001_preparacao_dos_dados.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preparação do dados\n",
    "_Feature Engineering_ e _Construção de Target_\n",
    "\n",
    "---\n",
    "\n",
    "## Sumário\n",
    "\n",
    "1. **Importação de bibliotecas**\n",
    "2. **Carregamento das bases**\n",
    "3. **Análise dos dataframes**\n",
    "4. **Feature Engineering**\n",
    "5. **Construção de Target**\n",
    "6. **Split do conjunto de dados**\n",
    "7. **Tratamento dos dados nulos/ausentes**\n",
    "8. **Gerando arquivos de treino e teste**\n",
    "\n",
    "<br>\n",
    "\n",
    "---\n",
    "\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Importação de bibliotecas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importação de pacotes e definição de parâmetros globais\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "import gc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configurações para exibição de dados no Jupyter Notebook\n",
    "\n",
    "# Configurar opção para exibir todas as linhas do Dataframe\n",
    "pd.set_option('display.max_rows', None)\n",
    "\n",
    "# Configurar para exibir o conteúdo completo das colunas\n",
    "pd.set_option('display.max_colwidth', None)\n",
    "\n",
    "# Configurar a supressão de mensagens de aviso durante a execução\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# Configurar estilo dos gráficos do seaborn\n",
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Carregamento das bases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Quantidade de objetos removidos da memória: 0\n"
     ]
    }
   ],
   "source": [
    "# Efetuando a limpeza da memória antes do carregamento dos dados\n",
    "print(f'\\nQuantidade de objetos removidos da memória: {gc.collect()}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "DATAFRAME: df_train\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Store</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>Date</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Customers</th>\n",
       "      <th>Open</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>5263</td>\n",
       "      <td>555</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>6064</td>\n",
       "      <td>625</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>8314</td>\n",
       "      <td>821</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>13995</td>\n",
       "      <td>1498</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>4822</td>\n",
       "      <td>559</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Store  DayOfWeek        Date  Sales  Customers  Open  Promo StateHoliday  \\\n",
       "0      1          5  2015-07-31   5263        555     1      1            0   \n",
       "1      2          5  2015-07-31   6064        625     1      1            0   \n",
       "2      3          5  2015-07-31   8314        821     1      1            0   \n",
       "3      4          5  2015-07-31  13995       1498     1      1            0   \n",
       "4      5          5  2015-07-31   4822        559     1      1            0   \n",
       "\n",
       "   SchoolHoliday  \n",
       "0              1  \n",
       "1              1  \n",
       "2              1  \n",
       "3              1  \n",
       "4              1  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Criando um dataframe a partir do arquivo train.csv\n",
    "df_train = pd.read_csv('dados/train.csv', sep=',')\n",
    "print('\\nDATAFRAME: df_train')\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "DATAFRAME: df_test\n"
     ]
    },
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Store</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday</th>\n",
       "      <th>SchoolHoliday</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2015-09-17</td>\n",
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       "      <th>1</th>\n",
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       "      <th>2</th>\n",
       "      <td>3</td>\n",
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       "      <td>4</td>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  Store  DayOfWeek        Date  Open  Promo StateHoliday  SchoolHoliday\n",
       "0   1      1          4  2015-09-17   1.0      1            0              0\n",
       "1   2      3          4  2015-09-17   1.0      1            0              0\n",
       "2   3      7          4  2015-09-17   1.0      1            0              0\n",
       "3   4      8          4  2015-09-17   1.0      1            0              0\n",
       "4   5      9          4  2015-09-17   1.0      1            0              0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Criando um dataframe a partir do arquivo test.csv\n",
    "df_test = pd.read_csv('dados/test.csv', sep=',')\n",
    "print('\\nDATAFRAME: df_test')\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "DATAFRAME: df_store\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\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>Store</th>\n",
       "      <th>StoreType</th>\n",
       "      <th>Assortment</th>\n",
       "      <th>CompetitionDistance</th>\n",
       "      <th>CompetitionOpenSinceMonth</th>\n",
       "      <th>CompetitionOpenSinceYear</th>\n",
       "      <th>Promo2</th>\n",
       "      <th>Promo2SinceWeek</th>\n",
       "      <th>Promo2SinceYear</th>\n",
       "      <th>PromoInterval</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>c</td>\n",
