Used Car Price Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Predicting the Price of Used Cars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this Project, we are going to predict the Price of Used Cars using various features like Brand, Price, Mileage, Fuel_Type, Year etc. The data used in this project was downloaded from Kaggle.\n",
    "\n",
    "**To be able to predict used cars market value can help both buyers and sellers.**\n",
    "\n",
    "There are lots of individuals who are interested in the used car market at some points in their life because they wanted to sell their car or buy a used car. In this process, it’s a big corner to pay too much or sell less then it’s market value."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.metrics import r2_score\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "\n",
    "sns.set_palette(\"GnBu_d\")\n",
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading the raw data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "car_data = pd.read_csv(\"Datasets/car_price_data1.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Brand</th>\n",
       "      <th>Price</th>\n",
       "      <th>Body</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>EngineV</th>\n",
       "      <th>Engine Type</th>\n",
       "      <th>Registration</th>\n",
       "      <th>Year</th>\n",
       "      <th>Model</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BMW</td>\n",
       "      <td>4200.0</td>\n",
       "      <td>sedan</td>\n",
       "      <td>277</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>yes</td>\n",
       "      <td>1991</td>\n",
       "      <td>320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mercedes-Benz</td>\n",
       "      <td>7900.0</td>\n",
       "      <td>van</td>\n",
       "      <td>427</td>\n",
       "      <td>2.9</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>yes</td>\n",
       "      <td>1999</td>\n",
       "      <td>Sprinter 212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mercedes-Benz</td>\n",
       "      <td>13300.0</td>\n",
       "      <td>sedan</td>\n",
       "      <td>358</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Gas</td>\n",
       "      <td>yes</td>\n",
       "      <td>2003</td>\n",
       "      <td>S 500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Audi</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>crossover</td>\n",
       "      <td>240</td>\n",
       "      <td>4.2</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>yes</td>\n",
       "      <td>2007</td>\n",
       "      <td>Q7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>18300.0</td>\n",
       "      <td>crossover</td>\n",
       "      <td>120</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>yes</td>\n",
       "      <td>2011</td>\n",
       "      <td>Rav 4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Brand    Price       Body  Mileage  EngineV Engine Type  \\\n",
       "0            BMW   4200.0      sedan      277      2.0      Petrol   \n",
       "1  Mercedes-Benz   7900.0        van      427      2.9      Diesel   \n",
       "2  Mercedes-Benz  13300.0      sedan      358      5.0         Gas   \n",
       "3           Audi  23000.0  crossover      240      4.2      Petrol   \n",
       "4         Toyota  18300.0  crossover      120      2.0      Petrol   \n",
       "\n",
       "  Registration  Year         Model  \n",
       "0          yes  1991           320  \n",
       "1          yes  1999  Sprinter 212  \n",
       "2          yes  2003         S 500  \n",
       "3          yes  2007            Q7  \n",
       "4          yes  2011         Rav 4  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring the descriptive statistics of the variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Brand</th>\n",
       "      <th>Price</th>\n",
       "      <th>Body</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>EngineV</th>\n",
       "      <th>Engine Type</th>\n",
       "      <th>Registration</th>\n",
       "      <th>Year</th>\n",
       "      <th>Model</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4345</td>\n",
       "      <td>4173.000000</td>\n",
       "      <td>4345</td>\n",
       "      <td>4345.000000</td>\n",
       "      <td>4195.000000</td>\n",
       "      <td>4345</td>\n",
       "      <td>4345</td>\n",
       "      <td>4345.000000</td>\n",
       "      <td>4345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Volkswagen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sedan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>E-Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>936</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1649</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019</td>\n",
       "      <td>3947</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>NaN</td>\n",
       "      <td>19418.746935</td>\n",
       "      <td>NaN</td>\n",
