EDA Preço de casas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Leitura de dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>tipo</th>\n",
       "      <th>bairro</th>\n",
       "      <th>tipo_vendedor</th>\n",
       "      <th>quartos</th>\n",
       "      <th>suites</th>\n",
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       "      <th>area_extra</th>\n",
       "      <th>diferenciais</th>\n",
       "      <th>...</th>\n",
       "      <th>piscina</th>\n",
       "      <th>playground</th>\n",
       "      <th>quadra</th>\n",
       "      <th>s_festas</th>\n",
       "      <th>s_jogos</th>\n",
       "      <th>s_ginastica</th>\n",
       "      <th>sauna</th>\n",
       "      <th>vista_mar</th>\n",
       "      <th>origem</th>\n",
       "      <th>preco</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Tamarineira</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
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       "      <th>2</th>\n",
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       "      <td>Apartamento</td>\n",
       "      <td>Boa Viagem</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>115</td>\n",
       "      <td>20</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Iputinga</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>92</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Engenho do Meio</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e copa</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4678</th>\n",
       "      <td>6678</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Boa Viagem</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>170</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>1200000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4679</th>\n",
       "      <td>6679</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Setubal</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>82</td>\n",
       "      <td>0</td>\n",
       "      <td>churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>258000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4680</th>\n",
       "      <td>6680</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Torre</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>75</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>252000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4681</th>\n",
       "      <td>6681</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Casa Amarela</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e copa</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>780000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4682</th>\n",
       "      <td>6682</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Madalena</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e playground</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>577035.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6683 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Id         tipo           bairro tipo_vendedor  quartos  suites  \\\n",
       "0        0  Apartamento             Pina   Imobiliaria        4       4   \n",
       "1        1  Apartamento      Tamarineira   Imobiliaria        2       0   \n",
       "2        2  Apartamento       Boa Viagem   Imobiliaria        3       1   \n",
       "3        3  Apartamento         Iputinga   Imobiliaria        3       0   \n",
       "4        4  Apartamento  Engenho do Meio   Imobiliaria        3       1   \n",
       "...    ...          ...              ...           ...      ...     ...   \n",
       "4678  6678  Apartamento       Boa Viagem   Imobiliaria        4       4   \n",
       "4679  6679  Apartamento          Setubal   Imobiliaria        2       0   \n",
       "4680  6680  Apartamento            Torre   Imobiliaria        3       1   \n",
       "4681  6681  Apartamento     Casa Amarela   Imobiliaria        3       2   \n",
       "4682  6682  Apartamento         Madalena   Imobiliaria        3       1   \n",
       "\n",
       "      vagas  area_util  area_extra             diferenciais  ...  piscina  \\\n",
       "0         3        182           0        copa e playground  ...        0   \n",
       "1         1         85           0                   nenhum  ...        0   \n",
       "2         2        115          20  piscina e churrasqueira  ...        1   \n",
       "3         1         92           0                   nenhum  ...        0   \n",
       "4         1         65           0           piscina e copa  ...        1   \n",
       "...     ...        ...         ...                      ...  ...      ...   \n",
       "4678      3        170           0  piscina e churrasqueira  ...        1   \n",
       "4679      1         82           0            churrasqueira  ...        0   \n",
       "4680      1         75           0                   nenhum  ...        0   \n",
       "4681      3        136           0           piscina e copa  ...        1   \n",
       "4682      2         84           0     piscina e playground  ...        1   \n",
       "\n",
       "      playground  quadra  s_festas  s_jogos  s_ginastica  sauna  vista_mar  \\\n",
       "0              1       0         0        0            0      0          0   \n",
       "1              0       0         0        0            0      0          0   \n",
       "2              0       0         0        0            0      0          0   \n",
       "3              0       0         0        0            0      0          0   \n",
       "4              0       0         0        0            0      0          0   \n",
       "...          ...     ...       ...      ...          ...    ...        ...   \n",
       "4678           0       0         0        0            0      0          0   \n",
       "4679           0       0         0        0            0      0          0   \n",
       "4680           0       0         0        0            0      0          0   \n",
       "4681           0       0         0        0            0      0          0   \n",
       "4682           1       0         0        0            0      0          0   \n",
       "\n",
       "      origem      preco  \n",
       "0      teste        NaN  \n",
       "1      teste        NaN  \n",
       "2      teste        NaN  \n",
       "3      teste        NaN  \n",
       "4      teste        NaN  \n",
       "...      ...        ...  \n",
       "4678  treino  1200000.0  \n",
       "4679  treino   258000.0  \n",
       "4680  treino   252000.0  \n",
       "4681  treino   780000.0  \n",
       "4682  treino   577035.0  \n",
       "\n",
       "[6683 rows x 22 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test = pd.read_csv('data/desafio 2/conjunto_de_teste_1.csv')\n",
    "train = pd.read_csv('data/desafio 2/conjunto_de_treinamento.csv')\n",
    "\n",
    "test['origem'] = 'teste'\n",
    "train['origem'] = 'treino'\n",
    "# house pricing df\n",
    "hp_df = pd.concat([test, train])\n",
    "\n",
    "hp_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id                   0\n",
       "tipo                 0\n",
       "bairro               0\n",
       "tipo_vendedor        0\n",
       "quartos              0\n",
       "suites               0\n",
       "vagas                0\n",
       "area_util            0\n",
       "area_extra           0\n",
       "diferenciais         0\n",
       "churrasqueira        0\n",
       "estacionamento       0\n",
       "piscina              0\n",
       "playground           0\n",
       "quadra               0\n",
       "s_festas             0\n",
       "s_jogos              0\n",
       "s_ginastica          0\n",
       "sauna                0\n",
       "vista_mar            0\n",
       "preco             2000\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hp_df.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id                  int64\n",
       "tipo               object\n",
       "bairro             object\n",
       "tipo_vendedor      object\n",
       "quartos             int64\n",
       "suites              int64\n",
       "vagas               int64\n",
       "area_util           int64\n",
       "area_extra          int64\n",
       "diferenciais       object\n",
       "churrasqueira       int64\n",
       "estacionamento      int64\n",
       "piscina             int64\n",
       "playground          int64\n",
       "quadra              int64\n",
       "s_festas            int64\n",
       "s_jogos             int64\n",
       "s_ginastica         int64\n",
       "sauna               int64\n",
       "vista_mar           int64\n",
       "origem             object\n",
       "preco             float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hp_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>tipo</th>\n",
       "      <th>bairro</th>\n",
       "      <th>tipo_vendedor</th>\n",
