car_prices_almost.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e77781e2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "9d2b409b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\brand\\AppData\\Local\\Temp\\ipykernel_11352\\135345739.py:6: DtypeWarning: Columns (21) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df2 = pd.read_csv('2_data.csv')\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "df0 = pd.read_csv('0_data.csv')\n",
    "df1 = pd.read_csv('1_data.csv')\n",
    "df2 = pd.read_csv('2_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "b5785d80",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "        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>vin</th>\n",
       "      <th>year</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>city</th>\n",
       "      <th>mileage</th>\n",
       "      <th>fuel</th>\n",
       "      <th>transmission</th>\n",
       "      <th>engine</th>\n",
       "      <th>drive</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ZACNJABB5KPJ92081</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>Jeep</td>\n",
       "      <td>Renegade</td>\n",
       "      <td>Bayamon</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>A</td>\n",
       "      <td>I4</td>\n",
       "      <td>FWD</td>\n",
       "      <td>23141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SALCJ2FX1LH858117</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>Land Rover</td>\n",
       "      <td>Discovery Sport</td>\n",
       "      <td>San Juan</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>A</td>\n",
       "      <td>I4</td>\n",
       "      <td>AWD</td>\n",
       "      <td>46500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JF1VA2M67G9829723</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>Subaru</td>\n",
       "      <td>WRX STI</td>\n",
       "      <td>Guaynabo</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>M</td>\n",
       "      <td>H4</td>\n",
       "      <td>AWD</td>\n",
       "      <td>46995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SALRR2RV0L2433391</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>Land Rover</td>\n",
       "      <td>Discovery</td>\n",
       "      <td>San Juan</td>\n",
       "      <td>11.0</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>A</td>\n",
       "      <td>V6</td>\n",
       "      <td>AWD</td>\n",
       "      <td>67430.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SALCJ2FXXLH862327</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>Land Rover</td>\n",
       "      <td>Discovery Sport</td>\n",
       "      <td>San Juan</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>A</td>\n",
       "      <td>I4</td>\n",
       "      <td>AWD</td>\n",
       "      <td>48880.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99995</th>\n",
       "      <td>WA1ANAFY0J2138713</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Audi</td>\n",
       "      <td>Q5</td>\n",
       "      <td>Selma</td>\n",
       "      <td>29085.0</td>\n",
       "      <td>Premium Unleaded</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4WD</td>\n",
       "      <td>31395.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99996</th>\n",
       "      <td>JF1VA1A60K9818070</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>Subaru</td>\n",
       "      <td>WRX</td>\n",
       "      <td>Charlotte</td>\n",
       "      <td>30003.0</td>\n",
       "      <td>Premium Unleaded</td>\n",
       "      <td>Manual</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4WD</td>\n",
       "      <td>29990.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99997</th>\n",
       "      <td>WBXYH9C03L5P79755</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>BMW</td>\n",
       "      <td>X2</td>\n",
       "      <td>Murrieta</td>\n",
       "      <td>8825.0</td>\n",
       "      <td>Premium Unleaded</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>2.0</td>\n",
       "      <td>FWD</td>\n",
       "      <td>35991.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99998</th>\n",
       "      <td>JTJYARBZ7H2082838</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>Lexus</td>\n",
       "      <td>NX</td>\n",
       "      <td>Buford</td>\n",
       "      <td>56955.0</td>\n",
       "      <td>Premium Unleaded</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>2.0</td>\n",
       "      <td>FWD</td>\n",
       "      <td>27960.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99999</th>\n",
       "      <td>WBXHT3C37J5L28038</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>BMW</td>\n",
       "      <td>X1</td>\n",
       "      <td>South Amboy</td>\n",
       "      <td>23342.0</td>\n",
       "      <td>Premium Unleaded</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4WD</td>\n",