       "      <td>161.237284</td>\n",
       "      <td>2.790734</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2006.550058</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>25584.242620</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.705797</td>\n",
       "      <td>5.066437</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.719097</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>NaN</td>\n",
       "      <td>600.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1969.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6999.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>1.800000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2003.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>11500.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>155.000000</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>21700.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>230.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2012.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>NaN</td>\n",
       "      <td>300000.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>980.000000</td>\n",
       "      <td>99.990000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Brand          Price   Body      Mileage      EngineV  \\\n",
       "count         4345    4173.000000   4345  4345.000000  4195.000000   \n",
       "unique           7            NaN      6          NaN          NaN   \n",
       "top     Volkswagen            NaN  sedan          NaN          NaN   \n",
       "freq           936            NaN   1649          NaN          NaN   \n",
       "mean           NaN   19418.746935    NaN   161.237284     2.790734   \n",
       "std            NaN   25584.242620    NaN   105.705797     5.066437   \n",
       "min            NaN     600.000000    NaN     0.000000     0.600000   \n",
       "25%            NaN    6999.000000    NaN    86.000000     1.800000   \n",
       "50%            NaN   11500.000000    NaN   155.000000     2.200000   \n",
       "75%            NaN   21700.000000    NaN   230.000000     3.000000   \n",
       "max            NaN  300000.000000    NaN   980.000000    99.990000   \n",
       "\n",
       "       Engine Type Registration         Year    Model  \n",
       "count         4345         4345  4345.000000     4345  \n",
       "unique           4            2          NaN      312  \n",
       "top         Diesel          yes          NaN  E-Class  \n",
       "freq          2019         3947          NaN      199  \n",
       "mean           NaN          NaN  2006.550058      NaN  \n",
       "std            NaN          NaN     6.719097      NaN  \n",
       "min            NaN          NaN  1969.000000      NaN  \n",
       "25%            NaN          NaN  2003.000000      NaN  \n",
       "50%            NaN          NaN  2008.000000      NaN  \n",
       "75%            NaN          NaN  2012.000000      NaN  \n",
       "max            NaN          NaN  2016.000000      NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_data.describe(include='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4345 entries, 0 to 4344\n",
      "Data columns (total 9 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Brand         4345 non-null   object \n",
      " 1   Price         4173 non-null   float64\n",
      " 2   Body          4345 non-null   object \n",
      " 3   Mileage       4345 non-null   int64  \n",
      " 4   EngineV       4195 non-null   float64\n",
      " 5   Engine Type   4345 non-null   object \n",
      " 6   Registration  4345 non-null   object \n",
      " 7   Year          4345 non-null   int64  \n",
      " 8   Model         4345 non-null   object \n",
      "dtypes: float64(2), int64(2), object(5)\n",
      "memory usage: 305.6+ KB\n"
     ]
    }
   ],
   "source": [
    "# Information of the data\n",
    "car_data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Drop features that are not required to build our model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# In Model column There are three hundred and twelve unique models. \n",
    "# That's something really hard to implement and a regression that would mean more than 300 dummies,\n",
    "df = car_data.drop(labels='Model', axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check for any missing value in data set and treat it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Brand             0\n",
       "Price           172\n",
       "Body              0\n",
       "Mileage           0\n",
       "EngineV         150\n",
       "Engine Type       0\n",
       "Registration      0\n",
       "Year              0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# so we are simply droping all nan values, and this is not always recommended, \n",
    "# however when we remove less than 5% of the data, then it is okay\n",
    "df_no_mv = df.dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Exploring the PDFs\n",