       "      <td>a</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>a</td>\n",
       "      <td>a</td>\n",
       "      <td>570.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Jan,Apr,Jul,Oct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>a</td>\n",
       "      <td>a</td>\n",
       "      <td>14130.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>Jan,Apr,Jul,Oct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>c</td>\n",
       "      <td>c</td>\n",
       "      <td>620.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>a</td>\n",
       "      <td>a</td>\n",
       "      <td>29910.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Store StoreType Assortment  CompetitionDistance  CompetitionOpenSinceMonth  \\\n",
       "0      1         c          a               1270.0                        9.0   \n",
       "1      2         a          a                570.0                       11.0   \n",
       "2      3         a          a              14130.0                       12.0   \n",
       "3      4         c          c                620.0                        9.0   \n",
       "4      5         a          a              29910.0                        4.0   \n",
       "\n",
       "   CompetitionOpenSinceYear  Promo2  Promo2SinceWeek  Promo2SinceYear  \\\n",
       "0                    2008.0       0              NaN              NaN   \n",
       "1                    2007.0       1             13.0           2010.0   \n",
       "2                    2006.0       1             14.0           2011.0   \n",
       "3                    2009.0       0              NaN              NaN   \n",
       "4                    2015.0       0              NaN              NaN   \n",
       "\n",
       "     PromoInterval  \n",
       "0              NaN  \n",
       "1  Jan,Apr,Jul,Oct  \n",
       "2  Jan,Apr,Jul,Oct  \n",
       "3              NaN  \n",
       "4              NaN  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Criando um dataframe a partir do arquivo store.csv\n",
    "df_store = pd.read_csv('dados/store.csv', sep=',')\n",
    "print('\\nDATAFRAME: df_store')\n",
    "df_store.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Análise dos dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "VOLUMETRIA\n",
      "\n",
      "df_train\n",
      "---------------------------------------------\n",
      "Quantidade de linhas (registros):  1017209\n",
      "Quantidade de colunas (variáveis): 9\n",
      "\n",
      "df_test\n",
      "---------------------------------------------\n",
      "Quantidade de linhas (registros):  41088\n",
      "Quantidade de colunas (variáveis): 8\n",
      "\n",
      "df_store\n",
      "---------------------------------------------\n",
      "Quantidade de linhas (registros):  1115\n",
      "Quantidade de colunas (variáveis): 10\n"
     ]
    }
   ],
   "source": [
    "# Exibindo a quantidade de linhas e colunas dos dataframes\n",
    "\n",
    "# Criação de um dicionário com os dataframes e seus respectivos nomes\n",
    "dfs = {\n",
    "    'df_train': df_train,\n",
    "    'df_test': df_test,\n",
    "    'df_store': df_store\n",
    "}\n",
    "\n",
    "# Iteração sobre o dicionário para exibir o nome e as dimensões dos dataframes\n",
    "print(f'\\nVOLUMETRIA')\n",
    "for nome, df in dfs.items():\n",
    "    print(f'\\n{nome}')\n",
    "    print(f'-'*45)\n",
    "    print(f'Quantidade de linhas (registros):  {df.shape[0]}')\n",
    "    print(f'Quantidade de colunas (variáveis): {df.shape[1]}')   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Unindo df_train com df_store\n",
    "df_train_full = pd.merge(df_train, df_store, on='Store', how='left')\n",
    "\n",
    "# Unindo df_train com df_store\n",
    "df_test_full = pd.merge(df_test, df_store, on='Store', how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>Date</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Customers</th>\n",
       "      <th>Open</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "      <th>StoreType</th>\n",
       "      <th>Assortment</th>\n",
       "      <th>CompetitionDistance</th>\n",
       "      <th>CompetitionOpenSinceMonth</th>\n",
       "      <th>CompetitionOpenSinceYear</th>\n",
       "      <th>Promo2</th>\n",
       "      <th>Promo2SinceWeek</th>\n",
       "      <th>Promo2SinceYear</th>\n",
       "      <th>PromoInterval</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>5263</td>\n",
       "      <td>555</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>c</td>\n",
       "      <td>a</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>6064</td>\n",
       "      <td>625</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>a</td>\n",
       "      <td>a</td>\n",
       "      <td>570.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Jan,Apr,Jul,Oct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>8314</td>\n",
       "      <td>821</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>a</td>\n",
       "      <td>a</td>\n",
       "      <td>14130.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>Jan,Apr,Jul,Oct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>13995</td>\n",
       "      <td>1498</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>c</td>\n",
       "      <td>c</td>\n",
       "      <td>620.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>4822</td>\n",