       "      <td>26288.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>300000 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     vin    year        make            model         city  \\\n",
       "0      ZACNJABB5KPJ92081  2019.0        Jeep         Renegade      Bayamon   \n",
       "1      SALCJ2FX1LH858117  2020.0  Land Rover  Discovery Sport     San Juan   \n",
       "2      JF1VA2M67G9829723  2016.0      Subaru          WRX STI     Guaynabo   \n",
       "3      SALRR2RV0L2433391  2020.0  Land Rover        Discovery     San Juan   \n",
       "4      SALCJ2FXXLH862327  2020.0  Land Rover  Discovery Sport     San Juan   \n",
       "...                  ...     ...         ...              ...          ...   \n",
       "99995  WA1ANAFY0J2138713  2018.0        Audi               Q5        Selma   \n",
       "99996  JF1VA1A60K9818070  2019.0      Subaru              WRX    Charlotte   \n",
       "99997  WBXYH9C03L5P79755  2020.0         BMW               X2     Murrieta   \n",
       "99998  JTJYARBZ7H2082838  2017.0       Lexus               NX       Buford   \n",
       "99999  WBXHT3C37J5L28038  2018.0         BMW               X1  South Amboy   \n",
       "\n",
       "       mileage              fuel transmission engine drive    price  \n",
       "0          7.0          Gasoline            A     I4   FWD  23141.0  \n",
       "1          8.0          Gasoline            A     I4   AWD  46500.0  \n",
       "2          NaN          Gasoline            M     H4   AWD  46995.0  \n",
       "3         11.0          Gasoline            A     V6   AWD  67430.0  \n",
       "4          7.0          Gasoline            A     I4   AWD  48880.0  \n",
       "...        ...               ...          ...    ...   ...      ...  \n",
       "99995  29085.0  Premium Unleaded    Automatic    2.0   4WD  31395.0  \n",
       "99996  30003.0  Premium Unleaded       Manual    2.0   4WD  29990.0  \n",
       "99997   8825.0  Premium Unleaded    Automatic    2.0   FWD  35991.0  \n",
       "99998  56955.0  Premium Unleaded    Automatic    2.0   FWD  27960.0  \n",
       "99999  23342.0  Premium Unleaded    Automatic    2.0   4WD  26288.0  \n",
       "\n",
       "[300000 rows x 11 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO: add transmission, engine something, vin -> country of manufacter, body type\n",
    "df0 = df0[['vin', 'year', 'make_name', 'model_name', 'city', 'mileage', 'fuel_type', 'transmission', 'engine_cylinders','wheel_system', 'price']]\n",
    "df0.columns = ['vin', 'year', 'make', 'model', 'city', 'mileage', 'fuel','transmission', 'engine','drive', 'price']\n",
    "\n",
    "df1 = df1[['VIN', 'year', 'manufacturer', 'model', 'region', 'odometer', 'fuel','transmission','cylinders','drive', 'price']]\n",
    "df1.columns = ['vin', 'year', 'make', 'model', 'city', 'mileage', 'fuel','transmission', 'engine','drive', 'price']\n",
    "\n",
    "df2 = df2[['vin', 'year', 'make', 'model', 'city', 'miles', 'fuel_type', 'transmission', 'engine_size','drivetrain', 'price']]\n",
    "df2.columns = ['vin', 'year', 'make', 'model', 'city', 'mileage', 'fuel','transmission', 'engine','drive', 'price']\n",
    "\n",
    "frames=[df0,df1,df2]\n",
    "df = pd.concat(frames)\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "6974ee49",
   "metadata": {},
   "outputs": [],
   "source": [
    "backup = df.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9cbb23a",
   "metadata": {},
   "source": [
    "# Preprocess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "88e5b0d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# cleaning\n",
    "\n",
    "#dropping null values\n",
    "df=df.dropna()\n",
    "\n",
    "#dropping any cars less than 100 dollars (all of the dropped ones actually have a price of 0)\n",
    "df=df.loc[df['price']>100]\n",
    "\n",
    "# standardizing the make feature\n",
    "def normal_string(s):\n",
    "    return s.lower().replace(' ', '').replace('-', '').replace('_', '')\n",
    " \n",
    "df['model'] = df['model'].apply(normal_string)\n",
    "df['make'] = df['make'].apply(normal_string)\n",
    "df['city'] = df['city'].apply(normal_string)\n",
    "df['drive'] = df['drive'].apply(normal_string)\n",
    "\n",
    "\n",
    "# standardizing the fuel feature\n",
    "gasoline = {'gas', \n",
    "            'E85 / Unleaded',\n",
    "       'Unleaded', 'Premium Unleaded',\n",
    "       'Premium Unleaded; Unleaded', \n",
    "       'Unleaded; Unleaded / E85', 'Unleaded / E85',\n",
    "       'E85 / Unleaded; Unleaded', 'Premium Unleaded / Unleaded',\n",
    "       'E85 / Premium Unleaded; E85 / Unleaded', \n",
    "       'E85', 'E85 / Premium Unleaded', \n",
    "       'Compressed Natural Gas; Unleaded',\n",
    "       'E85 / Unleaded; Unleaded / Unleaded',\n",
    "       'Diesel / Premium Unleaded', 'E85 / Unleaded; Unleaded / E85',\n",