    "The probability distribution will show us how that variable is distributed "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Car Price Distribution Plot')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# This makes it very easy to spot anomalies, such as outliers\n",
    "plt.figure(figsize=[11,5])\n",
    "sns.distplot(df_no_mv['Price'])\n",
    "plt.title('Car Price Distribution Plot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'EngineV Distribution Plot')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# car and mileage Distribution Plot\n",
    "plt.figure(figsize=[17,5])\n",
    "plt.subplot(1,3,1)\n",
    "sns.distplot(df_no_mv['Year'])\n",
    "plt.title('Car Year Distribution Plot')\n",
    "\n",
    "plt.subplot(1,3,2)\n",
    "sns.distplot(df_no_mv['Mileage'])\n",
    "plt.title('Car Mileage Distribution Plot')\n",
    "\n",
    "plt.subplot(1,3,3)\n",
    "sns.distplot(df_no_mv['EngineV'])\n",
    "plt.title('EngineV Distribution Plot')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Now its clear that some outliers presents in Price, year, Mileage and EngineV numerical veriables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dealing with outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Price column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here, the outliers are situated around the higher prices (right side of the graph)\n",
    "# we can deal with the problem easily by removing 0.5%, or 1% of the problematic samples\n",
    "# This is a dataset about used cars, therefore one can imagine how $300,000 is an excessive price\n",
    "# Outliers are a great issue for OLS, thus we must deal with them in some way\n",
    "\n",
    "# Let's declare a variable that will be equal to the 99th percentile of the 'Price' variable\n",
    "q = df_no_mv['Price'].quantile(0.99)\n",
    "\n",
    "# Then we can create a new df, with the condition that all prices must be below the 99 percentile of 'Price'\n",
    "data_1 = df_no_mv[df_no_mv['Price']<q]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Car Price Distribution Plot')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#check the PDF once again\n",
    "plt.figure(figsize=[11,5])\n",
    "sns.distplot(data_1['Price'])\n",
    "plt.title('Car Price Distribution Plot')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, there are much fewer outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " * Mileage Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Car Mileage Distribution Plot')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Now we can treat the other numerical variables outlier in a similar way\n",
    "sns.distplot(df_no_mv['Mileage'])\n",
    "plt.title('Car Mileage Distribution Plot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "q = data_1['Mileage'].quantile(0.99)\n",
    "data_2 = data_1[data_1['Mileage']<q]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Mileage', ylabel='Density'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Hurray this plot looks kind of normal\n",
    "sns.distplot(data_2['Mileage'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Year Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Year', ylabel='Density'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# In this scenario outliers are on the low end\n",
    "sns.distplot(df_no_mv['Year'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "q = data_2['Year'].quantile(0.01)\n",
    "data_3 = data_2[data_2['Year']>q]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Year', ylabel='Density'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(data_3['Year'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* EngineV Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'EngineV Distribution Plot')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The situation with engine volume is very strange\n",
    "# In such cases it makes sense to manually check what may be causing the problem\n",
    "# In our case the issue comes from the fact that most missing values are indicated with 99.99 or 99\n",
    "# There are also some incorrect entries like 75\n",
    "sns.distplot(df_no_mv['EngineV'])\n",
    "plt.title('EngineV Distribution Plot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Car engine volumes are usually (always?) below 6.5l, You can google it\n",
    "# This is a prime example of the fact that a domain expert (a person working in the car industry)\n",
    "# may find it much easier to determine problems with the data than an outsider\n",
    "data_4 = data_3[data_3['EngineV']<6.5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='EngineV', ylabel='Density'>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# now its looks kind of normal\n",
    "sns.distplot(data_4['EngineV'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reset index\n",