       "      <th>diferenciais</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Pina</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>copa e playground</td>\n",
       "      <td>teste</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Tamarineira</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>teste</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Boa Viagem</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>teste</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Iputinga</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>teste</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Engenho do Meio</td>\n",
       "      <td>Imobiliaria</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4678</th>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Boa Viagem</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>treino</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4679</th>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Setubal</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>churrasqueira</td>\n",
       "      <td>treino</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4680</th>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Torre</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>treino</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4681</th>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Casa Amarela</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>piscina e copa</td>\n",
       "      <td>treino</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4682</th>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Madalena</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>piscina e playground</td>\n",
       "      <td>treino</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6683 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             tipo           bairro tipo_vendedor             diferenciais  \\\n",
       "0     Apartamento             Pina   Imobiliaria        copa e playground   \n",
       "1     Apartamento      Tamarineira   Imobiliaria                   nenhum   \n",
       "2     Apartamento       Boa Viagem   Imobiliaria  piscina e churrasqueira   \n",
       "3     Apartamento         Iputinga   Imobiliaria                   nenhum   \n",
       "4     Apartamento  Engenho do Meio   Imobiliaria           piscina e copa   \n",
       "...           ...              ...           ...                      ...   \n",
       "4678  Apartamento       Boa Viagem   Imobiliaria  piscina e churrasqueira   \n",
       "4679  Apartamento          Setubal   Imobiliaria            churrasqueira   \n",
       "4680  Apartamento            Torre   Imobiliaria                   nenhum   \n",
       "4681  Apartamento     Casa Amarela   Imobiliaria           piscina e copa   \n",
       "4682  Apartamento         Madalena   Imobiliaria     piscina e playground   \n",
       "\n",
       "      origem  \n",
       "0      teste  \n",
       "1      teste  \n",
       "2      teste  \n",
       "3      teste  \n",
       "4      teste  \n",
       "...      ...  \n",
       "4678  treino  \n",
       "4679  treino  \n",
       "4680  treino  \n",
       "4681  treino  \n",
       "4682  treino  \n",
       "\n",
       "[6683 rows x 5 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hp_df.select_dtypes(include=object)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Encoding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "obj_cols = ['tipo', 'bairro', 'tipo_vendedor', 'diferenciais']\n",
    "\n",
    "def encode_string_col(df, col):\n",
    "    df[col] = df[col].astype('category').cat.codes\n",
    "    \n",
    "for col in obj_cols:\n",
    "    encode_string_col(hp_df, col)\n",
    "    "
   ]
  },
  {
   "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>Id</th>\n",
       "      <th>tipo</th>\n",
       "      <th>bairro</th>\n",
       "      <th>tipo_vendedor</th>\n",
       "      <th>quartos</th>\n",
       "      <th>suites</th>\n",
       "      <th>vagas</th>\n",
       "      <th>area_util</th>\n",
       "      <th>area_extra</th>\n",
       "      <th>diferenciais</th>\n",
       "      <th>...</th>\n",
       "      <th>piscina</th>\n",
       "      <th>playground</th>\n",
       "      <th>quadra</th>\n",
       "      <th>s_festas</th>\n",
       "      <th>s_jogos</th>\n",
       "      <th>s_ginastica</th>\n",
       "      <th>sauna</th>\n",
       "      <th>vista_mar</th>\n",
       "      <th>origem</th>\n",
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       "    </tr>\n",
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       "    <tr>\n",
       "      <th>4678</th>\n",
       "      <td>6678</td>\n",
       "      <td>0</td>\n",
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       "      <td>170</td>\n",
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       "      <td>...</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>1200000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4679</th>\n",
       "      <td>6679</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>82</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>258000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4680</th>\n",
       "      <td>6680</td>\n",
       "      <td>0</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>75</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>252000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4681</th>\n",
       "      <td>6681</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>780000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4682</th>\n",
       "      <td>6682</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>577035.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6683 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Id  tipo  bairro  tipo_vendedor  quartos  suites  vagas  area_util  \\\n",
       "0        0     0      48              0        4       4      3        182   \n",
       "1        1     0      63              0        2       0      1         85   \n",
       "2        2     0      10              0        3       1      2        115   \n",
       "3        3     0      38              0        3       0      1         92   \n",
       "4        4     0      26              0        3       1      1         65   \n",
       "...    ...   ...     ...            ...      ...     ...    ...        ...   \n",
       "4678  6678     0      10              0        4       4      3        170   \n",
       "4679  6679     0      59              0        2       0      1         82   \n",
       "4680  6680     0      65              0        3       1      1         75   \n",
       "4681  6681     0      15              0        3       2      3        136   \n",
       "4682  6682     0      43              0        3       1      2         84   \n",
       "\n",
       "      area_extra  diferenciais  ...  piscina  playground  quadra  s_festas  \\\n",
       "0              0            24  ...        0           1       0         0   \n",
       "1              0            50  ...        0           0       0         0   \n",
       "2             20            54  ...        1           0       0         0   \n",
       "3              0            50  ...        0           0       0         0   \n",
       "4              0            55  ...        1           0       0         0   \n",
       "...          ...           ...  ...      ...         ...     ...       ...   \n",
       "4678           0            54  ...        1           0       0         0   \n",
       "4679           0             9  ...        0           0       0         0   \n",
       "4680           0            50  ...        0           0       0         0   \n",
       "4681           0            55  ...        1           0       0         0   \n",
       "4682           0            60  ...        1           1       0         0   \n",
       "\n",
       "      s_jogos  s_ginastica  sauna  vista_mar  origem      preco  \n",
       "0           0            0      0          0   teste        NaN  \n",
       "1           0            0      0          0   teste        NaN  \n",
       "2           0            0      0          0   teste        NaN  \n",
       "3           0            0      0          0   teste        NaN  \n",
       "4           0            0      0          0   teste        NaN  \n",
       "...       ...          ...    ...        ...     ...        ...  \n",
       "4678        0            0      0          0  treino  1200000.0  \n",
       "4679        0            0      0          0  treino   258000.0  \n",
       "4680        0            0      0          0  treino   252000.0  \n",
       "4681        0            0      0          0  treino   780000.0  \n",
       "4682        0            0      0          0  treino   577035.0  \n",
       "\n",