    "       'Unleaded / Unleaded', \n",
    "       'Compressed Natural Gas / Unleaded', 'Diesel; Unleaded',\n",
    "       'Diesel; E85 / Unleaded', 'E85 / Unleaded; Premium Unleaded',\n",
    "       'Premium Unleaded; Premium Unleaded / E85', 'E85; E85 / Unleaded',\n",
    "       'Unleaded / Premium Unleaded',\n",
    "       'Premium Unleaded / E85',\n",
    "       'M85 / Unleaded'\n",
    "}\n",
    "\n",
    "diesel = {\n",
    "    'Biodiesel'\n",
    "}\n",
    "\n",
    "hybrid = {\n",
    "       'Electric / Premium Unleaded', \n",
    "       'Electric / Unleaded',\n",
    "       'Unleaded / Electric',\n",
    "       'Electric / Hydrogen',\n",
    "       'Electric / Premium Unleaded; Electric / Unleaded',\n",
    "       'Electric / Premium Unleaded; Premium Unleaded',\n",
    "       'Electric / E85'\n",
    "}\n",
    "\n",
    "other = {\n",
    "    'Hydrogen', \n",
    "    'Premium Unleaded / Natural Gas',\n",
    "    'Compressed Natural Gas / Lpg', \n",
    "    'Compressed Natural Gas', 'Propane',\n",
    "    'Flex Fuel Vehicle',\n",
    "}\n",
    "\n",
    "def fuel_preprocess(x):\n",
    "    if x in gasoline:\n",
    "        return 'gasoline'\n",
    "    if x in diesel:\n",
    "        return 'diesel'\n",
    "    if x in hybrid:\n",
    "        return 'hybrid'\n",
    "    if x in other:\n",
    "        return 'other'\n",
    "    return x\n",
    "\n",
    "\n",
    "df['fuel'] = df['fuel'].apply(fuel_preprocess)\n",
    "\n",
    "def find_engine_size(s):\n",
    "    if type(s) == float:\n",
    "        return s\n",
    "    elif type(s) == str:\n",
    "        n_str = ''\n",
    "        for c in s:\n",
    "            if c.isnumeric() or c == '.':\n",
    "                n_str += c\n",
    "        if len(n_str) > 0:\n",
    "            return float(n_str)/2\n",
    "        else:\n",
    "            return(np.nan)\n",
    "    else:\n",
    "        print('other type')\n",
    "        return(np.nan)\n",
    "\n",
    "df['engine'] = df['engine'].apply(find_engine_size)\n",
    "df = df.dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77cb26a1",
   "metadata": {},
   "source": [
    "# explore top x most common variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "c12777be",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "top 10 variables of make make up 65.6% our its values\n",
      "top 10 variables of model make up 16.24% our its values\n",
      "top 10 variables of city make up 7.55% our its values\n",
      "top 10 variables of fuel make up 100.0% our its values\n",
      "top 10 variables of transmission make up 100.0% our its values\n",
      "top 10 variables of drive make up 100.0% our its values\n"
     ]
    }
   ],
   "source": [
    "x = 10\n",
    "\n",
    "cat_list = ['make', 'model', 'city', 'fuel', 'transmission', 'drive']\n",
    "cat_df = df[cat_list]\n",
    "\n",
    "def get_top_ratio(column, x):\n",
    "    top_x = sum(column.value_counts().tolist()[:x])\n",
    "    total = column.value_counts().sum()\n",
    "    return top_x / total\n",
    "\n",
    "for column in cat_df:\n",
    "    ratio = get_top_ratio(df[column], x) * 100\n",
    "    print(f'top {x} variables of {column} make up {np.round(ratio, 2)}% our its values')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90da1678",
   "metadata": {},
   "source": [
    "# one hot encoding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "e4f9f651",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import OneHotEncoder\n",
    "\n",
    "enc = OneHotEncoder(sparse_output = False, max_categories = x)\n",
    "cat_df = enc.fit_transform(cat_df)\n",
    "cat_df = pd.DataFrame(cat_df)\n",
    "cat_df.columns = enc.get_feature_names_out()\n",
    "cat_df.head()\n",
    "\n",
    "df = df.drop(cat_list, axis = 1)\n",
    "df = cat_df.join(df, how='outer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "73b40a2d",
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>make_bmw</th>\n",
       "      <th>make_chevrolet</th>\n",
       "      <th>make_dodge</th>\n",
       "      <th>make_ford</th>\n",
       "      <th>make_honda</th>\n",
       "      <th>make_jeep</th>\n",
       "      <th>make_mercedesbenz</th>\n",
       "      <th>make_nissan</th>\n",
       "      <th>make_toyota</th>\n",
       "      <th>make_infrequent_sklearn</th>\n",
       "      <th>model_challenger</th>\n",
       "      <th>model_ecosport</th>\n",
       "      <th>model_equinox</th>\n",
       "      <th>model_escape</th>\n",
       "      <th>model_f150</th>\n",
       "      <th>model_fusion</th>\n",
       "      <th>model_grandcherokee</th>\n",
       "      <th>model_ram2500pickup</th>\n",
       "      <th>model_silverado1500</th>\n",
       "      <th>model_infrequent_sklearn</th>\n",
       "      <th>city_anchorage/matsu</th>\n",
       "      <th>city_bronx</th>\n",