    "cleaned_data = data_4.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>Price</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>EngineV</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3867.000000</td>\n",
       "      <td>3867.000000</td>\n",
       "      <td>3867.000000</td>\n",
       "      <td>3867.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>18194.455679</td>\n",
       "      <td>160.542539</td>\n",
       "      <td>2.450440</td>\n",
       "      <td>2006.709853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>19085.855165</td>\n",
       "      <td>95.633291</td>\n",
       "      <td>0.949366</td>\n",
       "      <td>6.103870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>800.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>1988.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7200.000000</td>\n",
       "      <td>91.000000</td>\n",
       "      <td>1.800000</td>\n",
       "      <td>2003.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>11700.000000</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>2008.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>21700.000000</td>\n",
       "      <td>225.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2012.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>129222.000000</td>\n",
       "      <td>435.000000</td>\n",
       "      <td>6.300000</td>\n",
       "      <td>2016.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Price      Mileage      EngineV         Year\n",
       "count    3867.000000  3867.000000  3867.000000  3867.000000\n",
       "mean    18194.455679   160.542539     2.450440  2006.709853\n",
       "std     19085.855165    95.633291     0.949366     6.103870\n",
       "min       800.000000     0.000000     0.600000  1988.000000\n",
       "25%      7200.000000    91.000000     1.800000  2003.000000\n",
       "50%     11700.000000   157.000000     2.200000  2008.000000\n",
       "75%     21700.000000   225.000000     3.000000  2012.000000\n",
       "max    129222.000000   435.000000     6.300000  2016.000000"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# once again checking discriptive statistics\n",
    "cleaned_data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## lets check the linearity using a scatter plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Price and EngineV')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Scatter Plot of independent variables vs dependent variables\n",
    "plt.figure(figsize=[20,7])\n",
    "plt.subplot(1,3,1)\n",
    "plt.title(\"Price and Year\")\n",
    "sns.scatterplot(x='Year',y='Price',data=cleaned_data)\n",
    "\n",
    "plt.subplot(1,3,2)\n",
    "plt.title(\"Price and Mileage\")\n",
    "sns.scatterplot(x='Price',y='Mileage',data=cleaned_data)\n",
    "\n",
    "plt.subplot(1,3,3)\n",
    "sns.scatterplot(y='Price',x='EngineV',data=cleaned_data)\n",
    "plt.title(\"Price and EngineV\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we can spot patterns but definitely not perfect linear once. we know we should not run a linear regression in this case. we should first transform one or more variables recall the ditribution plot of price to all these plot are pointing us towards the idea that **price is not normally distributed.**\n",
    "\n",
    "And from there its relationships with the other rather normally distributed features is not linear."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Price', ylabel='Density'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#recall the distribution plot of price\n",
    "sns.distplot(cleaned_data['Price'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See The patterns are quite exponentials in this condition **log transformation is a common way to deal with this issue.** log transformation is especially useful when facing exponential scatter plots like we do now."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Let's transform 'Price' with a log transformation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>Brand</th>\n",
       "      <th>Price</th>\n",
       "      <th>Body</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>EngineV</th>\n",
       "      <th>Engine Type</th>\n",
       "      <th>Registration</th>\n",
       "      <th>Year</th>\n",
       "      <th>log_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BMW</td>\n",
       "      <td>4200.0</td>\n",
       "      <td>sedan</td>\n",
       "      <td>277</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>yes</td>\n",
       "      <td>1991</td>\n",
       "      <td>8.342840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mercedes-Benz</td>\n",
       "      <td>7900.0</td>\n",
       "      <td>van</td>\n",
       "      <td>427</td>\n",
       "      <td>2.9</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>yes</td>\n",
       "      <td>1999</td>\n",
       "      <td>8.974618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mercedes-Benz</td>\n",
       "      <td>13300.0</td>\n",
       "      <td>sedan</td>\n",