       "      <td>559</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>a</td>\n",
       "      <td>a</td>\n",
       "      <td>29910.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Store  DayOfWeek        Date  Sales  Customers  Open  Promo StateHoliday  \\\n",
       "0      1          5  2015-07-31   5263        555     1      1            0   \n",
       "1      2          5  2015-07-31   6064        625     1      1            0   \n",
       "2      3          5  2015-07-31   8314        821     1      1            0   \n",
       "3      4          5  2015-07-31  13995       1498     1      1            0   \n",
       "4      5          5  2015-07-31   4822        559     1      1            0   \n",
       "\n",
       "   SchoolHoliday StoreType Assortment  CompetitionDistance  \\\n",
       "0              1         c          a               1270.0   \n",
       "1              1         a          a                570.0   \n",
       "2              1         a          a              14130.0   \n",
       "3              1         c          c                620.0   \n",
       "4              1         a          a              29910.0   \n",
       "\n",
       "   CompetitionOpenSinceMonth  CompetitionOpenSinceYear  Promo2  \\\n",
       "0                        9.0                    2008.0       0   \n",
       "1                       11.0                    2007.0       1   \n",
       "2                       12.0                    2006.0       1   \n",
       "3                        9.0                    2009.0       0   \n",
       "4                        4.0                    2015.0       0   \n",
       "\n",
       "   Promo2SinceWeek  Promo2SinceYear    PromoInterval  \n",
       "0              NaN              NaN              NaN  \n",
       "1             13.0           2010.0  Jan,Apr,Jul,Oct  \n",
       "2             14.0           2011.0  Jan,Apr,Jul,Oct  \n",
       "3              NaN              NaN              NaN  \n",
       "4              NaN              NaN              NaN  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train_full.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "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>Id</th>\n",
       "      <th>Store</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "      <th>StoreType</th>\n",
       "      <th>Assortment</th>\n",
       "      <th>CompetitionDistance</th>\n",
       "      <th>CompetitionOpenSinceMonth</th>\n",
       "      <th>CompetitionOpenSinceYear</th>\n",
       "      <th>Promo2</th>\n",
       "      <th>Promo2SinceWeek</th>\n",
       "      <th>Promo2SinceYear</th>\n",
       "      <th>PromoInterval</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>c</td>\n",
       "      <td>a</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>a</td>\n",
       "      <td>a</td>\n",
       "      <td>14130.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>Jan,Apr,Jul,Oct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>24000.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>a</td>\n",
       "      <td>a</td>\n",
       "      <td>7520.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>2030.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  Store  DayOfWeek        Date  Open  Promo StateHoliday  SchoolHoliday  \\\n",
       "0   1      1          4  2015-09-17   1.0      1            0              0   \n",
       "1   2      3          4  2015-09-17   1.0      1            0              0   \n",
       "2   3      7          4  2015-09-17   1.0      1            0              0   \n",
       "3   4      8          4  2015-09-17   1.0      1            0              0   \n",
       "4   5      9          4  2015-09-17   1.0      1            0              0   \n",
       "\n",
       "  StoreType Assortment  CompetitionDistance  CompetitionOpenSinceMonth  \\\n",
       "0         c          a               1270.0                        9.0   \n",
       "1         a          a              14130.0                       12.0   \n",
       "2         a          c              24000.0                        4.0   \n",
       "3         a          a               7520.0                       10.0   \n",
       "4         a          c               2030.0                        8.0   \n",
       "\n",
       "   CompetitionOpenSinceYear  Promo2  Promo2SinceWeek  Promo2SinceYear  \\\n",
       "0                    2008.0       0              NaN              NaN   \n",
       "1                    2006.0       1             14.0           2011.0   \n",
       "2                    2013.0       0              NaN              NaN   \n",
       "3                    2014.0       0              NaN              NaN   \n",
       "4                    2000.0       0              NaN              NaN   \n",
       "\n",
       "     PromoInterval  \n",
       "0              NaN  \n",
       "1  Jan,Apr,Jul,Oct  \n",
       "2              NaN  \n",
       "3              NaN  \n",
       "4              NaN  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test_full.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Função para geração de um dataframe de metadados\n",
    "\n",
    "def gerar_metadados(dataframe):\n",
    "    '''\n",
    "    Gera um dataframe contendo metadados das colunas do dataframe fornecido.\n",
    "\n",
    "    :param dataframe: Dataframe\n",
