majorproject_manas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 425,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Name', 'Location', 'Year', 'Kilometers_Driven', 'Fuel_Type',\n",
      "       'Transmission', 'Owner_Type', 'Mileage', 'Engine', 'Power', 'Seats',\n",
      "       'Price'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "data = pd.read_excel('/Users/manasmaurya/Downloads/Data_Train.xlsx')\n",
    "print(data.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 427,
   "metadata": {},
   "outputs": [],
   "source": [
    "org = pd.read_excel('/Users/manasmaurya/Downloads/Data_Train.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        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>Name</th>\n",
       "      <th>Location</th>\n",
       "      <th>Year</th>\n",
       "      <th>Kilometers_Driven</th>\n",
       "      <th>Fuel_Type</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>Owner_Type</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>Engine</th>\n",
       "      <th>Power</th>\n",
       "      <th>Seats</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Maruti Wagon R LXI CNG</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2010</td>\n",
       "      <td>72000</td>\n",
       "      <td>CNG</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>26.6 km/kg</td>\n",
       "      <td>998 CC</td>\n",
       "      <td>58.16 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Hyundai Creta 1.6 CRDi SX Option</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2015</td>\n",
       "      <td>41000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>19.67 kmpl</td>\n",
       "      <td>1582 CC</td>\n",
       "      <td>126.2 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Honda Jazz V</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2011</td>\n",
       "      <td>46000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>18.2 kmpl</td>\n",
       "      <td>1199 CC</td>\n",
       "      <td>88.7 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Maruti Ertiga VDI</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2012</td>\n",
       "      <td>87000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>20.77 kmpl</td>\n",
       "      <td>1248 CC</td>\n",
       "      <td>88.76 bhp</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Audi A4 New 2.0 TDI Multitronic</td>\n",
       "      <td>Coimbatore</td>\n",
       "      <td>2013</td>\n",
       "      <td>40670</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>Second</td>\n",
       "      <td>15.2 kmpl</td>\n",
       "      <td>1968 CC</td>\n",
       "      <td>140.8 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>17.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Hyundai EON LPG Era Plus Option</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>2012</td>\n",
       "      <td>75000</td>\n",
       "      <td>LPG</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>21.1 km/kg</td>\n",
       "      <td>814 CC</td>\n",
       "      <td>55.2 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Nissan Micra Diesel XV</td>\n",
       "      <td>Jaipur</td>\n",
       "      <td>2013</td>\n",
       "      <td>86999</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>23.08 kmpl</td>\n",
       "      <td>1461 CC</td>\n",
       "      <td>63.1 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Toyota Innova Crysta 2.8 GX AT 8S</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2016</td>\n",
       "      <td>36000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>First</td>\n",
       "      <td>11.36 kmpl</td>\n",
       "      <td>2755 CC</td>\n",
       "      <td>171.5 bhp</td>\n",
       "      <td>8.0</td>\n",
       "      <td>17.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Volkswagen Vento Diesel Comfortline</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2013</td>\n",
       "      <td>64430</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>20.54 kmpl</td>\n",
       "      <td>1598 CC</td>\n",
       "      <td>103.6 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Tata Indica Vista Quadrajet LS</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2012</td>\n",