       "      <td>358</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Gas</td>\n",
       "      <td>yes</td>\n",
       "      <td>2003</td>\n",
       "      <td>9.495519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Audi</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>crossover</td>\n",
       "      <td>240</td>\n",
       "      <td>4.2</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>yes</td>\n",
       "      <td>2007</td>\n",
       "      <td>10.043249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>18300.0</td>\n",
       "      <td>crossover</td>\n",
       "      <td>120</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>yes</td>\n",
       "      <td>2011</td>\n",
       "      <td>9.814656</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Brand    Price       Body  Mileage  EngineV Engine Type  \\\n",
       "0            BMW   4200.0      sedan      277      2.0      Petrol   \n",
       "1  Mercedes-Benz   7900.0        van      427      2.9      Diesel   \n",
       "2  Mercedes-Benz  13300.0      sedan      358      5.0         Gas   \n",
       "3           Audi  23000.0  crossover      240      4.2      Petrol   \n",
       "4         Toyota  18300.0  crossover      120      2.0      Petrol   \n",
       "\n",
       "  Registration  Year  log_price  \n",
       "0          yes  1991   8.342840  \n",
       "1          yes  1999   8.974618  \n",
       "2          yes  2003   9.495519  \n",
       "3          yes  2007  10.043249  \n",
       "4          yes  2011   9.814656  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's transform 'Price' with a log transformation\n",
    "log_price = np.log(cleaned_data['Price'])\n",
    "\n",
    "# Then we add it to our data frame\n",
    "cleaned_data['log_price'] = log_price\n",
    "cleaned_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Log price and EngineV')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's check the three scatters once again\n",
    "\n",
    "plt.figure(figsize=[20,7])\n",
    "plt.subplot(1,3,1)\n",
    "plt.title(\"Log price and Year\")\n",
    "sns.scatterplot(x='Year',y='log_price',data=cleaned_data)\n",
    "\n",
    "plt.subplot(1,3,2)\n",
    "plt.title(\"Log price and Mileage\")\n",
    "sns.scatterplot(y='log_price',x='Mileage',data=cleaned_data)\n",
    "\n",
    "plt.subplot(1,3,3)\n",
    "sns.scatterplot(y='log_price',x='EngineV',data=cleaned_data)\n",
    "plt.title(\"Log price and EngineV\")\n",
    "\n",
    "# The relationships show a clear linear relationship\n",
    "# This is some good linear regression material"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Since we will be using the log price variable, we can drop the old 'Price' one\n",
    "cleaned_data = cleaned_data.drop(['Price'],axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Checking Multicollinearity Using VIF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>VIF</th>\n",
       "      <th>Features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.791584</td>\n",
       "      <td>Mileage</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.354854</td>\n",
       "      <td>Year</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.662068</td>\n",
       "      <td>EngineV</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         VIF Features\n",
       "0   3.791584  Mileage\n",
       "1  10.354854     Year\n",
       "2   7.662068  EngineV"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
    "variables = cleaned_data[['Mileage','Year','EngineV']]\n",
    "vif = pd.DataFrame()\n",
    "vif[\"VIF\"] = [variance_inflation_factor(variables.values, i) for i in range(variables.shape[1])]\n",
    "# Finally, I like to include names so it is easier to explore the result\n",
    "vif[\"Features\"] = variables.columns\n",
    "vif"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Fixing Multicollinearity:*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 'Year' has high VIF so we are just droping that column\n",
    "# So even if EngineV seems with a high VIF, too, once 'Year' is gone that will no longer be the case\n",
    "data_no_multicolinearity = cleaned_data.drop('Year',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Brand</th>\n",
       "      <th>Body</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>EngineV</th>\n",
       "      <th>Engine Type</th>\n",
       "      <th>Registration</th>\n",
       "      <th>log_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BMW</td>\n",
       "      <td>sedan</td>\n",
       "      <td>277</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>yes</td>\n",
       "      <td>8.342840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mercedes-Benz</td>\n",
       "      <td>van</td>\n",
       "      <td>427</td>\n",
       "      <td>2.9</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>yes</td>\n",
       "      <td>8.974618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mercedes-Benz</td>\n",