       "[6683 rows x 22 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hp_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "hp_df.to_csv('data/desafio 2/hp_from_eda.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Id\n",
      "6683\n",
      "[   0    1    2 ... 6680 6681 6682]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tipo\n",
      "4\n",
      "['Apartamento' 'Casa' 'Loft' 'Quitinete']\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bairro\n",
      "69\n",
      "['Pina' 'Tamarineira' 'Boa Viagem' 'Iputinga' 'Engenho do Meio'\n",
      " 'Rosarinho' 'Casa Forte' 'Cordeiro' 'Torre' 'Parnamirim' 'Gracas'\n",
      " 'Poco da Panela' 'Aflitos' 'Espinheiro' 'Madalena' 'Imbiribeira'\n",
      " 'Encruzilhada' 'Caxanga' 'Casa Amarela' 'Prado' 'Jd S Paulo' 'Jaqueira'\n",
      " 'Boa Vista' 'San Martin' 'Campo Grande' 'Sto Amaro' 'Ibura' 'Setubal'\n",
      " 'Varzea' 'Dois Irmaos' 'Derby' 'Ilha do Retiro' 'Apipucos' 'Monteiro'\n",
      " 'Arruda' 'S Jose' 'Bongi' 'Cajueiro' 'Beberibe' 'Torreao'\n",
      " 'Cid Universitaria' 'Agua Fria' 'Santana' 'Ipsep' 'Recife' 'Coelhos'\n",
      " 'Afogados' 'Fundao' 'Guabiraba' 'Hipodromo' 'Sancho' 'Beira Rio'\n",
      " 'Ilha do Leite' 'Piedade' 'Paissandu' 'Tejipio' 'Areias' 'Barro' 'Poco'\n",
      " 'Macaxeira' 'Lagoa do Araca' 'Ponto de Parada' 'Estancia' 'Zumbi'\n",
      " 'Benfica' 'Soledade' 'Centro' 'Sto Antonio' 'Cohab']\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tipo_vendedor\n",
      "2\n",
      "['Imobiliaria' 'Pessoa Fisica']\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quartos\n",
      "10\n",
      "[ 4  2  3  5  1  6 10  9  7  8]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "suites\n",
      "7\n",
      "[4 0 1 2 3 5 6]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vagas\n",
      "17\n",
      "[ 3  1  2  0  4 30  5  6  7  8 10 12 20 18 17 13 15]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "area_util\n",
      "383\n",
      "[ 182   85  115   92   65   62  107   97   50  250  131  151  149   70\n",
      "  125  105   61   68   82  225  123   40   58   54   55   90   86  208\n",
      "  185  215  150  220  170   77  300   67  330  206  203  240   30  600\n",
      "   95   64   75   52  180  140  312  280   88  152  401   87  156   80\n",
      "  324   45   60   72   94   59   69   57  207  374  128  132   47   25\n",
      "  193  270  100  139  205   66  142  201  130   93  117   74   96  147\n",
      "  450  120   53   35  187  161  520   98  800  160  370   81  108  110\n",
      "  153  126  119  113  200  315   83   51  106   79  118  398  174  186\n",
      "  264  135  276  260   71   36  307   48   84  247   44   63  230  164\n",
      "  303  316  127  940 2735  116  144  176   89  103  168  143  145   38\n",
      "  172  550  146  183  335  121  155  278  188   46  241  217  245  189\n",
      "  257  175  181  173  104  129  157   39  255  109  169  236  400  148\n",
      "  360  134  137  138  162   56  223   78  136  420  311   32   73  158\n",
      "  210  320  249  436   99  239  232   91  163  569  298  191   33  124\n",
      "  402  133  213  380  430  229  111  179  122  190   42  114  102  234\n",
      "  235  256   28  202   76  112  385   31  141  154  198  192  407  101\n",
      "  341  246  580  227  204  317  221  900   41  470   37  577  231  196\n",
      "  295  218  375  262  467   24  289  340   34  274  237  353   27   43\n",
      "  224   49  212   16  384  282  177  226  297  584   26  285  248  178\n",
      "  165  275  357  452  242  254  304  389  457  233  291   29  950  284\n",
      "  500  209  310  159  263 1304  265  166  405  480  464 1000  171  199\n",
      "  167  472  322  750  302  343  350  775  197  216  618  321  447  214\n",
      "  243 1855  258   23  495  296  259  238  455  561  388  339  288  682\n",
      "  338  290  273  403  184  337  556  292  650 1580  261  530  308 1019\n",
      "  253  251  429  219  553  354  268  453  931  848  716  323  386  327\n",
      "  244  252  334  283  333  466  406  720  639  529  287  367  490  277\n",
      "  685  410  195  211 2045  807  326  328  266  395  700  680  394  560\n",
      "  365  294   21  281 1705]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "area_extra\n",
      "200\n",
      "[    0    20   200    55    10   119    95    30   130  1050    63    31\n",
      "    14    37   280    34     9    28   139    49    82    25   430   136\n",
      " 12060    87   100    47    22   177    15   750    69    29   220   110\n",
      "    86   614    90   530    11    27   104    36    40     1     7   121\n",
      "    67   151   160    74    80   103     6   193     4    32     5    72\n",
      "    24    23    35    65   250    75   210   105  1210    21   440    12\n",
      "  6022   134    78    42    53   147   337    38   239    16    77    19\n",
      "    26   161   162   146    50   116    46    52    92   441   472   150\n",
      "    33   143   203    18    81   202    17   118  2461    60     2  2810\n",
      "   167   117    39   415    88   545    83    76    13    48   222   152\n",
      "   112   135    43   232    57    99   126    51   231    58   140   144\n",
      "    66   129     8   800    54    73   133    71   252    41   882    84\n",
      "    68    62   500    56   360   125   478  1100   470   370  4173    70\n",
      "   181   145   304    85   185   155    61   320   170   120   225   536\n",
      "  1285   111   213   270   730    44   132   223     3  1308    94    79\n",
      "    45    89   620   248   217    59    98   224   169   321   300   173\n",
      "    64   336   289   107   306   180    91 17450]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "diferenciais\n",
      "91\n",
      "['copa e playground' 'nenhum' 'piscina e churrasqueira' 'piscina e copa'\n",
      " 'piscina e playground' 'playground' 'copa e esquina' 'salao de festas'\n",
      " 'estacionamento visitantes e playground' 'piscina e esquina'\n",
      " 'playground e quadra poliesportiva' 'copa' 'piscina e sala de ginastica'\n",
      " 'piscina e salao de festas' 'campo de futebol e playground'\n",
      " 'piscina e sauna' 'frente para o mar e playground'\n",
      " 'piscina e campo de futebol' 'churrasqueira e sauna'\n",
      " 'playground e salao de festas' 'copa e estacionamento visitantes'\n",
      " 'piscina' 'estacionamento visitantes' 'playground e sala de ginastica'\n",
      " 'churrasqueira e salao de festas' 'frente para o mar e esquina'\n",
      " 'piscina e estacionamento visitantes' 'churrasqueira'\n",
      " 'quadra poliesportiva e salao de festas' 'copa e salao de festas'\n",
      " 'churrasqueira e children care' 'churrasqueira e copa'\n",
      " 'sauna e playground' 'sauna e quadra poliesportiva'\n",
      " 'estacionamento visitantes e salao de jogos'\n",
      " 'salao de festas e salao de jogos' 'frente para o mar e copa'\n",
      " 'sala de ginastica e salao de festas' 'frente para o mar'\n",
      " 'piscina e frente para o mar' 'frente para o mar e salao de festas'\n",
      " 'piscina e quadra poliesportiva' 'hidromassagem e salao de festas'\n",
      " 'estacionamento visitantes e hidromassagem'\n",
      " 'churrasqueira e sala de ginastica' 'churrasqueira e playground'\n",
      " 'frente para o mar e campo de futebol' 'vestiario' 'sauna e esquina'\n",
      " 'salao de jogos' 'estacionamento visitantes e salao de festas'\n",
      " 'churrasqueira e estacionamento visitantes'\n",
      " 'frente para o mar e hidromassagem' 'esquina e estacionamento visitantes'\n",
      " 'churrasqueira e frente para o mar' 'sauna e copa' 'esquina'\n",
      " 'piscina e children care' 'sauna e frente para o mar'\n",
      " 'copa e hidromassagem' 'esquina e playground'\n",
      " 'salao de festas e vestiario' 'esquina e salao de festas'\n",
      " 'churrasqueira e esquina' 'sauna' 'copa e quadra poliesportiva'\n",
      " 'churrasqueira e campo de futebol' 'frente para o mar e children care'\n",
      " 'campo de futebol e sala de ginastica' 'sala de ginastica'\n",
      " 'piscina e hidromassagem' 'esquina e quadra poliesportiva'\n",
      " 'campo de futebol e salao de festas'\n",
      " 'frente para o mar e quadra poliesportiva' 'sauna e salao de festas'\n",
      " 'sauna e campo de futebol' 'campo de futebol e esquina'\n",
      " 'campo de futebol e estacionamento visitantes'\n",
      " 'piscina e quadra de squash' 'esquina e sala de ginastica'\n",
      " 'sala de ginastica e salao de jogos' 'piscina e salao de jogos'\n",
      " 'sauna e sala de ginastica' 'children care' 'copa e sala de ginastica'\n",
      " 'playground e salao de jogos' 'quadra poliesportiva'\n",
      " 'children care e playground'\n",
      " 'estacionamento visitantes e sala de ginastica' 'campo de futebol e copa'\n",
      " 'campo de futebol e quadra poliesportiva']\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "churrasqueira\n",
      "2\n",
      "[0 1]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "estacionamento\n",
      "2\n",
      "[0 1]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "piscina\n",