       "      <td>65932</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second</td>\n",
       "      <td>22.3 kmpl</td>\n",
       "      <td>1248 CC</td>\n",
       "      <td>74 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.95</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Name    Location  Year  Kilometers_Driven  \\\n",
       "0               Maruti Wagon R LXI CNG      Mumbai  2010              72000   \n",
       "1     Hyundai Creta 1.6 CRDi SX Option        Pune  2015              41000   \n",
       "2                         Honda Jazz V     Chennai  2011              46000   \n",
       "3                    Maruti Ertiga VDI     Chennai  2012              87000   \n",
       "4      Audi A4 New 2.0 TDI Multitronic  Coimbatore  2013              40670   \n",
       "5      Hyundai EON LPG Era Plus Option   Hyderabad  2012              75000   \n",
       "6               Nissan Micra Diesel XV      Jaipur  2013              86999   \n",
       "7    Toyota Innova Crysta 2.8 GX AT 8S      Mumbai  2016              36000   \n",
       "8  Volkswagen Vento Diesel Comfortline        Pune  2013              64430   \n",
       "9       Tata Indica Vista Quadrajet LS     Chennai  2012              65932   \n",
       "\n",
       "  Fuel_Type Transmission Owner_Type     Mileage   Engine      Power  Seats  \\\n",
       "0       CNG       Manual      First  26.6 km/kg   998 CC  58.16 bhp    5.0   \n",
       "1    Diesel       Manual      First  19.67 kmpl  1582 CC  126.2 bhp    5.0   \n",
       "2    Petrol       Manual      First   18.2 kmpl  1199 CC   88.7 bhp    5.0   \n",
       "3    Diesel       Manual      First  20.77 kmpl  1248 CC  88.76 bhp    7.0   \n",
       "4    Diesel    Automatic     Second   15.2 kmpl  1968 CC  140.8 bhp    5.0   \n",
       "5       LPG       Manual      First  21.1 km/kg   814 CC   55.2 bhp    5.0   \n",
       "6    Diesel       Manual      First  23.08 kmpl  1461 CC   63.1 bhp    5.0   \n",
       "7    Diesel    Automatic      First  11.36 kmpl  2755 CC  171.5 bhp    8.0   \n",
       "8    Diesel       Manual      First  20.54 kmpl  1598 CC  103.6 bhp    5.0   \n",
       "9    Diesel       Manual     Second   22.3 kmpl  1248 CC     74 bhp    5.0   \n",
       "\n",
       "   Price  \n",
       "0   1.75  \n",
       "1  12.50  \n",
       "2   4.50  \n",
       "3   6.00  \n",
       "4  17.74  \n",
       "5   2.35  \n",
       "6   3.50  \n",
       "7  17.50  \n",
       "8   5.20  \n",
       "9   1.95  "
      ]
     },
     "execution_count": 428,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 429,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop('Name', axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "metadata": {},
   "outputs": [],
   "source": [
    "locations = data.Location.unique()\n",
    "num = list(np.arange(data.Location.nunique()))\n",
    "data['Location'] = data['Location'].map({location : n for location,n in zip(locations,num)})\n",
    "yr = data.Year.unique()\n",
    "num = np.arange(data.Year.nunique())\n",
    "data['Year'] = data['Year'].map({y : n for y,n in zip(yr,num)})\n",
    "fuel = data.Fuel_Type.unique()\n",
    "num = np.arange(data.Fuel_Type.nunique())\n",
    "data['Fuel_Type'] = data['Fuel_Type'].map({f : n for f,n in zip(fuel,num)})\n",
    "transm = data.Transmission.unique()\n",
    "num = np.arange(data.Transmission.nunique())\n",
    "data['Transmission'] = data['Transmission'].map({t : n for t,n in zip(transm,num)})\n",
    "own = data.Owner_Type.unique()\n",
    "num = np.arange(data.Owner_Type.nunique())\n",
    "data['Owner_Type'] =  data['Owner_Type'].map({o : n for o,n in zip(own,num)})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 431,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Location</th>\n",
       "      <th>Year</th>\n",
       "      <th>Kilometers_Driven</th>\n",
       "      <th>Fuel_Type</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>Owner_Type</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>Engine</th>\n",
       "      <th>Power</th>\n",
       "      <th>Seats</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>72000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6 km/kg</td>\n",