       "      <td>sedan</td>\n",
       "      <td>358</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Gas</td>\n",
       "      <td>yes</td>\n",
       "      <td>9.495519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Audi</td>\n",
       "      <td>crossover</td>\n",
       "      <td>240</td>\n",
       "      <td>4.2</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>yes</td>\n",
       "      <td>10.043249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>crossover</td>\n",
       "      <td>120</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>yes</td>\n",
       "      <td>9.814656</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Brand       Body  Mileage  EngineV Engine Type Registration  \\\n",
       "0            BMW      sedan      277      2.0      Petrol          yes   \n",
       "1  Mercedes-Benz        van      427      2.9      Diesel          yes   \n",
       "2  Mercedes-Benz      sedan      358      5.0         Gas          yes   \n",
       "3           Audi  crossover      240      4.2      Petrol          yes   \n",
       "4         Toyota  crossover      120      2.0      Petrol          yes   \n",
       "\n",
       "   log_price  \n",
       "0   8.342840  \n",
       "1   8.974618  \n",
       "2   9.495519  \n",
       "3  10.043249  \n",
       "4   9.814656  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_no_multicolinearity.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature Selection\n",
    "\n",
    "Feature selection simplified models, improves speed and prevent a series of unwanted issues arising from having many features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--Correated Features with target variable--\n",
      "\n",
      "Mileage         0.614806\n",
      "Registration    0.462986\n",
      "EngineV         0.411935\n",
      "Body            0.387294\n",
      "Brand           0.099597\n",
      "Engine Type     0.014890\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "temp_data = data_no_multicolinearity.copy()\n",
    "for col in temp_data.columns:\n",
    "    if temp_data[col].dtypes == 'object':\n",
    "        encoder = LabelEncoder()\n",
    "        temp_data[col] = encoder.fit_transform(temp_data[col])\n",
    "        \n",
    "# Correated Features with target variable\n",
    "print('\\n--Correated Features with target variable--\\n')\n",
    "print(abs(temp_data.corrwith(temp_data['log_price'])).sort_values(ascending=False)[1:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# correlation heat map\n",
    "plt.figure(figsize=[15,7])\n",
    "sns.heatmap(data_no_multicolinearity.corr(), annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Feature Importance**\n",
    "\n",
    "*Feature importance gives you a score for each feature of your data, the higher the score more important or relevant is the feature towards our Target variable.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ExtraTreesRegressor()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">ExtraTreesRegressor</label><div class=\"sk-toggleable__content\"><pre>ExtraTreesRegressor()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "ExtraTreesRegressor()"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Important feature using ExtraTreesRegressor\n",
    "from sklearn.ensemble import ExtraTreesRegressor\n",
    "X = temp_data.drop('log_price',axis=1)\n",
    "y = temp_data['log_price']\n",
    "model = ExtraTreesRegressor()\n",
    "model.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot graph of feature importances for better visualization\n",
    "plt.figure(figsize=[12,6])\n",
    "feat_importances = pd.Series(model.feature_importances_, index=X.columns)\n",
    "feat_importances.nlargest(6).plot(kind='barh')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mileage         0.367932\n",
      "Registration    0.189849\n",
      "EngineV         0.181115\n",
      "Body            0.112891\n",
      "Brand           0.104562\n",
      "Engine Type     0.043651\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(feat_importances.sort_values(ascending=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Categorical Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creating Dummie Variables\n",
    "data_with_dummies = pd.get_dummies(data_no_multicolinearity,drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Mileage</th>\n",
       "      <th>EngineV</th>\n",
       "      <th>log_price</th>\n",
       "      <th>Brand_BMW</th>\n",
       "      <th>Brand_Mercedes-Benz</th>\n",
       "      <th>Brand_Mitsubishi</th>\n",
       "      <th>Brand_Renault</th>\n",
       "      <th>Brand_Toyota</th>\n",
       "      <th>Brand_Volkswagen</th>\n",
       "      <th>Body_hatch</th>\n",
       "      <th>Body_other</th>\n",
       "      <th>Body_sedan</th>\n",
       "      <th>Body_vagon</th>\n",
       "      <th>Body_van</th>\n",