      "2\n",
      "[0 1]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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YJOl64DngqtR9K7AEGAJeAq4DiIijkm4BdqZ+N0fEqW8Om5lZm9UM/Yi4eoxNl43SN4CVYxxnHbBuXLMzM7OW8idyzcwy4tA3M8uIQ9/MLCMOfTOzjDj0zcwy4tA3M8uIQ9/MLCMOfTOzjDj0zcwy4tA3M8uIQ9/MLCMOfTOzjDj0zcwy4tA3M8uIQ9/MLCMOfTOzjDj0zcwy4tA3M8uIQ9/MLCNNhb6kg5L2SdojaVdqO0/SNklPp59TU7sk3SVpSNJeSRe1ogAzM6tfK870F0XEgojoTeurge0RMRfYntYBrgDmpkc/cG8LxjYzs3Fox+WdpcCGtLwBuLKq/b6o2AFMkTS9DeObmdkYFBGN7yw9CxwDAvhcRAxIejEipqTtAo5FxBRJDwK3RcSjadt24OMRseuUY/ZTeSVAT0/P2zdu3Njw/I4cPc4LP29494bNn3Fu8YMmIyMjTJ48uWPjFy23esE1F23f8PGOjDvn3AkN17xo0aLdVVdfXmViU7OCP4yIYUlvBLZJ+l71xogISeN6VomIAWAAoLe3N0qlUsOTu/v+zazZ12yJ43fwmlLhY55ULpdp5nfWbXKrF1xz0Vas3tKRcdf3TWpLzU1d3omI4fTzCPAAcDHwwsnLNunnkdR9GJhVtfvM1GZmZgVpOPQlTZJ0zsllYDHwBDAILE/dlgOb0/IgcG26i2chcDwiDjc8czMzG7dmrn30AA9ULtszEfhSRPybpJ3AJknXA88BV6X+W4ElwBDwEnBdE2ObmVkDGg79iHgGeNso7T8GLhulPYCVjY5nZmbN8ydyzcwy4tA3M8uIQ9/MLCMOfTOzjDj0zcwy4tA3M8uIQ9/MLCMOfTOzjDj0zcwy4tA3M8uIQ9/MLCMOfTOzjDj0zcwy4tA3M8uIQ9/MLCMOfTOzjDj0zcwy4tA3M8uIQ9/MLCOFh76kPklPSRqStLro8c3MclZo6EuaANwDXAHMA66WNK/IOZiZ5azoM/2LgaGIeCYi/gfYCCwteA5mZtmaWPB4M4Dnq9YPAZdUd5DUD/Sn1RFJTzUx3jTgR03s3xDdXvSIr9KRmjsot3rBNWdh0e1N1fy7Y20oOvRriogBYKAVx5K0KyJ6W3GsbpFbzbnVC645F+2quejLO8PArKr1manNzMwKUHTo7wTmSpoj6UxgGTBY8BzMzLJV6OWdiDgh6QbgIWACsC4i9rdxyJZcJuoyudWcW73gmnPRlpoVEe04rpmZvQb5E7lmZhlx6JuZZaTrQ7/W1zpIOkvSV9L2xyTN7sA0W6qOmj8q6YCkvZK2Sxrznt1uUe/Xd0j6M0khqetv76unZklXpT/r/ZK+VPQcW62Ov9u/I+lhSd9Jf7+XdGKerSJpnaQjkp4YY7sk3ZV+H3slXdT0oBHRtQ8qbwZ/H/g94Ezgu8C8U/r8NfDZtLwM+Eqn511AzYuA30rLH8qh5tTvHOARYAfQ2+l5F/DnPBf4DjA1rb+x0/MuoOYB4ENpeR5wsNPzbrLmPwIuAp4YY/sS4BuAgIXAY82O2e1n+vV8rcNSYENa/ipwmSQVOMdWq1lzRDwcES+l1R1UPg/Rzer9+o5bgNuBXxQ5uTapp+a/BO6JiGMAEXGk4Dm2Wj01B/Dbaflc4L8KnF/LRcQjwNHTdFkK3BcVO4ApkqY3M2a3h/5oX+swY6w+EXECOA68oZDZtUc9NVe7nsqZQjerWXN62TsrIrYUObE2qufP+S3AWyT9h6QdkvoKm1171FPzJ4H3SToEbAX+ppipdcx4/73X9Jr7GgZrHUnvA3qBP+70XNpJ0uuAO4AVHZ5K0SZSucRTovJq7hFJ8yPixU5Oqs2uBtZHxBpJ7wC+KOmCiPjfTk+sW3T7mX49X+vwqz6SJlJ5SfjjQmbXHnV9lYWkPwH+Hnh3RLxc0NzapVbN5wAXAGVJB6lc+xzs8jdz6/lzPgQMRsQvI+JZ4D+pPAl0q3pqvh7YBBAR3wJeT+XL2H5Ttfyra7o99Ov5WodBYHlafi/wzUjvkHSpmjVLuhD4HJXA7/brvFCj5og4HhHTImJ2RMym8j7GuyNiV2em2xL1/N3+Vypn+UiaRuVyzzMFzrHV6qn5B8BlAJL+gEro/3ehsyzWIHBtuotnIXA8Ig43c8CuvrwTY3ytg6SbgV0RMQispfIScIjKGybLOjfj5tVZ8z8Ck4F/Se9Z/yAi3t2xSTepzpp/o9RZ80PAYkkHgFeAj0VE176KrbPmVcDnJf0tlTd1V3TzSZykL1N54p6W3qe4CTgDICI+S+V9iyXAEPAScF3TY3bx78vMzMap2y/vmJnZODj0zcwy4tA3M8uIQ9/MLCMOfTOzjDj0zcwy4tA3M8vI/wF9bNqOYnUaGQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "playground\n",
      "2\n",
      "[1 0]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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IoS9JFRn60J/tax0i4mURcWtZfndEjAxgmD3VoObfj4gHI+L+iNgbETM+szssmn59R0T8ekRkRAz9431Nao6Ii8vf+oGI+EK/x9hrDf5t/2xE3BkR95V/3+sHMc5eiYjtEXEkIr41w/KIiI+X1+P+iDin651m5tD+0L4Z/G3g54FTgW8Cq57T57eAT5fpjcCtgx53H2p+B/AzZfoDNdRc+p0B3AXsA0YHPe4+/J1XAvcBS8r86wY97j7UPA58oEyvAg4Oetxd1vzLwDnAt2ZYvh74eyCA1cDd3e5z2M/0m3ytwwZgR5n+ErAmIqKPY+y1WWvOzDsz8+kyu4/25yGGWdOv77gauBb4UT8Ht0Ca1PybwCcy8xhAZh7p8xh7rUnNCbyyTL8K+Pc+jq/nMvMu4OgLdNkA3JRt+4DFEXFmN/sc9tA/2dc6LJupT2ZOA8eB1/RldAujSc2dNtM+Uxhms9Zc3vauyMyv9nNgC6jJ3/kNwBsi4p8jYl9ErOvb6BZGk5r/DHh/RBwCbgN+pz9DG5i5/n+f1YvuaxjUOxHxfmAU+JVBj2UhRcRLgI8Clw14KP22iPYlnjHa7+buioizM/OpQQ5qgb0P+FxmXhcRbwM+HxFvysz/HfTAhsWwn+k3+VqHZ/tExCLabwmf7MvoFkajr7KIiF8F/gS4MDOf6dPYFspsNZ8BvAmYiIiDtK997h7ym7lN/s6HgN2Z+T+Z+R3g32gfBIZVk5o3AzsBMvNfgJfT/jK2n1Y9/+qaYQ/9Jl/rsBvYVKbfA9yR5Q7JkJq15oh4K/AZ2oE/7Nd5YZaaM/N4Zi7NzJHMHKF9H+PCzNw/mOH2RJN/239H+yyfiFhK+3LPo30cY681qfm7wBqAiPhF2qH/H30dZX/tBi4tT/GsBo5n5hPdbHCoL+/kDF/rEBFXAfszczdwI+23gJO0b5hsHNyIu9ew5r8AXgH8dbln/d3MvHBgg+5Sw5p/qjSs+XZgbUQ8CPwY+IPMHNp3sQ1r3gp8NiJ+j/ZN3cuG+SQuIr5I+8C9tNyn2Aa8FCAzP037vsV6YBJ4Gri8630O8eslSZqjYb+8I0maA0Nfkipi6EtSRQx9SaqIoS9JFTH0Jakihr4kVeT/AAwlfXE+7oarAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quadra\n",
      "2\n",
      "[0 1]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "s_festas\n",
      "2\n",
      "[0 1]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "s_jogos\n",
      "2\n",
      "[0 1]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "s_ginastica\n",
      "2\n",
      "[0 1]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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/yWEGT+F8GnggyXbgReC61v0h4BpgBngNuAmgqo4luR14rPW7rare+OKwJOkMWzD0q+qj82y68jR9C7h5nuPsBnYvanSSpJHyHbmS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdWTNuE+YZAvwWeAs4Der6tPjHoMkDWPjrb+3Yuf+/JZzz8hxx3qnn+Qs4FeBq4GLgY8muXicY5Ckno17eucyYKaqXqiqPwfuB7aOeQyS1K1xT++sB16as34YuHxuhyQ7gB1tdTbJN5ZxvvOBP1vG/kuSO8Z9xtetSL0rzJr70F3NH7xjWTX/tfk2jH1OfyFVtQvYNYpjJXm8qiZHcazVoLd6wZp7Yc2jM+7pnSPAhXPWN7Q2SdIYjDv0HwM2JbkoydnA9cC+MY9Bkro11umdqjqZ5B8CDzN4ZHN3VT1zBk85kmmiVaS3esGae2HNI5KqOhPHlSS9BfmOXEnqiKEvSR1Z9aGfZEuSbySZSXLraba/I8kX2/ZHk2xcgWGO1BA1/5MkzyZ5KsmBJPM+s7taLFTznH4/l6SSrPrH+4apOcl17Xf9TJLfGvcYR22If9t/NckjSZ5s/76vWYlxjkqS3UmOJvn6PNuT5K7283gqyaXLPmlVrdovBi8G/zHw14GzgT8ELn5Dn38A/Hpbvh744kqPeww1fxD4K235l3qoufV7F/AV4CAwudLjHsPveRPwJLCurf/oSo97DDXvAn6pLV8MHFrpcS+z5p8BLgW+Ps/2a4D/DAS4Anh0uedc7Xf6w3ysw1ZgT1t+ELgyScY4xlFbsOaqeqSqXmurBxm8H2I1G/bjO24H7gC+O87BnSHD1Pz3gV+tquMAVXV0zGMctWFqLuCH2/K7gf85xvGNXFV9BTj2Jl22AvfWwEFgbZILlnPO1R76p/tYh/Xz9amqk8AJ4D1jGd2ZMUzNc21ncKewmi1Yc/uz98KqWrmPRRytYX7PPw78eJL/muRg+wTb1WyYmv8V8AtJDgMPAR8fz9BWzGL/e1/QW+5jGDQ6SX4BmAT+9kqP5UxK8jbgV4CPrfBQxm0NgymeKQZ/zX0lySVV9epKDuoM+yjw+aq6M8kHgC8k+amq+r8rPbDVYrXf6Q/zsQ6v90myhsGfhN8ey+jOjKE+yiLJ3wH+JfDhqvremMZ2pixU87uAnwKmkxxiMPe5b5W/mDvM7/kwsK+q/k9VfRP4HwwuAqvVMDVvBx4AqKr/BryTwYex/WU18o+uWe2hP8zHOuwDtrXljwBfrvYKySq1YM1J3g/8OwaBv9rneWGBmqvqRFWdX1Ubq2ojg9cxPlxVj6/McEdimH/bv8PgLp8k5zOY7nlhjGMctWFq/hPgSoAkf5NB6P/pWEc5XvuAG9tTPFcAJ6rq5eUccFVP79Q8H+uQ5Dbg8araB9zD4E/AGQYvmFy/ciNeviFr/jfADwH/ob1m/SdV9eEVG/QyDVnzXypD1vwwsDnJs8D3gX9aVav2r9gha74F+I0k/5jBi7ofW803cUl+m8GF+/z2OsVO4O0AVfXrDF63uAaYAV4Dblr2OVfxz0uStEirfXpHkrQIhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqyP8DQ006uSdgpTkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sauna\n",
      "2\n",
      "[0 1]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vista_mar\n",
      "2\n",
      "[0 1]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "origem\n",
      "2\n",
      "['teste' 'treino']\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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nuN/bgV9Nsqr9XyUXAf8820ZHzZ1+VX03yefaDzf+Cfg74PPtEc0k8NvAKcC7k/wP8N/AG9rmW4FPJflGVb0iycXAR9ozNJh6xn/oP6ckadEOadd/At8aWPxBYC3wxUzF7NvA+XPc76Ptfx+8lal/Meysqu2zbXfUvLIpSVq8o+nxjiRpkYy+JHXE6EtSR4y+JHXE6EtSR4y+JHXE6EtSR/4XqvaNDTObq0MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "preco\n",
      "679\n",
      "[          nan 1.0000000e+06 6.8000000e+05 4.5000000e+05 1.0800000e+06\n",
      " 3.5000000e+05 4.9000000e+05 3.9000000e+05 1.3500000e+06 4.0000000e+05\n",
      " 9.8000000e+05 1.2000000e+06 2.1500000e+05 7.5000000e+05 5.8000000e+05\n",
      " 1.5000000e+06 3.0000000e+05 4.2000000e+05 5.6000000e+05 4.8900000e+05\n",
      " 1.3000000e+06 3.8000000e+05 6.9000000e+05 7.0000000e+05 2.2000000e+06\n",
      " 3.7000000e+05 5.7900000e+05 2.6500000e+05 4.7000000e+05 9.0000000e+05\n",
      " 8.1400000e+05 2.9850000e+05 1.1000000e+06 6.3500000e+05 1.6000000e+05\n",
      " 4.8000000e+05 9.5000000e+05 4.4000000e+05 7.9000000e+05 8.6000000e+05\n",
      " 4.6000000e+05 1.6900000e+05 1.6000000e+06 3.3000000e+05 5.3000000e+05\n",
      " 4.3500000e+05 3.2000000e+05 1.7500000e+06 2.2000000e+05 2.0000000e+05\n",
      " 3.1400000e+05 6.0700000e+05 2.2500000e+05 3.9500000e+05 1.4000000e+06\n",
      " 5.5000000e+05 2.7000000e+05 1.0036800e+06 8.2000000e+05 1.7500000e+05\n",
      " 5.2000000e+05 3.5000000e+06 2.4000000e+05 6.2000000e+05 8.5000000e+05\n",
      " 2.4900000e+05 4.7400000e+05 3.0500000e+05 4.3000000e+05 6.5000000e+05\n",
      " 7.8000000e+05 1.0650000e+06 1.2500000e+06 4.5600000e+05 4.0900000e+05\n",
      " 3.6000000e+05 9.5900000e+05 2.7500000e+06 2.2500000e+06 1.3075500e+06\n",
      " 3.1700000e+05 1.1500000e+06 1.4900000e+06 3.4000000e+05 1.6577850e+06\n",
      " 3.2500000e+05 6.3000000e+05 2.9500000e+05 4.2500000e+05 8.7000000e+05\n",
      " 3.8800800e+05 2.8753500e+05 1.2900000e+06 4.3410000e+05 2.3500000e+06\n",
      " 2.8000000e+05 8.9000000e+05 6.6500000e+05 3.3500000e+05 3.7900000e+06\n",
      " 1.8000000e+05 2.8500000e+05 4.5500000e+05 1.7000000e+05 3.1000000e+05\n",
      " 8.4000000e+05 7.2000000e+05 2.6850000e+05 6.0000000e+05 7.4000000e+05\n",
      " 5.9900000e+05 2.1000000e+06 3.7300000e+05 5.2500000e+05 2.1700000e+05\n",
      " 5.9000000e+05 5.9840000e+05 4.1000000e+05 8.0000000e+05 1.6200000e+06\n",
      " 3.9900000e+05 2.5000000e+06 5.7000000e+05 6.7000000e+05 2.7000000e+06\n",
      " 3.4800000e+05 2.6000000e+05 3.9800000e+05 5.4000000e+05 2.9000000e+05\n",
      " 1.6500000e+05 7.6100000e+05 1.9000000e+06 7.3500000e+05 2.8900000e+05\n",
      " 5.4500000e+05 1.5980000e+06 4.9600000e+05 4.9900000e+05 8.8000000e+05\n",
      " 1.1400000e+06 4.3800000e+05 5.3500000e+05 2.3000000e+05 5.0000000e+05\n",