    "        DataFrame para o qual os metadados serão gerados.\n",
    "    :return: DataFrame\n",
    "        DataFrame contendo os metadados.\n",
    "    '''\n",
    "    metadados = pd.DataFrame({\n",
    "        'Variável': dataframe.columns,\n",
    "        'Tipo': dataframe.dtypes,\n",
    "        'Qtde de nulos': dataframe.isnull().sum(),\n",
    "        '% de nulos': round((dataframe.isnull().sum()/len(dataframe))*100, 2),\n",
    "        'Cardinalidade': dataframe.nunique(),\n",
    "    })\n",
    "    metadados = metadados.sort_values(by='Qtde de nulos', ascending=False)\n",
    "    metadados = metadados.reset_index(drop=True)\n",
    "    return metadados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "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>Variável</th>\n",
       "      <th>Tipo</th>\n",
       "      <th>Qtde de nulos</th>\n",
       "      <th>% de nulos</th>\n",
       "      <th>Cardinalidade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PromoInterval</td>\n",
       "      <td>object</td>\n",
       "      <td>508031</td>\n",
       "      <td>49.94</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Promo2SinceYear</td>\n",
       "      <td>float64</td>\n",
       "      <td>508031</td>\n",
       "      <td>49.94</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Promo2SinceWeek</td>\n",
       "      <td>float64</td>\n",
       "      <td>508031</td>\n",
       "      <td>49.94</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CompetitionOpenSinceYear</td>\n",
       "      <td>float64</td>\n",
       "      <td>323348</td>\n",
       "      <td>31.79</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CompetitionOpenSinceMonth</td>\n",
       "      <td>float64</td>\n",
       "      <td>323348</td>\n",
       "      <td>31.79</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CompetitionDistance</td>\n",
       "      <td>float64</td>\n",
       "      <td>2642</td>\n",
       "      <td>0.26</td>\n",
       "      <td>654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>DayOfWeek</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Promo2</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Assortment</td>\n",
       "      <td>object</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Store</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SchoolHoliday</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>StateHoliday</td>\n",
       "      <td>object</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Promo</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Open</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Customers</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Sales</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>21734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Date</td>\n",
       "      <td>object</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>StoreType</td>\n",
       "      <td>object</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Variável     Tipo  Qtde de nulos  % de nulos  \\\n",
       "0               PromoInterval   object         508031       49.94   \n",
       "1             Promo2SinceYear  float64         508031       49.94   \n",
       "2             Promo2SinceWeek  float64         508031       49.94   \n",
       "3    CompetitionOpenSinceYear  float64         323348       31.79   \n",
       "4   CompetitionOpenSinceMonth  float64         323348       31.79   \n",
       "5         CompetitionDistance  float64           2642        0.26   \n",
       "6                   DayOfWeek    int64              0        0.00   \n",
       "7                      Promo2    int64              0        0.00   \n",
       "8                  Assortment   object              0        0.00   \n",
       "9                       Store    int64              0        0.00   \n",
       "10              SchoolHoliday    int64              0        0.00   \n",
       "11               StateHoliday   object              0        0.00   \n",
       "12                      Promo    int64              0        0.00   \n",
       "13                       Open    int64              0        0.00   \n",
       "14                  Customers    int64              0        0.00   \n",
       "15                      Sales    int64              0        0.00   \n",
       "16                       Date   object              0        0.00   \n",
       "17                  StoreType   object              0        0.00   \n",
       "\n",
       "    Cardinalidade  \n",
       "0               3  \n",
       "1               7  \n",
       "2              24  \n",
       "3              23  \n",
       "4              12  \n",
       "5             654  \n",
       "6               7  \n",
       "7               2  \n",
       "8               3  \n",
       "9            1115  \n",
       "10              2  \n",
       "11              5  \n",
       "12              2  \n",
       "13              2  \n",
       "14           4086  \n",
       "15          21734  \n",
       "16            942  \n",
       "17              4  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exibindo os metadados do dataframe unificado de treino\n",
    "gerar_metadados(df_train_full)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Customers', 'Sales'], dtype='object')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Colunas que estão em df_train_full mas não em df_test_full\n",