       "      <td>998 CC</td>\n",
       "      <td>58.16 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>41000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19.67 kmpl</td>\n",
       "      <td>1582 CC</td>\n",
       "      <td>126.2 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>46000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18.2 kmpl</td>\n",
       "      <td>1199 CC</td>\n",
       "      <td>88.7 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>87000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20.77 kmpl</td>\n",
       "      <td>1248 CC</td>\n",
       "      <td>88.76 bhp</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>40670</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>15.2 kmpl</td>\n",
       "      <td>1968 CC</td>\n",
       "      <td>140.8 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>17.74</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Location  Year  Kilometers_Driven  Fuel_Type  Transmission  Owner_Type  \\\n",
       "0         0     0              72000          0             0           0   \n",
       "1         1     1              41000          1             0           0   \n",
       "2         2     2              46000          2             0           0   \n",
       "3         2     3              87000          1             0           0   \n",
       "4         3     4              40670          1             1           1   \n",
       "\n",
       "      Mileage   Engine      Power  Seats  Price  \n",
       "0  26.6 km/kg   998 CC  58.16 bhp    5.0   1.75  \n",
       "1  19.67 kmpl  1582 CC  126.2 bhp    5.0  12.50  \n",
       "2   18.2 kmpl  1199 CC   88.7 bhp    5.0   4.50  \n",
       "3  20.77 kmpl  1248 CC  88.76 bhp    7.0   6.00  \n",
       "4   15.2 kmpl  1968 CC  140.8 bhp    5.0  17.74  "
      ]
     },
     "execution_count": 431,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(data.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "13.2 km/kg\n",
      "33.54 km/kg\n",
      "0.0 kmpl\n",
      "9.9 kmpl\n"
     ]
    }
   ],
   "source": [
    "print(data.loc[(data.Fuel_Type == 0) | (data.Fuel_Type == 3) ].Mileage.dropna().min())\n",
    "print(data.loc[(data.Fuel_Type == 0) | (data.Fuel_Type == 3) ].Mileage.dropna().max())\n",
    "print(data.loc[(data.Fuel_Type != 0) & (data.Fuel_Type != 3) ].Mileage.dropna().min())\n",
    "print(data.loc[(data.Fuel_Type != 0) & (data.Fuel_Type != 3) ].Mileage.dropna().max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 433,
   "metadata": {},
   "outputs": [],
   "source": [
    "gas = data.loc[(data.Fuel_Type != 0) & (data.Fuel_Type != 3) ].Mileage\n",
    "ngas = data.loc[(data.Fuel_Type == 0) | (data.Fuel_Type == 3) ].Mileage\n",
    "gas = gas.fillna('0 kmpl')\n",
    "data['Mileage'] = data.Mileage.fillna('0 kmpl')\n",
    "data['Engine'] = data.Engine.fillna('0 CC')\n",
    "data['Power'] = data.Power.fillna('0 bhp')\n",
    "data['Seats'] = data.Seats.fillna(1.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Location             0\n",
       "Year                 0\n",
       "Kilometers_Driven    0\n",
       "Fuel_Type            0\n",
       "Transmission         0\n",
       "Owner_Type           0\n",
       "Mileage              0\n",
       "Engine               0\n",
       "Power                0\n",
       "Seats                0\n",
       "Price                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 434,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 435,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1a3777e1d0>"
      ]
     },
     "execution_count": 435,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 72 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 436,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,5))\n",
    "plt.subplot(1,2,1)\n",
    "sns.scatterplot(gas,data.Price) #petrol diesel\n",
    "plt.subplot(1,2,2)\n",
    "sns.scatterplot(ngas,data.Price) #cng lpg\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 437,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,5))\n",
    "plt.subplot(1,2,1)\n",
    "sns.scatterplot(data.Engine,data.Price)\n",
    "plt.subplot(1,2,2)\n",