      " 2.5000000e+05 4.7290000e+05 5.1000000e+05 2.1000000e+05 9.1500000e+05\n",
      " 7.9700000e+05 5.5000000e+06 4.9500000e+05 3.8500000e+05 1.1180000e+06\n",
      " 2.6100000e+05 1.4500000e+06 7.1000000e+05 6.4000000e+05 2.9100000e+05\n",
      " 3.7568200e+05 1.7000000e+06 2.7500000e+05 2.5980000e+05 7.6700000e+05\n",
      " 3.1900000e+05 6.3000000e+08 1.2899240e+06 1.0500000e+06 4.7500000e+05\n",
      " 1.6500000e+06 3.0093000e+05 1.3490000e+06 2.4000000e+06 4.6200000e+05\n",
      " 5.5396600e+05 2.0500000e+05 3.8000000e+06 4.5147300e+05 3.1500000e+05\n",
      " 2.9700000e+05 8.3000000e+05 1.8000000e+06 6.9600000e+05 2.9600000e+05\n",
      " 1.5500000e+05 4.8800000e+05 5.4000000e+06 2.5500000e+05 4.0600000e+05\n",
      " 1.5570000e+06 6.1000000e+05 4.5360000e+05 9.8655700e+05 1.7300000e+06\n",
      " 1.1100000e+06 1.8900000e+05 2.0000000e+06 1.3210000e+06 4.5990000e+05\n",
      " 5.8900000e+05 2.2658000e+05 5.6700000e+05 1.2780000e+06 4.1000000e+06\n",
      " 1.2390000e+06 4.7900000e+05 5.7500000e+05 2.5900000e+05 1.2000000e+05\n",
      " 4.0500000e+05 3.2400000e+05 5.9500000e+05 2.2300000e+05 2.1500000e+06\n",
      " 3.8600000e+05 2.3500000e+05 5.1900000e+05 1.3900000e+06 2.6800000e+05\n",
      " 2.9900000e+05 3.3600000e+05 7.2200000e+05 8.9400000e+05 3.2000000e+06\n",
      " 7.7000000e+05 7.5040000e+05 2.6900000e+05 1.8500000e+05 5.4630000e+05\n",
      " 1.0300000e+06 7.3000000e+05 1.9600000e+05 1.9400000e+06 5.5307900e+05\n",
      " 2.6800000e+06 5.0419300e+05 2.6500000e+06 6.0697600e+05 6.4500000e+05\n",
      " 3.5800000e+05 5.8000000e+06 3.3765700e+05 1.5500000e+06 3.8691000e+05\n",
      " 6.5000000e+06 7.7500000e+05 7.2500000e+05 4.4500000e+05 2.4500000e+06\n",
      " 3.5700000e+05 1.8500000e+06 3.3168500e+05 3.1344900e+05 3.4828500e+05\n",
      " 4.5200000e+05 5.0500000e+05 4.9700000e+05 3.7500000e+05 3.5400000e+05\n",
      " 7.4500000e+05 4.5700000e+05 3.6500000e+05 1.5416800e+06 1.9500000e+06\n",
      " 1.3000000e+05 4.1600000e+05 9.7000000e+05 6.0316600e+05 5.5800000e+05\n",
      " 1.4000000e+05 4.6572200e+05 4.7000000e+06 3.8100000e+05 7.6500000e+05\n",
      " 4.5000000e+06 3.4500000e+05 3.5300000e+05 5.2900000e+05 3.5650000e+05\n",
      " 3.3924200e+05 1.4300000e+06 7.4550000e+05 9.9000000e+05 2.6000000e+06\n",
      " 9.5500000e+05 4.5800000e+05 3.5400000e+06 1.9000000e+05 5.2100000e+05\n",
      " 6.3100000e+05 1.0720000e+06 5.8500000e+05 3.8200000e+05 4.6500000e+05\n",
      " 1.9900000e+05 4.3400000e+05 8.4500000e+05 7.7480000e+05 4.0550000e+05\n",
      " 4.4800000e+05 3.9700000e+05 1.2950000e+06 3.9279000e+05 9.4000000e+05\n",
      " 3.1345800e+05 1.6800000e+05 4.9400000e+05 3.3100000e+05 9.4500000e+05\n",
      " 4.0051500e+05 4.7800000e+05 9.7500000e+05 1.1440000e+06 6.9980000e+05\n",
      " 3.8300000e+05 5.9100000e+05 7.0620000e+05 9.3000000e+05 4.1700000e+05\n",
      " 9.5600000e+05 3.5500000e+05 2.9500000e+06 3.4290000e+05 6.1800000e+05\n",
      " 4.5423100e+05 4.8500000e+05 3.4500000e+06 1.1200000e+06 5.0144900e+05\n",
      " 3.0000000e+06 4.0910000e+05 2.3000000e+06 4.7200000e+05 4.3900000e+05\n",
      " 1.9500000e+05 8.6500000e+05 3.2840000e+05 2.5420000e+05 6.9500000e+05\n",
      " 3.6400000e+05 3.4900000e+05 5.1200000e+05 3.5200000e+05 5.6200000e+05\n",
      " 1.4650000e+06 3.7900000e+05 4.0800000e+05 4.0000000e+06 1.5800000e+05\n",
      " 1.2100000e+06 2.7300000e+05 4.8720000e+05 6.2200000e+05 1.2206300e+06\n",
      " 6.0901700e+05 4.6041000e+05 2.8103600e+05 7.9500000e+05 9.1800000e+05\n",
      " 4.4000000e+06 3.9279300e+05 2.5079100e+05 6.0690000e+05 8.1000000e+05\n",
      " 7.0600000e+05 3.0200000e+05 1.5000000e+05 5.0000000e+06 3.5350000e+05\n",
      " 3.7100000e+05 3.8400000e+05 2.3400000e+05 7.6000000e+05 3.1000000e+06\n",
      " 5.5141900e+05 5.5400000e+05 3.6435000e+05 2.9999000e+05 4.1500000e+05\n",
      " 7.2760000e+05 4.1155800e+05 7.9157400e+05 1.0000000e+05 4.5771300e+05\n",
      " 8.9500000e+05 3.5697900e+05 3.3919000e+05 6.6000000e+05 3.8284200e+05\n",
      " 6.0300000e+05 4.9256200e+05 4.8700000e+05 6.5500000e+05 2.3250000e+05\n",
      " 7.0500000e+05 3.1200000e+05 1.2899250e+06 3.8614600e+05 4.6080000e+05\n",
      " 4.1200000e+05 6.8900000e+05 7.1000000e+06 1.1900000e+06 1.0890000e+06\n",
      " 3.0380000e+05 5.9800000e+05 4.3539500e+05 2.9000000e+06 6.0289700e+05\n",
      " 2.3550000e+05 4.4100000e+05 2.4500000e+05 5.7800000e+05 2.9672100e+05\n",
      " 2.7900000e+05 1.9300000e+05 5.6500000e+05 3.7360000e+05 3.3800000e+05\n",
      " 3.0870000e+05 2.6640000e+05 4.4038800e+05 2.1480000e+06 3.7140000e+06\n",
      " 4.1750000e+05 4.5147400e+05 1.2800000e+06 5.5200000e+05 2.0600000e+05\n",
      " 1.3300000e+06 3.8520000e+05 2.6700000e+05 3.8614700e+05 3.3281510e+06\n",
      " 2.4600000e+05 3.2600000e+05 2.0900000e+05 5.7303200e+05 8.0665000e+05\n",
      " 6.4754400e+05 1.2500000e+05 2.9999900e+05 1.1450000e+06 3.7700000e+05\n",
      " 5.5900000e+05 2.0700000e+05 7.7600000e+05 9.0500000e+05 2.8400000e+05\n",
      " 7.4800000e+05 3.5615000e+05 8.8600000e+05 8.3600000e+05 2.9547500e+05\n",
      " 5.7400000e+05 2.8000000e+06 3.0600000e+05 6.9900000e+05 2.8700000e+05\n",
      " 2.6165400e+05 2.4294000e+05 2.7200000e+05 3.7127400e+05 2.5500000e+06\n",
      " 1.9900000e+06 5.1500000e+05 9.8500000e+05 1.1800000e+06 2.8499900e+05\n",
      " 5.9180100e+05 4.3300000e+05 3.3270000e+06 2.5550000e+05 6.1441900e+05\n",
      " 4.3794000e+05 5.3040000e+05 6.9800000e+05 4.9800000e+05 2.5248000e+05\n",
      " 3.0453700e+05 6.1500000e+05 4.1800000e+05 4.9301300e+05 6.1600000e+05\n",
      " 3.3700000e+05 8.1600000e+05 3.6670000e+05 1.2600000e+06 2.8999900e+05\n",
      " 2.2300000e+06 6.8500000e+05 1.7300000e+05 3.5250000e+05 1.1906580e+06\n",
      " 6.5000000e+07 3.6900000e+05 2.7100000e+05 4.5272700e+05 8.6783300e+05\n",
      " 1.4800000e+06 1.3150000e+06 3.6000000e+06 1.4950000e+06 9.1200000e+05\n",
      " 8.3100000e+05 3.1960400e+05 3.5500000e+06 2.9950000e+06 8.4900000e+05\n",
      " 2.7400000e+05 4.2027000e+05 1.1410000e+06 1.4400000e+06 5.6420000e+05\n",
      " 3.5097700e+05 9.8465700e+05 3.7415000e+05 2.0977360e+06 1.6264500e+05\n",
      " 1.7700000e+05 2.5220000e+05 6.4437900e+05 3.2800000e+05 5.4600000e+05\n",
      " 3.6878213e+05 5.4700000e+05 1.2280000e+06 3.7400000e+05 1.1700000e+06\n",
      " 9.2000000e+05 1.1490000e+06 9.4900000e+05 1.8490000e+06 3.4000000e+06\n",
      " 2.4900000e+06 5.0700000e+05 7.3521600e+05 2.5250000e+05 3.7800000e+05\n",
      " 3.5220000e+06 3.6602500e+05 1.3800000e+06 7.9800000e+05 6.2350000e+05\n",
      " 2.9245000e+05 5.8200000e+05 5.4900000e+05 4.1423300e+05 2.7800000e+05\n",
      " 3.6700000e+05 3.8158800e+05 1.6900000e+06 3.2990000e+05 9.0000000e+04\n",
      " 7.1500000e+05 7.0590000e+05 2.7645000e+06 1.1799000e+06 2.0977350e+06\n",
      " 4.1900000e+05 7.6200000e+05 5.4522700e+05 1.2750000e+06 4.3402900e+05\n",
      " 4.3977000e+05 6.1900000e+05 6.2034000e+05 1.2700000e+06 3.2300000e+05\n",
      " 8.6300000e+05 9.4800000e+05 4.7100000e+05 6.4999900e+05 6.8999900e+05\n",
      " 1.1698000e+06 1.5900000e+06 2.9391000e+05 2.4750000e+05 9.7990000e+05\n",
      " 2.1900000e+05 7.4999000e+05 4.2200000e+05 9.1990000e+05 8.7573500e+05\n",
      " 6.0000000e+06 3.6030000e+05 5.2700000e+05 2.4100000e+05 1.3700000e+06\n",
      " 1.2990000e+06 3.2900000e+05 1.4500000e+05 1.1390000e+06 4.3112400e+05\n",
      " 1.2249250e+06 1.1300000e+06 4.9037000e+05 1.5600000e+06 1.0200000e+06\n",
      " 3.0900000e+05 5.2600000e+05 8.2200000e+05 1.2150000e+06 2.6200000e+05\n",
      " 6.1900000e+06 1.4700000e+05 8.3500000e+05 7.8700000e+05 5.1800000e+05\n",
      " 6.4942700e+05 7.5000000e+02 3.0800000e+05 2.5600000e+05 5.4400000e+05\n",
      " 3.3400000e+05 2.4800000e+06 2.1990000e+05 1.0930000e+06 4.6740000e+05\n",
      " 1.3600000e+06 7.7800000e+05 1.2088240e+06 5.4671300e+05 3.4000000e+08\n",
      " 6.9450000e+05 4.6623300e+05 4.9888800e+05 6.2500000e+05 6.7500000e+05\n",
      " 9.2100000e+05 1.9700000e+05 4.6107800e+05 1.9684000e+05 7.2300000e+05\n",
      " 1.0900000e+06 3.1560000e+05 5.5300000e+05 1.2250000e+06 9.1873600e+05\n",
      " 4.2162200e+05 5.4441600e+05 3.9300000e+05 6.0500000e+05 9.6500000e+05\n",
      " 1.7110000e+06 4.0700000e+05 9.8000000e+04 4.6600000e+05 3.4389300e+05\n",
      " 8.2077700e+05 1.5400000e+05 6.7600000e+05 7.9900000e+05 3.3000000e+06\n",
      " 3.2190000e+06 1.4200000e+06 3.4550000e+05 4.0300000e+05 1.5400000e+06\n",
      " 2.7150000e+05 3.4510000e+06 3.6783000e+05 4.3200000e+05 3.2860000e+05\n",
      " 1.8900000e+06 1.0550000e+06 7.9600000e+05 4.4700000e+05 8.8500000e+05\n",
      " 1.2240000e+06 2.0900000e+06 8.6800000e+05 8.1910700e+05 3.4876900e+05\n",
      " 9.3100000e+05 3.8800000e+05 2.5800000e+05 2.5200000e+05 5.7703500e+05]\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for col in hp_df.columns.tolist():\n",
    "    print(col)\n",
    "    print(hp_df[col].nunique())\n",
    "    print(hp_df[col].unique())\n",
    "    print('\\n')\n",