    "diff_columns = df_train_full.columns.difference(df_test_full.columns)\n",
    "diff_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Id'], dtype='object')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Colunas que estão em  df_test_full mas não em df_train_full\n",
    "diff_columns = df_test_full.columns.difference(df_train_full.columns)\n",
    "diff_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Excluindo coluna 'Id' de df_test_full\n",
    "# A coluna não existe em df_train_full\n",
    "df_test_full = df_test_full.drop('Id', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transforma para o tipo de dados datetime\n",
    "df_train_full['Date'] = pd.to_datetime(df_train_full['Date'])\n",
    "df_test_full['Date'] = pd.to_datetime(df_test_full['Date'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dicionário com os dataframes de treino e teste\n",
    "dfs = {\n",
    "    'df_train_full': df_train_full,\n",
    "    'df_test_full': df_test_full\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Variáveis temporais\n",
    "\n",
    "for name, df in dfs.items():\n",
    "    df['Year'] = df['Date'].dt.year\n",
    "    df['Month'] = df['Date'].dt.month\n",
    "    df['Day'] = df['Date'].dt.day\n",
    "    df['Quarter'] = df['Date'].dt.quarter\n",
    "    df['DayOfWeek'] = df['Date'].dt.dayofweek\n",
    "    df['IsWeekend'] = df['Date'].dt.dayofweek >= 5\n",
    "    df['DayOfYear'] = df['Date'].dt.dayofyear"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Variáveis da concorrência\n",
    "\n",
    "def calculate_months_since_competition_opened(sub_df):\n",
    "    '''\n",
    "    Calcula o número de meses desde que a concorrência abriu para cada loja.\n",
    "    \n",
    "    :param sub_df: dataframe\n",
    "        Um DataFrame contendo as colunas expecíficas\n",
    "    :return: Series\n",
    "        Uma série com o número de meses desde que a concorrência abriu, com\n",
    "        valore maiores ou iguais a zero(0).\n",
    "    ''' \n",
    "    months = (sub_df['Year'] - sub_df['CompetitionOpenSinceYear']) * 12 + (\n",
    "        sub_df['Month'] - sub_df['CompetitionOpenSinceMonth'])\n",
    "    return months.clip(lower=0)\n",
    "\n",
    "\n",
    "def calculate_years_since_competition_opened(sub_df):\n",
    "    '''\n",
    "    Calcula o número de anos desde que a concorrência abriu para cada loja.\n",
    "    \n",
    "    :param sub_df: dataframe\n",
    "        Um DataFrame contendo as colunas expecíficas\n",
    "    :return: Series\n",
    "        Uma série com o número de anos desde que a concorrência abriu, com\n",
    "        valore maiores ou iguais a zero(0).\n",
    "    ''' \n",
    "    years = (sub_df['Year'] - sub_df['CompetitionOpenSinceYear']) + (\n",
    "        sub_df['Month'] - sub_df['CompetitionOpenSinceMonth']) / 12\n",
    "    return years.clip(lower=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "for name, df in dfs.items():\n",
    "\n",
    "\tdf['MonthsSinceTheCompetitionOpened'] = (\n",
    "\t\tdf.groupby('Store').apply(calculate_months_since_competition_opened\n",
    "                            ).reset_index(drop=True))\n",
    "\n",
    "\tdf['YearsSinceTheCompetitionOpened'] = (\n",
    "\t\tdf.groupby('Store').apply(calculate_years_since_competition_opened\n",
    "                            ).reset_index(drop=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Variáveis de somas móveis\n",
    "\n",
    "def add_rolling_sums(df, windows, vars):\n",
    "    '''\n",
    "    Adicionar variáveis de somas móveis.\n",
    "    \n",
    "    param df: Dataframe\n",
    "        DataFrame onde as somas móveis serão adicionadas.\n",
    "    param windows: list\n",
    "        Lista de tamanhos de janelas móveis para calcular a soma.\n",
    "    param vars:\n",
    "        Lista contendo duas strings: a primeira é a variável para agrupar e a segunda\n",
    "        é a variável sobre a qual calcular a soma móvel.\n",
    "        \n",
    "    return: Dataframe\n",
    "        DataFrame original com as novas colunas de soma móvel adicionadas.\n",
    "    '''\n",
    "    for window in windows:\n",
    "        name = f'{vars[1]}RollingSum_{window}'\n",
    "        df[name] = df.groupby(vars[0])[vars[1]].transform(lambda x: x.rolling(window=window).sum())\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "windows = [3, 5, 7, 14, 21, 28, 30, 60, 90, 120, 150, 180, 360]\n",
    "vars = ['Store', 'Promo']\n",
    "\n",
    "df_train_full = add_rolling_sums(df_train_full, windows, vars)\n",
    "df_test_full = add_rolling_sums(df_test_full, windows, vars)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Construção de target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Soma das vendas nos próximos 42 dias (6 semanas), excluindo o dia atual\n",
    "df_train_full['Target'] = df_train_full.groupby('Store')['Sales'].transform(\n",
    "    lambda x: x.rolling(window=42, min_periods=1).sum().shift(-42))\n",
    "\n",
    "# Definir Target como zero para os dias com 'Sales' igual a zero\n",
    "# Ajuste necessário pois algumas lojas não abrem em dias de\n",
    "# sábado, domingo e feirados.\n",
    "df_train_full['Target'] = np.where(df_train_full['Sales'] == 0, 0, df_train_full['Target'])\n",
    "\n",
    "# Remover as linhas onde o Target não pode ser calculado (últimos 42 dias)\n",
