{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         ID  Price  Levy Manufacturer    Model  Prod. year   Category  \\\n",
      "0  45654403  13328  1399        LEXUS   RX 450        2010       Jeep   \n",
      "1  44731507  16621  1018    CHEVROLET  Equinox        2011       Jeep   \n",
      "2  45774419   8467     -        HONDA      FIT        2006  Hatchback   \n",
      "3  45769185   3607   862         FORD   Escape        2011       Jeep   \n",
      "4  45809263  11726   446        HONDA      FIT        2014  Hatchback   \n",
      "\n",
      "  Leather interior Fuel type Engine volume    Mileage  Cylinders  \\\n",
      "0              Yes    Hybrid           3.5  186005 km        6.0   \n",
      "1               No    Petrol             3  192000 km        6.0   \n",
      "2               No    Petrol           1.3  200000 km        4.0   \n",
      "3              Yes    Hybrid           2.5  168966 km        4.0   \n",
      "4              Yes    Petrol           1.3   91901 km        4.0   \n",
      "\n",
      "  Gear box type Drive wheels   Doors             Wheel   Color  Airbags  \n",
      "0     Automatic          4x4  04-May        Left wheel  Silver       12  \n",
      "1     Tiptronic          4x4  04-May        Left wheel   Black        8  \n",
      "2      Variator        Front  04-May  Right-hand drive   Black        2  \n",
      "3     Automatic          4x4  04-May        Left wheel   White        0  \n",
      "4     Automatic        Front  04-May        Left wheel  Silver        4  \n",
      "Index(['ID', 'Price', 'Levy', 'Manufacturer', 'Model', 'Prod. year',\n",
      "       'Category', 'Leather interior', 'Fuel type', 'Engine volume', 'Mileage',\n",
      "       'Cylinders', 'Gear box type', 'Drive wheels', 'Doors', 'Wheel', 'Color',\n",
      "       'Airbags'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import sklearn\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score\n",
    "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.linear_model import LinearRegression, LogisticRegression\n",
    "from sklearn.tree import DecisionTreeRegressor, DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier\n",
    "from sklearn.metrics import mean_squared_error, f1_score, accuracy_score, roc_auc_score, confusion_matrix, classification_report\n",
    "df = pd.read_csv(\"./static/csv/car_price_prediction.csv\")\n",
    "print(df.head())\n",
    "print(df.columns)"
   ]
  }
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