturamento_estimado_grupo\", \"de_faixa_faturamento_estimado\", \"idade_emp_cat\"])\n",
-        "\n",
-        "count = 0\n",
-        "for col in df_droped.columns:\n",
-        "    count += len(df_droped[col].unique())\n",
-        "    s1 = [col, len(df_droped[col].unique()), df_droped[col].unique()]\n",
-        "    s2 = [col, len(df_droped[col].unique())]\n",
-        "    print(s1)\n",
-        "print(count)"
-      ]
+      "execution_count": 36,
+      "outputs": []
     },
     {
       "cell_type": "code",
-      "execution_count": 100,
+      "source": [
+        ""
+      ],
       "metadata": {
-        "id": "4Zh-1vEG7nLZ"
+        "id": "wtUjajLfbX61"
       },
-      "outputs": [],
-      "source": [
-        "colunas_categoricas_novo_filtro = ['de_natureza_juridica', 'de_faixa_faturamento_estimado', 'de_faixa_faturamento_estimado_grupo', 'nm_segmento', 'nm_divisao', 'setor', 'natureza_juridica_macro']"
-      ]
+      "execution_count": null,
+      "outputs": []
     }
   ],
   "metadata": {
@@ -1292,4 +1748,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}
\ No newline at end of file