    "sns.scatterplot(data.Power,data.Price) #cng lpg\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 438,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 15 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "fig, ax = plt.subplots(3,5, figsize = (15,10))\n",
    "col = data.columns\n",
    "\n",
    "fix=data.Power.str.replace('bhp','')\n",
    "fix.loc[fix == 'null '] = 0\n",
    "fix = fix.astype('float')\n",
    "\n",
    "data['Mileage'] = data.Mileage.str.replace('kmpl','')\n",
    "data['Mileage'] = data.Mileage.str.replace('km/kg','').astype('float')\n",
    "data['Power'] = fix\n",
    "data['Engine'] = data.Engine.str.replace('CC','').astype('float')\n",
    "i = 0\n",
    "\n",
    "for m in range(3):\n",
    "    for n in range(5):\n",
    "        sns.distplot(data[col[i]], ax = ax[m][n], kde = False)\n",
    "        i += 1\n",
    "        if i == 11:\n",
    "            break\n",
    "        \n",
    "# getting a better idea about choosing features by looking at distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "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>Location</th>\n",
       "      <th>Year</th>\n",
       "      <th>Kilometers_Driven</th>\n",
       "      <th>Fuel_Type</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>Owner_Type</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>Engine</th>\n",
       "      <th>Power</th>\n",
       "      <th>Seats</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Location</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.052203</td>\n",
       "      <td>-0.029288</td>\n",
       "      <td>-0.057276</td>\n",
       "      <td>-0.031249</td>\n",
       "      <td>-0.072897</td>\n",
       "      <td>0.045962</td>\n",
       "      <td>0.004521</td>\n",
       "      <td>0.014801</td>\n",
       "      <td>-0.001937</td>\n",
       "      <td>0.020010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <td>-0.052203</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.016725</td>\n",
       "      <td>0.086658</td>\n",
       "      <td>-0.004423</td>\n",
       "      <td>0.157145</td>\n",
       "      <td>-0.121006</td>\n",
       "      <td>-0.027024</td>\n",
       "      <td>-0.068464</td>\n",
       "      <td>-0.009259</td>\n",
       "      <td>-0.012938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kilometers_Driven</th>\n",
       "      <td>-0.029288</td>\n",
       "      <td>0.016725</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.098833</td>\n",
       "      <td>-0.025663</td>\n",
       "      <td>0.081791</td>\n",
       "      <td>-0.064915</td>\n",
       "      <td>0.087549</td>\n",
       "      <td>0.022738</td>\n",
       "      <td>0.072391</td>\n",
       "      <td>-0.011493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fuel_Type</th>\n",
       "      <td>-0.057276</td>\n",
       "      <td>0.086658</td>\n",
       "      <td>-0.098833</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.113006</td>\n",
       "      <td>0.045866</td>\n",
       "      <td>-0.170188</td>\n",
       "      <td>-0.383526</td>\n",
       "      <td>-0.252976</td>\n",
       "      <td>-0.281128</td>\n",
       "      <td>-0.289585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transmission</th>\n",
       "      <td>-0.031249</td>\n",
       "      <td>-0.004423</td>\n",
       "      <td>-0.025663</td>\n",
       "      <td>-0.113006</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.011413</td>\n",
       "      <td>-0.334307</td>\n",
       "      <td>0.490800</td>\n",
       "      <td>0.626233</td>\n",
       "      <td>-0.063468</td>\n",
       "      <td>0.586025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Owner_Type</th>\n",
       "      <td>-0.072897</td>\n",
       "      <td>0.157145</td>\n",
       "      <td>0.081791</td>\n",
       "      <td>0.045866</td>\n",
       "      <td>-0.011413</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.154041</td>\n",
       "      <td>0.036330</td>\n",
       "      <td>-0.010148</td>\n",
       "      <td>-0.009767</td>\n",
       "      <td>-0.095508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mileage</th>\n",
       "      <td>0.045962</td>\n",