    "    hp_df[col].hist()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>tipo</th>\n",
       "      <th>bairro</th>\n",
       "      <th>tipo_vendedor</th>\n",
       "      <th>quartos</th>\n",
       "      <th>suites</th>\n",
       "      <th>vagas</th>\n",
       "      <th>area_util</th>\n",
       "      <th>area_extra</th>\n",
       "      <th>diferenciais</th>\n",
       "      <th>...</th>\n",
       "      <th>piscina</th>\n",
       "      <th>playground</th>\n",
       "      <th>quadra</th>\n",
       "      <th>s_festas</th>\n",
       "      <th>s_jogos</th>\n",
       "      <th>s_ginastica</th>\n",
       "      <th>sauna</th>\n",
       "      <th>vista_mar</th>\n",
       "      <th>origem</th>\n",
       "      <th>preco</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2000</td>\n",
       "      <td>Casa</td>\n",
       "      <td>Imbiribeira</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>223</td>\n",
       "      <td>167</td>\n",
       "      <td>piscina e copa</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2001</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Casa Amarela</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>157</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>680000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2002</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Encruzilhada</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>450000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2003</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Boa Viagem</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>149</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>1080000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2004</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Rosarinho</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>350000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4678</th>\n",
       "      <td>6678</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Boa Viagem</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>170</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>1200000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4679</th>\n",
       "      <td>6679</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Setubal</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>82</td>\n",
       "      <td>0</td>\n",
       "      <td>churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>258000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4680</th>\n",
       "      <td>6680</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Torre</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>75</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>252000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4681</th>\n",
       "      <td>6681</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Casa Amarela</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e copa</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>780000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4682</th>\n",
       "      <td>6682</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Madalena</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e playground</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>577035.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4683 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Id         tipo        bairro tipo_vendedor  quartos  suites  vagas  \\\n",
       "0     2000         Casa   Imbiribeira   Imobiliaria        3       3      5   \n",
       "1     2001  Apartamento  Casa Amarela   Imobiliaria        4       4      2   \n",
       "2     2002  Apartamento  Encruzilhada   Imobiliaria        3       1      0   \n",
       "3     2003  Apartamento    Boa Viagem   Imobiliaria        4       3      2   \n",
       "4     2004  Apartamento     Rosarinho   Imobiliaria        2       1      1   \n",
       "...    ...          ...           ...           ...      ...     ...    ...   \n",
       "4678  6678  Apartamento    Boa Viagem   Imobiliaria        4       4      3   \n",
       "4679  6679  Apartamento       Setubal   Imobiliaria        2       0      1   \n",
       "4680  6680  Apartamento         Torre   Imobiliaria        3       1      1   \n",
       "4681  6681  Apartamento  Casa Amarela   Imobiliaria        3       2      3   \n",
       "4682  6682  Apartamento      Madalena   Imobiliaria        3       1      2   \n",
       "\n",
       "      area_util  area_extra             diferenciais  ...  piscina  \\\n",
       "0           223         167           piscina e copa  ...        1   \n",
       "1           157           0  piscina e churrasqueira  ...        1   \n",
       "2            53           0                   nenhum  ...        0   \n",
       "3           149           0  piscina e churrasqueira  ...        1   \n",
       "4            54           0  piscina e churrasqueira  ...        1   \n",
       "...         ...         ...                      ...  ...      ...   \n",
       "4678        170           0  piscina e churrasqueira  ...        1   \n",
       "4679         82           0            churrasqueira  ...        0   \n",
       "4680         75           0                   nenhum  ...        0   \n",
       "4681        136           0           piscina e copa  ...        1   \n",
       "4682         84           0     piscina e playground  ...        1   \n",
       "\n",
       "      playground  quadra  s_festas  s_jogos  s_ginastica  sauna  vista_mar  \\\n",
       "0              0       0         0        0            0      0          0   \n",
       "1              0       0         0        0            0      0          0   \n",
       "2              0       0         0        0            0      0          0   \n",
       "3              0       0         0        0            0      0          0   \n",
       "4              0       0         0        0            0      0          0   \n",
       "...          ...     ...       ...      ...          ...    ...        ...   \n",
       "4678           0       0         0        0            0      0          0   \n",
       "4679           0       0         0        0            0      0          0   \n",
       "4680           0       0         0        0            0      0          0   \n",
       "4681           0       0         0        0            0      0          0   \n",
       "4682           1       0         0        0            0      0          0   \n",
       "\n",
       "      origem      preco  \n",
       "0     treino  1000000.0  \n",
       "1     treino   680000.0  \n",
       "2     treino   450000.0  \n",
       "3     treino  1080000.0  \n",
       "4     treino   350000.0  \n",
       "...      ...        ...  \n",
       "4678  treino  1200000.0  \n",
       "4679  treino   258000.0  \n",
       "4680  treino   252000.0  \n",
       "4681  treino   780000.0  \n",
       "4682  treino   577035.0  \n",
       "\n",
       "[4683 rows x 22 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test = hp_df[hp_df['preco'].notnull()]\n",
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    4.683000e+03\n",
       "mean     9.277053e+05\n",
       "std      1.050607e+07\n",
       "min      7.500000e+02\n",
       "25%      3.550000e+05\n",
       "50%      5.150000e+05\n",
       "75%      8.300000e+05\n",
       "max      6.300000e+08\n",
       "Name: preco, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test['preco'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_analysis = test[test['preco'] < 1.300000e+06]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4162, 22)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_analysis.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_analysis['preco'].hist()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      2879.000000\n",
       "mean     393239.563088\n",
       "std      115459.109831\n",
       "min         750.000000\n",
       "25%      310000.000000\n",
       "50%      380000.000000\n",
       "75%      480000.000000\n",
       "max      625000.000000\n",
       "Name: preco, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_analysis['preco'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test['preco'].hist()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>tipo</th>\n",
       "      <th>bairro</th>\n",
       "      <th>tipo_vendedor</th>\n",
       "      <th>quartos</th>\n",
       "      <th>suites</th>\n",
       "      <th>vagas</th>\n",
       "      <th>area_util</th>\n",
       "      <th>area_extra</th>\n",
       "      <th>diferenciais</th>\n",
       "      <th>...</th>\n",
       "      <th>piscina</th>\n",
       "      <th>playground</th>\n",
       "      <th>quadra</th>\n",
       "      <th>s_festas</th>\n",
       "      <th>s_jogos</th>\n",
       "      <th>s_ginastica</th>\n",
       "      <th>sauna</th>\n",
       "      <th>vista_mar</th>\n",