       "      <th>city_brooklyn</th>\n",
       "      <th>city_clintontownship</th>\n",
       "      <th>city_danbury</th>\n",
       "      <th>city_novi</th>\n",
       "      <th>city_rochesterhills</th>\n",
       "      <th>city_stamford</th>\n",
       "      <th>city_waterbury</th>\n",
       "      <th>city_infrequent_sklearn</th>\n",
       "      <th>fuel_Diesel</th>\n",
       "      <th>fuel_Gasoline</th>\n",
       "      <th>fuel_Hybrid</th>\n",
       "      <th>fuel_diesel</th>\n",
       "      <th>fuel_electric</th>\n",
       "      <th>fuel_gasoline</th>\n",
       "      <th>fuel_hybrid</th>\n",
       "      <th>fuel_other</th>\n",
       "      <th>transmission_A</th>\n",
       "      <th>transmission_Automatic</th>\n",
       "      <th>transmission_CVT</th>\n",
       "      <th>transmission_Dual Clutch</th>\n",
       "      <th>transmission_M</th>\n",
       "      <th>transmission_Manual</th>\n",
       "      <th>transmission_automatic</th>\n",
       "      <th>transmission_manual</th>\n",
       "      <th>transmission_other</th>\n",
       "      <th>drive_4wd</th>\n",
       "      <th>drive_4x2</th>\n",
       "      <th>drive_awd</th>\n",
       "      <th>drive_fwd</th>\n",
       "      <th>drive_rwd</th>\n",
       "      <th>vin</th>\n",
       "      <th>year</th>\n",
       "      <th>mileage</th>\n",
       "      <th>engine</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>ZACNJABB5KPJ92081</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>23141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1GCWGFCF3F1284719</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>115879.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>20998.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>SALCJ2FX1LH858117</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>46500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>WBY7Z8C59JVB87514</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>7339.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>27921.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>ML32F4FJ2JHF10325</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>39798.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>11055.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   make_bmw  make_chevrolet  make_dodge  make_ford  make_honda  make_jeep  \\\n",
       "0       0.0             0.0         0.0        0.0         0.0        1.0   \n",
       "0       0.0             0.0         0.0        0.0         0.0        1.0   \n",
       "1       0.0             0.0         0.0        0.0         0.0        0.0   \n",
       "1       0.0             0.0         0.0        0.0         0.0        0.0   \n",
       "2       0.0             0.0         0.0        0.0         0.0        0.0   \n",
       "\n",
       "   make_mercedesbenz  make_nissan  make_toyota  make_infrequent_sklearn  \\\n",
       "0                0.0          0.0          0.0                      0.0   \n",
       "0                0.0          0.0          0.0                      0.0   \n",
       "1                0.0          0.0          0.0                      1.0   \n",
       "1                0.0          0.0          0.0                      1.0   \n",
       "2                0.0          0.0          0.0                      1.0   \n",
       "\n",
       "   model_challenger  model_ecosport  model_equinox  model_escape  model_f150  \\\n",
       "0               0.0             0.0            0.0           0.0         0.0   \n",
       "0               0.0             0.0            0.0           0.0         0.0   \n",
       "1               0.0             0.0            0.0           0.0         0.0   \n",
       "1               0.0             0.0            0.0           0.0         0.0   \n",
       "2               0.0             0.0            0.0           0.0         0.0   \n",
       "\n",
       "   model_fusion  model_grandcherokee  model_ram2500pickup  \\\n",
       "0           0.0                  0.0                  0.0   \n",
       "0           0.0                  0.0                  0.0   \n",
       "1           0.0                  0.0                  0.0   \n",
       "1           0.0                  0.0                  0.0   \n",
       "2           0.0                  0.0                  0.0   \n",
       "\n",
       "   model_silverado1500  model_infrequent_sklearn  city_anchorage/matsu  \\\n",
       "0                  0.0                       1.0                   0.0   \n",
       "0                  0.0                       1.0                   0.0   \n",
       "1                  0.0                       1.0                   0.0   \n",
       "1                  0.0                       1.0                   0.0   \n",
       "2                  0.0                       1.0                   0.0   \n",