       "      <th>Engine Type_Gas</th>\n",
       "      <th>Engine Type_Other</th>\n",
       "      <th>Engine Type_Petrol</th>\n",
       "      <th>Registration_yes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>277</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.342840</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>427</td>\n",
       "      <td>2.9</td>\n",
       "      <td>8.974618</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>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>358</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.495519</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>240</td>\n",
       "      <td>4.2</td>\n",
       "      <td>10.043249</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>120</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.814656</td>\n",
       "      <td>0</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>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>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mileage  EngineV  log_price  Brand_BMW  Brand_Mercedes-Benz  \\\n",
       "0      277      2.0   8.342840          1                    0   \n",
       "1      427      2.9   8.974618          0                    1   \n",
       "2      358      5.0   9.495519          0                    1   \n",
       "3      240      4.2  10.043249          0                    0   \n",
       "4      120      2.0   9.814656          0                    0   \n",
       "\n",
       "   Brand_Mitsubishi  Brand_Renault  Brand_Toyota  Brand_Volkswagen  \\\n",
       "0                 0              0             0                 0   \n",
       "1                 0              0             0                 0   \n",
       "2                 0              0             0                 0   \n",
       "3                 0              0             0                 0   \n",
       "4                 0              0             1                 0   \n",
       "\n",
       "   Body_hatch  Body_other  Body_sedan  Body_vagon  Body_van  Engine Type_Gas  \\\n",
       "0           0           0           1           0         0                0   \n",
       "1           0           0           0           0         1                0   \n",
       "2           0           0           1           0         0                1   \n",
       "3           0           0           0           0         0                0   \n",
       "4           0           0           0           0         0                0   \n",
       "\n",
       "   Engine Type_Other  Engine Type_Petrol  Registration_yes  \n",
       "0                  0                   1                 1  \n",
       "1                  0                   0                 1  \n",
       "2                  0                   0                 1  \n",
       "3                  0                   1                 1  \n",
       "4                  0                   1                 1  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_with_dummies.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model Development"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Declaring dependent and independent variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = data_with_dummies.drop('log_price',axis=1)\n",
    "y = data_with_dummies['log_price']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Scaling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>StandardScaler()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">StandardScaler</label><div class=\"sk-toggleable__content\"><pre>StandardScaler()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "StandardScaler()"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler()\n",
    "scaler.fit(x[['Mileage','EngineV']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# It is not usually recommended to standardize dummy variables\n",
    "#For ML purposes we rarely put too much thought into it and go with the scale dummies as \n",
    "#scaling has no effect on their predictive power.\n",
    "inputs_scaled = scaler.transform(x[['Mileage','EngineV']])\n",
    "scaled_data = pd.DataFrame(inputs_scaled,columns=['Mileage','EngineV'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_scaled2 =scaled_data.join(x.drop(['Mileage','EngineV'],axis=1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training and Testing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "x_train, x_test, y_train, y_test = train_test_split(input_scaled2,y,test_size=0.2, random_state=365)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Linear Regression Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_squared : 0.7726984972665856\n",
      "RMSE : 0.42982065395637997\n"
     ]
    }
   ],
   "source": [
    "# Model Building\n",
    "from sklearn.linear_model import LinearRegression\n",
    "lr = LinearRegression()\n",
    "\n",
    "# Training Model\n",
    "lr.fit(x_train,y_train)\n",
    "\n",