       "      <th>origem</th>\n",
       "      <th>preco</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Pina</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>182</td>\n",
       "      <td>0</td>\n",
       "      <td>copa e playground</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Tamarineira</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Boa Viagem</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>115</td>\n",
       "      <td>20</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Iputinga</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>92</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Engenho do Meio</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e copa</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>1995</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Poco da Panela</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>1996</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Madalena</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>1997</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Boa Viagem</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e salao de festas</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>1998</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Torre</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>112</td>\n",
       "      <td>2810</td>\n",
       "      <td>piscina e frente para o mar</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>1999</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Encruzilhada</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>playground e sala de ginastica</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Id         tipo           bairro tipo_vendedor  quartos  suites  \\\n",
       "0        0  Apartamento             Pina   Imobiliaria        4       4   \n",
       "1        1  Apartamento      Tamarineira   Imobiliaria        2       0   \n",
       "2        2  Apartamento       Boa Viagem   Imobiliaria        3       1   \n",
       "3        3  Apartamento         Iputinga   Imobiliaria        3       0   \n",
       "4        4  Apartamento  Engenho do Meio   Imobiliaria        3       1   \n",
       "...    ...          ...              ...           ...      ...     ...   \n",
       "1995  1995  Apartamento   Poco da Panela   Imobiliaria        2       1   \n",
       "1996  1996  Apartamento         Madalena   Imobiliaria        3       1   \n",
       "1997  1997  Apartamento       Boa Viagem   Imobiliaria        3       1   \n",
       "1998  1998  Apartamento            Torre   Imobiliaria        4       3   \n",
       "1999  1999  Apartamento     Encruzilhada   Imobiliaria        2       1   \n",
       "\n",
       "      vagas  area_util  area_extra                    diferenciais  ...  \\\n",
       "0         3        182           0               copa e playground  ...   \n",
       "1         1         85           0                          nenhum  ...   \n",
       "2         2        115          20         piscina e churrasqueira  ...   \n",
       "3         1         92           0                          nenhum  ...   \n",
       "4         1         65           0                  piscina e copa  ...   \n",
       "...     ...        ...         ...                             ...  ...   \n",
       "1995      2        100           0                          nenhum  ...   \n",
       "1996      1         90           0                          nenhum  ...   \n",
       "1997      1         73           0       piscina e salao de festas  ...   \n",
       "1998      2        112        2810     piscina e frente para o mar  ...   \n",
       "1999      1         51           0  playground e sala de ginastica  ...   \n",
       "\n",
       "      piscina  playground  quadra  s_festas  s_jogos  s_ginastica  sauna  \\\n",
       "0           0           1       0         0        0            0      0   \n",
       "1           0           0       0         0        0            0      0   \n",
       "2           1           0       0         0        0            0      0   \n",
       "3           0           0       0         0        0            0      0   \n",
       "4           1           0       0         0        0            0      0   \n",
       "...       ...         ...     ...       ...      ...          ...    ...   \n",
       "1995        0           0       0         0        0            0      0   \n",
       "1996        0           0       0         0        0            0      0   \n",
       "1997        1           0       0         1        0            0      0   \n",
       "1998        1           0       0         0        0            0      0   \n",
       "1999        0           1       0         0        0            1      0   \n",
       "\n",
       "      vista_mar  origem  preco  \n",
       "0             0   teste    NaN  \n",
       "1             0   teste    NaN  \n",
       "2             0   teste    NaN  \n",
       "3             0   teste    NaN  \n",
       "4             0   teste    NaN  \n",
       "...         ...     ...    ...  \n",
       "1995          0   teste    NaN  \n",
       "1996          0   teste    NaN  \n",
       "1997          0   teste    NaN  \n",
       "1998          1   teste    NaN  \n",
       "1999          0   teste    NaN  \n",
       "\n",
       "[2000 rows x 22 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train = hp_df[hp_df['preco'].isna()]\n",
    "train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>tipo</th>\n",
       "      <th>bairro</th>\n",
       "      <th>tipo_vendedor</th>\n",
       "      <th>quartos</th>\n",
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       "      <th>quadra</th>\n",
       "      <th>s_festas</th>\n",
       "      <th>s_jogos</th>\n",
       "      <th>s_ginastica</th>\n",
       "      <th>sauna</th>\n",
       "      <th>vista_mar</th>\n",
       "      <th>origem</th>\n",
       "      <th>preco</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2000</td>\n",
       "      <td>Casa</td>\n",
       "      <td>Imbiribeira</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>223</td>\n",
       "      <td>167</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2001</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Casa Amarela</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>157</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>680000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2002</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Encruzilhada</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>450000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2003</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Boa Viagem</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>149</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>1080000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2004</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Rosarinho</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e churrasqueira</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>350000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>1995</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Poco da Panela</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>1996</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Madalena</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>nenhum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>1997</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Boa Viagem</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>piscina e salao de festas</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>1998</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Torre</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>112</td>\n",
       "      <td>2810</td>\n",
       "      <td>piscina e frente para o mar</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>1999</td>\n",
       "      <td>Apartamento</td>\n",
       "      <td>Encruzilhada</td>\n",
       "      <td>Imobiliaria</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>playground e sala de ginastica</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6162 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Id         tipo          bairro tipo_vendedor  quartos  suites  vagas  \\\n",
       "0     2000         Casa     Imbiribeira   Imobiliaria        3       3      5   \n",
       "1     2001  Apartamento    Casa Amarela   Imobiliaria        4       4      2   \n",
       "2     2002  Apartamento    Encruzilhada   Imobiliaria        3       1      0   \n",
       "3     2003  Apartamento      Boa Viagem   Imobiliaria        4       3      2   \n",
       "4     2004  Apartamento       Rosarinho   Imobiliaria        2       1      1   \n",
       "...    ...          ...             ...           ...      ...     ...    ...   \n",
       "1995  1995  Apartamento  Poco da Panela   Imobiliaria        2       1      2   \n",