    "df_train_full.dropna(subset=['Target'], inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "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>Store</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5263</td>\n",
       "      <td>157057.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>6064</td>\n",
       "      <td>176872.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>8314</td>\n",
       "      <td>245876.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>13995</td>\n",
       "      <td>355383.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>4822</td>\n",
       "      <td>162083.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Store  Sales    Target\n",
       "0      1   5263  157057.0\n",
       "1      2   6064  176872.0\n",
       "2      3   8314  245876.0\n",
       "3      4  13995  355383.0\n",
       "4      5   4822  162083.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train_full[['Store', 'Sales', 'Target']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Split do conjunto de dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Customers', 'Sales', 'Target'], dtype='object')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Colunas que estão em df_train_full mas não em df_test_full\n",
    "diff_columns = df_train_full.columns.difference(df_test_full.columns)\n",
    "diff_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([], dtype='object')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Colunas que estão em  df_test_full mas não em df_train_full\n",
    "diff_columns = df_test_full.columns.difference(df_train_full.columns)\n",
    "diff_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Excluindo as colunas 'Customers' e 'Sales' de df_train_full\n",
    "# As colunas não existe em df_test_full e não serão utilizadas\n",
    "# na construção do modelo preditivo.\n",
    "df_train_full = df_train_full.drop(['Customers', 'Sales'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tamanho do conjunto de treino: (978360, 38)\n",
      "Data inicial: 2013-01-01 00:00:00\n",
      "Data final:   2015-07-31 00:00:00\n",
      "\n",
      "Tamanho do conjunto de teste: (41088, 37)\n",
      "Data inicial: 2015-08-01 00:00:00\n",
      "Data final:   2015-09-17 00:00:00\n"
     ]
    }
   ],
   "source": [
    "print(f'Tamanho do conjunto de treino: {df_train_full.shape}\\n'\n",
    "      f'Data inicial: {df_train_full['Date'].min()}\\n'\n",
    "      f'Data final:   {df_train_full['Date'].max()}')\n",
    "\n",
    "print(f'\\nTamanho do conjunto de teste: {df_test_full.shape}\\n'\n",
    "      f'Data inicial: {df_test_full['Date'].min()}\\n'\n",
    "      f'Data final:   {df_test_full['Date'].max()}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Definindo a data de corte para o último mês\n",
    "cut_off_date = df_train_full['Date'].max() - pd.DateOffset(months=1)\n",
    "\n",
    "# Criando o DataFrame de validação\n",
    "df_validation_full = df_train_full[df_train_full['Date'] > cut_off_date]\n",
    "\n",
    "# Atualizando df_train_full para remover os dados de validação\n",
    "df_train_full = df_train_full[df_train_full['Date'] <= cut_off_date]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tamanho do conjunto de treino: (943795, 38)\n",
      "Data inicial: 2013-01-01 00:00:00\n",
      "Data final:   2015-06-30 00:00:00\n",
      "\n",
      "Tamanho do conjunto de validação: (34565, 38)\n",
      "Data inicial: 2015-07-01 00:00:00\n",
      "Data final:   2015-07-31 00:00:00\n",
      "\n",
      "Tamanho do conjunto de teste: (41088, 37)\n",
      "Data inicial: 2015-08-01 00:00:00\n",
      "Data final:   2015-09-17 00:00:00\n"
     ]
    }
   ],
   "source": [
    "print(f'Tamanho do conjunto de treino: {df_train_full.shape}\\n'\n",
    "      f'Data inicial: {df_train_full['Date'].min()}\\n'\n",
    "      f'Data final:   {df_train_full['Date'].max()}')\n",
    "\n",
    "print(f'\\nTamanho do conjunto de validação: {df_validation_full.shape}\\n'\n",
    "      f'Data inicial: {df_validation_full['Date'].min()}\\n'\n",
    "      f'Data final:   {df_validation_full['Date'].max()}')\n",
    "\n",
    "print(f'\\nTamanho do conjunto de teste: {df_test_full.shape}\\n'\n",
    "      f'Data inicial: {df_test_full['Date'].min()}\\n'\n",
    "      f'Data final:   {df_test_full['Date'].max()}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. Tratamento dos dados nulos/ausentes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "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>Variável</th>\n",
       "      <th>Tipo</th>\n",
       "      <th>Qtde de nulos</th>\n",
       "      <th>% de nulos</th>\n",
       "      <th>Cardinalidade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PromoInterval</td>\n",
       "      <td>object</td>\n",
       "      <td>472224</td>\n",
       "      <td>50.03</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Promo2SinceYear</td>\n",
       "      <td>float64</td>\n",
       "      <td>472224</td>\n",
       "      <td>50.03</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Promo2SinceWeek</td>\n",
       "      <td>float64</td>\n",
       "      <td>472224</td>\n",
       "      <td>50.03</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PromoRollingSum_360</td>\n",
       "      <td>float64</td>\n",
       "      <td>365720</td>\n",
       "      <td>38.75</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>YearsSinceTheCompetitionOpened</td>\n",
       "      <td>float64</td>\n",