    "# Model Summary\n",
    "y_pred_lr = lr.predict(x_test)\n",
    "\n",
    "r_squared = r2_score(y_test,y_pred_lr)\n",
    "rmse = np.sqrt(mean_squared_error(y_test,y_pred_lr))\n",
    "print(\"R_squared :\",r_squared)\n",
    "print(\"RMSE :\",rmse)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Random Forest Regressor Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_squared : 0.8096323124973345\n",
      "RMSE : 0.39335325135860916\n"
     ]
    }
   ],
   "source": [
    "# Model Building\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "rf = RandomForestRegressor()\n",
    "\n",
    "# Training Model\n",
    "rf.fit(x_train,y_train)\n",
    "\n",
    "# Model Summary\n",
    "y_pred_rf = rf.predict(x_test)\n",
    "\n",
    "r_squared = r2_score(y_test,y_pred_rf)\n",
    "rmse = np.sqrt(mean_squared_error(y_test,y_pred_rf))\n",
    "print(\"R_squared :\",r_squared)\n",
    "print(\"RMSE :\",rmse)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GBT Regressor Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_squared : 0.812488456013145\n",
      "RMSE : 0.39039130120803894\n"
     ]
    }
   ],
   "source": [
    "# Model Building\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "gbt = GradientBoostingRegressor()\n",
    "\n",
    "# Training Model\n",
    "gbt.fit(x_train,y_train)\n",
    "\n",
    "# Model Summary\n",
    "y_pred_gbt = gbt.predict(x_test)\n",
    "\n",
    "r_squared = r2_score(y_test,y_pred_gbt)\n",
    "rmse = np.sqrt(mean_squared_error(y_test,y_pred_gbt))\n",
    "print(\"R_squared :\",r_squared)\n",
    "print(\"RMSE :\",rmse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 0.28811245515466427\n",
      "MSE: 0.15240536805890578\n",
      "RMSE: 0.39039130120803894\n"
     ]
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "\n",
    "print('MAE:', metrics.mean_absolute_error(y_test, y_pred_gbt))\n",
    "print('MSE:', metrics.mean_squared_error(y_test, y_pred_gbt))\n",
    "print('RMSE:', np.sqrt(metrics.mean_squared_error(y_test, y_pred_gbt)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Select The Best Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*So as we try diferent Regression Alorithms and found that **\"GBT Regressor Model\"** is giving better accuracy compare to other.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# let's manually check these predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>Predicted Price</th>\n",
       "      <th>Actual Price</th>\n",
       "      <th>Residual</th>\n",
       "      <th>Difference%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>769</th>\n",
       "      <td>24080.20</td>\n",
       "      <td>29500.00</td>\n",
       "      <td>5419.80</td>\n",
       "      <td>18.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>770</th>\n",
       "      <td>9552.79</td>\n",
       "      <td>9600.00</td>\n",
       "      <td>47.21</td>\n",
       "      <td>0.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>771</th>\n",
       "      <td>14320.47</td>\n",
       "      <td>18300.00</td>\n",
       "      <td>3979.53</td>\n",
       "      <td>21.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>772</th>\n",
       "      <td>29363.56</td>\n",
       "      <td>68500.00</td>\n",
       "      <td>39136.44</td>\n",
       "      <td>57.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>773</th>\n",
       "      <td>11213.79</td>\n",
       "      <td>10800.00</td>\n",
       "      <td>-413.79</td>\n",
       "      <td>3.83</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Predicted Price  Actual Price  Residual  Difference%\n",
       "769         24080.20      29500.00   5419.80        18.37\n",
       "770          9552.79       9600.00     47.21         0.49\n",
       "771         14320.47      18300.00   3979.53        21.75\n",
       "772         29363.56      68500.00  39136.44        57.13\n",
       "773         11213.79      10800.00   -413.79         3.83"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Finally, let's manually check these predictions\n",
    "# To obtain the actual prices, we take the exponential of the log_price\n",
    "df_ev = pd.DataFrame(np.exp(y_pred_gbt), columns=['Predicted Price'])\n",
    "\n",
    "# We can also include the Actual price column in that data frame (so we can manually compare them)\n",
    "y_test = y_test.reset_index(drop=True)\n",
    "df_ev['Actual Price'] = np.exp(y_test)\n",
    "\n",
    "# we can calculate the difference between the targets and the predictions\n",
    "df_ev['Residual'] = df_ev['Actual Price'] - df_ev['Predicted Price']\n",
    "df_ev['Difference%'] = np.absolute(df_ev['Residual']/df_ev['Actual Price']*100)\n",
    "\n",
    "pd.set_option('display.float_format', lambda x: '%.2f' % x)\n",
    "df_ev.sort_values(by=['Difference%'])\n",
    "\n",
    "df_ev.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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