       "1996  1996  Apartamento        Madalena   Imobiliaria        3       1      1   \n",
       "1997  1997  Apartamento      Boa Viagem   Imobiliaria        3       1      1   \n",
       "1998  1998  Apartamento           Torre   Imobiliaria        4       3      2   \n",
       "1999  1999  Apartamento    Encruzilhada   Imobiliaria        2       1      1   \n",
       "\n",
       "      area_util  area_extra                    diferenciais  ...  piscina  \\\n",
       "0           223         167                  piscina e copa  ...        1   \n",
       "1           157           0         piscina e churrasqueira  ...        1   \n",
       "2            53           0                          nenhum  ...        0   \n",
       "3           149           0         piscina e churrasqueira  ...        1   \n",
       "4            54           0         piscina e churrasqueira  ...        1   \n",
       "...         ...         ...                             ...  ...      ...   \n",
       "1995        100           0                          nenhum  ...        0   \n",
       "1996         90           0                          nenhum  ...        0   \n",
       "1997         73           0       piscina e salao de festas  ...        1   \n",
       "1998        112        2810     piscina e frente para o mar  ...        1   \n",
       "1999         51           0  playground e sala de ginastica  ...        0   \n",
       "\n",
       "      playground  quadra  s_festas  s_jogos  s_ginastica  sauna  vista_mar  \\\n",
       "0              0       0         0        0            0      0          0   \n",
       "1              0       0         0        0            0      0          0   \n",
       "2              0       0         0        0            0      0          0   \n",
       "3              0       0         0        0            0      0          0   \n",
       "4              0       0         0        0            0      0          0   \n",
       "...          ...     ...       ...      ...          ...    ...        ...   \n",
       "1995           0       0         0        0            0      0          0   \n",
       "1996           0       0         0        0            0      0          0   \n",
       "1997           0       0         1        0            0      0          0   \n",
       "1998           0       0         0        0            0      0          1   \n",
       "1999           1       0         0        0            1      0          0   \n",
       "\n",
       "      origem      preco  \n",
       "0     treino  1000000.0  \n",
       "1     treino   680000.0  \n",
       "2     treino   450000.0  \n",
       "3     treino  1080000.0  \n",
       "4     treino   350000.0  \n",
       "...      ...        ...  \n",
       "1995   teste        NaN  \n",
       "1996   teste        NaN  \n",
       "1997   teste        NaN  \n",
       "1998   teste        NaN  \n",
       "1999   teste        NaN  \n",
       "\n",
       "[6162 rows x 22 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "outliers = pd.concat([test_analysis, train])\n",
    "outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "obj_cols = ['tipo', 'bairro', 'tipo_vendedor', 'diferenciais']\n",
    "\n",
    "def encode_string_col(df, col):\n",
    "    df[col] = df[col].astype('category').cat.codes\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "for col in obj_cols:\n",
    "    encode_string_col(outliers, col)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>tipo</th>\n",
       "      <th>bairro</th>\n",
       "      <th>tipo_vendedor</th>\n",
       "      <th>quartos</th>\n",
       "      <th>suites</th>\n",
       "      <th>vagas</th>\n",
       "      <th>area_util</th>\n",
       "      <th>area_extra</th>\n",
       "      <th>diferenciais</th>\n",
       "      <th>...</th>\n",
       "      <th>piscina</th>\n",
       "      <th>playground</th>\n",
       "      <th>quadra</th>\n",
       "      <th>s_festas</th>\n",
       "      <th>s_jogos</th>\n",
       "      <th>s_ginastica</th>\n",
       "      <th>sauna</th>\n",
       "      <th>vista_mar</th>\n",
       "      <th>origem</th>\n",
       "      <th>preco</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>223</td>\n",
       "      <td>167</td>\n",
       "      <td>55</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2001</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>157</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>680000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2002</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>450000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2003</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>149</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>1080000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2004</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>treino</td>\n",
       "      <td>350000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>1996</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>1997</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>64</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>1998</td>\n",
       "      <td>0</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>112</td>\n",
       "      <td>2810</td>\n",
       "      <td>58</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>1999</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>69</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>teste</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6162 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Id  tipo  bairro  tipo_vendedor  quartos  suites  vagas  area_util  \\\n",
       "0     2000     1      36              0        3       3      5        223   \n",
       "1     2001     0      15              0        4       4      2        157   \n",
       "2     2002     0      25              0        3       1      0         53   \n",
       "3     2003     0      10              0        4       3      2        149   \n",
       "4     2004     0      54              0        2       1      1         54   \n",
       "...    ...   ...     ...            ...      ...     ...    ...        ...   \n",
       "1995  1995     0      50              0        2       1      2        100   \n",
       "1996  1996     0      43              0        3       1      1         90   \n",
       "1997  1997     0      10              0        3       1      1         73   \n",
       "1998  1998     0      65              0        4       3      2        112   \n",
       "1999  1999     0      25              0        2       1      1         51   \n",
       "\n",
       "      area_extra  diferenciais  ...  piscina  playground  quadra  s_festas  \\\n",
       "0            167            55  ...        1           0       0         0   \n",
       "1              0            54  ...        1           0       0         0   \n",
       "2              0            50  ...        0           0       0         0   \n",
       "3              0            54  ...        1           0       0         0   \n",
       "4              0            54  ...        1           0       0         0   \n",
       "...          ...           ...  ...      ...         ...     ...       ...   \n",
       "1995           0            50  ...        0           0       0         0   \n",
       "1996           0            50  ...        0           0       0         0   \n",
       "1997           0            64  ...        1           0       0         1   \n",
       "1998        2810            58  ...        1           0       0         0   \n",
       "1999           0            69  ...        0           1       0         0   \n",
       "\n",
       "      s_jogos  s_ginastica  sauna  vista_mar  origem      preco  \n",
       "0           0            0      0          0  treino  1000000.0  \n",
       "1           0            0      0          0  treino   680000.0  \n",
       "2           0            0      0          0  treino   450000.0  \n",
       "3           0            0      0          0  treino  1080000.0  \n",
       "4           0            0      0          0  treino   350000.0  \n",
       "...       ...          ...    ...        ...     ...        ...  \n",
       "1995        0            0      0          0   teste        NaN  \n",
       "1996        0            0      0          0   teste        NaN  \n",
       "1997        0            0      0          0   teste        NaN  \n",
       "1998        0            0      0          1   teste        NaN  \n",
       "1999        0            1      0          0   teste        NaN  \n",
       "\n",
       "[6162 rows x 22 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "outliers.to_csv('data/desafio 2/hp_from_eda_2.csv', index=False)"
   ]
  }
 ],
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