       "      <td>304228</td>\n",
       "      <td>32.23</td>\n",
       "      <td>350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MonthsSinceTheCompetitionOpened</td>\n",
       "      <td>float64</td>\n",
       "      <td>304228</td>\n",
       "      <td>32.23</td>\n",
       "      <td>336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CompetitionOpenSinceMonth</td>\n",
       "      <td>float64</td>\n",
       "      <td>300043</td>\n",
       "      <td>31.79</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CompetitionOpenSinceYear</td>\n",
       "      <td>float64</td>\n",
       "      <td>300043</td>\n",
       "      <td>31.79</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>PromoRollingSum_180</td>\n",
       "      <td>float64</td>\n",
       "      <td>165020</td>\n",
       "      <td>17.48</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>PromoRollingSum_150</td>\n",
       "      <td>float64</td>\n",
       "      <td>131570</td>\n",
       "      <td>13.94</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>PromoRollingSum_120</td>\n",
       "      <td>float64</td>\n",
       "      <td>98120</td>\n",
       "      <td>10.40</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>PromoRollingSum_90</td>\n",
       "      <td>float64</td>\n",
       "      <td>64670</td>\n",
       "      <td>6.85</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>PromoRollingSum_60</td>\n",
       "      <td>float64</td>\n",
       "      <td>31220</td>\n",
       "      <td>3.31</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>CompetitionDistance</td>\n",
       "      <td>float64</td>\n",
       "      <td>2444</td>\n",
       "      <td>0.26</td>\n",
       "      <td>654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>PromoRollingSum_30</td>\n",
       "      <td>float64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>PromoRollingSum_28</td>\n",
       "      <td>float64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>PromoRollingSum_21</td>\n",
       "      <td>float64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>PromoRollingSum_14</td>\n",
       "      <td>float64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>PromoRollingSum_7</td>\n",
       "      <td>float64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>PromoRollingSum_5</td>\n",
       "      <td>float64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>PromoRollingSum_3</td>\n",
       "      <td>float64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Store</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Quarter</td>\n",
       "      <td>int32</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>DayOfYear</td>\n",
       "      <td>int32</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>IsWeekend</td>\n",
       "      <td>bool</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>DayOfWeek</td>\n",
       "      <td>int32</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Day</td>\n",
       "      <td>int32</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Month</td>\n",
       "      <td>int32</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Year</td>\n",
       "      <td>int32</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Promo2</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Assortment</td>\n",
       "      <td>object</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>StoreType</td>\n",
       "      <td>object</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>SchoolHoliday</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>StateHoliday</td>\n",
       "      <td>object</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Promo</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Open</td>\n",
       "      <td>int64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Date</td>\n",
       "      <td>datetime64[ns]</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Target</td>\n",
       "      <td>float64</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>278695</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Variável            Tipo  Qtde de nulos  \\\n",
       "0                     PromoInterval          object         472224   \n",
       "1                   Promo2SinceYear         float64         472224   \n",
       "2                   Promo2SinceWeek         float64         472224   \n",
       "3               PromoRollingSum_360         float64         365720   \n",
       "4    YearsSinceTheCompetitionOpened         float64         304228   \n",
       "5   MonthsSinceTheCompetitionOpened         float64         304228   \n",
       "6         CompetitionOpenSinceMonth         float64         300043   \n",
       "7          CompetitionOpenSinceYear         float64         300043   \n",
       "8               PromoRollingSum_180         float64         165020   \n",
       "9               PromoRollingSum_150         float64         131570   \n",
       "10              PromoRollingSum_120         float64          98120   \n",
       "11               PromoRollingSum_90         float64          64670   \n",
       "12               PromoRollingSum_60         float64          31220   \n",
       "13              CompetitionDistance         float64           2444   \n",
       "14               PromoRollingSum_30         float64              0   \n",
       "15               PromoRollingSum_28         float64              0   \n",