       "\n",
       "   city_bronx  city_brooklyn  city_clintontownship  city_danbury  city_novi  \\\n",
       "0         0.0            0.0                   0.0           0.0        0.0   \n",
       "0         0.0            0.0                   0.0           0.0        0.0   \n",
       "1         0.0            0.0                   0.0           0.0        0.0   \n",
       "1         0.0            0.0                   0.0           0.0        0.0   \n",
       "2         0.0            0.0                   0.0           0.0        0.0   \n",
       "\n",
       "   city_rochesterhills  city_stamford  city_waterbury  \\\n",
       "0                  0.0            0.0             0.0   \n",
       "0                  0.0            0.0             0.0   \n",
       "1                  0.0            0.0             0.0   \n",
       "1                  0.0            0.0             0.0   \n",
       "2                  0.0            0.0             0.0   \n",
       "\n",
       "   city_infrequent_sklearn  fuel_Diesel  fuel_Gasoline  fuel_Hybrid  \\\n",
       "0                      1.0          0.0            1.0          0.0   \n",
       "0                      1.0          0.0            1.0          0.0   \n",
       "1                      1.0          0.0            1.0          0.0   \n",
       "1                      1.0          0.0            1.0          0.0   \n",
       "2                      1.0          0.0            1.0          0.0   \n",
       "\n",
       "   fuel_diesel  fuel_electric  fuel_gasoline  fuel_hybrid  fuel_other  \\\n",
       "0          0.0            0.0            0.0          0.0         0.0   \n",
       "0          0.0            0.0            0.0          0.0         0.0   \n",
       "1          0.0            0.0            0.0          0.0         0.0   \n",
       "1          0.0            0.0            0.0          0.0         0.0   \n",
       "2          0.0            0.0            0.0          0.0         0.0   \n",
       "\n",
       "   transmission_A  transmission_Automatic  transmission_CVT  \\\n",
       "0             1.0                     0.0               0.0   \n",
       "0             1.0                     0.0               0.0   \n",
       "1             1.0                     0.0               0.0   \n",
       "1             1.0                     0.0               0.0   \n",
       "2             1.0                     0.0               0.0   \n",
       "\n",
       "   transmission_Dual Clutch  transmission_M  transmission_Manual  \\\n",
       "0                       0.0             0.0                  0.0   \n",
       "0                       0.0             0.0                  0.0   \n",
       "1                       0.0             0.0                  0.0   \n",
       "1                       0.0             0.0                  0.0   \n",
       "2                       0.0             0.0                  0.0   \n",
       "\n",
       "   transmission_automatic  transmission_manual  transmission_other  drive_4wd  \\\n",
       "0                     0.0                  0.0                 0.0        0.0   \n",
       "0                     0.0                  0.0                 0.0        0.0   \n",
       "1                     0.0                  0.0                 0.0        0.0   \n",
       "1                     0.0                  0.0                 0.0        0.0   \n",
       "2                     0.0                  0.0                 0.0        0.0   \n",
       "\n",
       "   drive_4x2  drive_awd  drive_fwd  drive_rwd                vin    year  \\\n",
       "0        0.0        0.0        1.0        0.0  ZACNJABB5KPJ92081  2019.0   \n",
       "0        0.0        0.0        1.0        0.0  1GCWGFCF3F1284719  2015.0   \n",
       "1        0.0        1.0        0.0        0.0  SALCJ2FX1LH858117  2020.0   \n",
       "1        0.0        1.0        0.0        0.0  WBY7Z8C59JVB87514  2018.0   \n",
       "2        0.0        1.0        0.0        0.0  ML32F4FJ2JHF10325  2018.0   \n",
       "\n",
       "    mileage  engine    price  \n",
       "0       7.0     2.0  23141.0  \n",
       "0  115879.0     4.8  20998.0  \n",
       "1       8.0     2.0  46500.0  \n",
       "1    7339.0     0.6  27921.0  \n",
       "2   39798.0     1.2  11055.0  "
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7d26d9e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "almost_df = df.drop('vin', axis=1)\n",
    "\n",
    "almost_df = almost_df.sample(frac=0.2, random_state = 2)\n",
    "\n",
    "almost_df.memory_usage(index=True).sum()/1000000\n",
    "\n",
    "#almost_df.to_csv('almost_df.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e32595f9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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