       "16               PromoRollingSum_21         float64              0   \n",
       "17               PromoRollingSum_14         float64              0   \n",
       "18                PromoRollingSum_7         float64              0   \n",
       "19                PromoRollingSum_5         float64              0   \n",
       "20                PromoRollingSum_3         float64              0   \n",
       "21                            Store           int64              0   \n",
       "22                          Quarter           int32              0   \n",
       "23                        DayOfYear           int32              0   \n",
       "24                        IsWeekend            bool              0   \n",
       "25                        DayOfWeek           int32              0   \n",
       "26                              Day           int32              0   \n",
       "27                            Month           int32              0   \n",
       "28                             Year           int32              0   \n",
       "29                           Promo2           int64              0   \n",
       "30                       Assortment          object              0   \n",
       "31                        StoreType          object              0   \n",
       "32                    SchoolHoliday           int64              0   \n",
       "33                     StateHoliday          object              0   \n",
       "34                            Promo           int64              0   \n",
       "35                             Open           int64              0   \n",
       "36                             Date  datetime64[ns]              0   \n",
       "37                           Target         float64              0   \n",
       "\n",
       "    % de nulos  Cardinalidade  \n",
       "0        50.03              3  \n",
       "1        50.03              7  \n",
       "2        50.03             24  \n",
       "3        38.75             20  \n",
       "4        32.23            350  \n",
       "5        32.23            336  \n",
       "6        31.79             12  \n",
       "7        31.79             23  \n",
       "8        17.48             16  \n",
       "9        13.94             16  \n",
       "10       10.40             12  \n",
       "11        6.85             12  \n",
       "12        3.31             13  \n",
       "13        0.26            654  \n",
       "14        0.00             13  \n",
       "15        0.00             11  \n",
       "16        0.00              7  \n",
       "17        0.00             11  \n",
       "18        0.00              6  \n",
       "19        0.00              6  \n",
       "20        0.00              4  \n",
       "21        0.00           1115  \n",
       "22        0.00              4  \n",
       "23        0.00            365  \n",
       "24        0.00              2  \n",
       "25        0.00              7  \n",
       "26        0.00             31  \n",
       "27        0.00             12  \n",
       "28        0.00              3  \n",
       "29        0.00              2  \n",
       "30        0.00              3  \n",
       "31        0.00              4  \n",
       "32        0.00              2  \n",
       "33        0.00              5  \n",
       "34        0.00              2  \n",
       "35        0.00              2  \n",
       "36        0.00            911  \n",
       "37        0.00         278695  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exibindo os metadados do dataframe unificado de treino\n",
    "gerar_metadados(df_train_full)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preenchendo todos os valores ausentes da coluna 'PromoInterval' com o\n",
    "# valor 'NoPromoInterval' (sem intervalo de promoções)\n",
    "\n",
    "df_train_full.loc[:,'PromoInterval'] = df_train_full['PromoInterval'].fillna('NoPromoInterval')\n",
    "df_validation_full.loc[:,'PromoInterval'] = df_train_full['PromoInterval'].fillna('NoPromoInterval')\n",
    "df_test_full.loc[:,'PromoInterval'] = df_test_full['PromoInterval'].fillna('NoPromoInterval')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preenchendo todos os valores ausentes das colunas numéricas com o valor zero '0'\n",
    "\n",
    "df_train_full.fillna(0, inplace=True)\n",
    "df_validation_full.fillna(0, inplace=True)\n",
    "df_test_full.fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8. Gerando arquivos de treino e teste"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Arquivo train_001.csv gerado com sucesso!\n",
      "\n",
      "Arquivo validation_001.csv gerado com sucesso!\n",
      "\n",
      "Arquivo test_001.csv gerado com sucesso!\n"
     ]
    }
   ],
   "source": [
    "# Dicionário com os dataframes a serem transformados em arquivos csv\n",
    "files_csv = {\n",
    "    'train' : df_train_full,\n",
    "    'validation' : df_validation_full,\n",
    "    'test' : df_test_full\n",
    "}\n",
    "\n",
    "# Percorre o dicionário para salvar cada dataframe como um arquivo CSV\n",
    "for name, df in files_csv.items():\n",
    "    try:\n",
    "        df.to_csv(f'dados/{name}_001.csv', index=False)\n",
    "        print(f'\\nArquivo {name}_001.csv gerado com sucesso!')\n",
    "    except Exception as e:\n",
    "        print(f'\\nErro ao salvar o arquivo: {e}')"
   ]
  }
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