       "      <td>-0.121006</td>\n",
       "      <td>-0.064915</td>\n",
       "      <td>-0.170188</td>\n",
       "      <td>-0.334307</td>\n",
       "      <td>-0.154041</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.549938</td>\n",
       "      <td>-0.419891</td>\n",
       "      <td>-0.229486</td>\n",
       "      <td>-0.306191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Engine</th>\n",
       "      <td>0.004521</td>\n",
       "      <td>-0.027024</td>\n",
       "      <td>0.087549</td>\n",
       "      <td>-0.383526</td>\n",
       "      <td>0.490800</td>\n",
       "      <td>0.036330</td>\n",
       "      <td>-0.549938</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.844788</td>\n",
       "      <td>0.429117</td>\n",
       "      <td>0.647232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Power</th>\n",
       "      <td>0.014801</td>\n",
       "      <td>-0.068464</td>\n",
       "      <td>0.022738</td>\n",
       "      <td>-0.252976</td>\n",
       "      <td>0.626233</td>\n",
       "      <td>-0.010148</td>\n",
       "      <td>-0.419891</td>\n",
       "      <td>0.844788</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.162230</td>\n",
       "      <td>0.751724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seats</th>\n",
       "      <td>-0.001937</td>\n",
       "      <td>-0.009259</td>\n",
       "      <td>0.072391</td>\n",
       "      <td>-0.281128</td>\n",
       "      <td>-0.063468</td>\n",
       "      <td>-0.009767</td>\n",
       "      <td>-0.229486</td>\n",
       "      <td>0.429117</td>\n",
       "      <td>0.162230</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.057717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Price</th>\n",
       "      <td>0.020010</td>\n",
       "      <td>-0.012938</td>\n",
       "      <td>-0.011493</td>\n",
       "      <td>-0.289585</td>\n",
       "      <td>0.586025</td>\n",
       "      <td>-0.095508</td>\n",
       "      <td>-0.306191</td>\n",
       "      <td>0.647232</td>\n",
       "      <td>0.751724</td>\n",
       "      <td>0.057717</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Location      Year  Kilometers_Driven  Fuel_Type  \\\n",
       "Location           1.000000 -0.052203          -0.029288  -0.057276   \n",
       "Year              -0.052203  1.000000           0.016725   0.086658   \n",
       "Kilometers_Driven -0.029288  0.016725           1.000000  -0.098833   \n",
       "Fuel_Type         -0.057276  0.086658          -0.098833   1.000000   \n",
       "Transmission      -0.031249 -0.004423          -0.025663  -0.113006   \n",
       "Owner_Type        -0.072897  0.157145           0.081791   0.045866   \n",
       "Mileage            0.045962 -0.121006          -0.064915  -0.170188   \n",
       "Engine             0.004521 -0.027024           0.087549  -0.383526   \n",
       "Power              0.014801 -0.068464           0.022738  -0.252976   \n",
       "Seats             -0.001937 -0.009259           0.072391  -0.281128   \n",
       "Price              0.020010 -0.012938          -0.011493  -0.289585   \n",
       "\n",
       "                   Transmission  Owner_Type   Mileage    Engine     Power  \\\n",
       "Location              -0.031249   -0.072897  0.045962  0.004521  0.014801   \n",
       "Year                  -0.004423    0.157145 -0.121006 -0.027024 -0.068464   \n",
       "Kilometers_Driven     -0.025663    0.081791 -0.064915  0.087549  0.022738   \n",
       "Fuel_Type             -0.113006    0.045866 -0.170188 -0.383526 -0.252976   \n",
       "Transmission           1.000000   -0.011413 -0.334307  0.490800  0.626233   \n",
       "Owner_Type            -0.011413    1.000000 -0.154041  0.036330 -0.010148   \n",
       "Mileage               -0.334307   -0.154041  1.000000 -0.549938 -0.419891   \n",
       "Engine                 0.490800    0.036330 -0.549938  1.000000  0.844788   \n",
       "Power                  0.626233   -0.010148 -0.419891  0.844788  1.000000   \n",
       "Seats                 -0.063468   -0.009767 -0.229486  0.429117  0.162230   \n",
       "Price                  0.586025   -0.095508 -0.306191  0.647232  0.751724   \n",
       "\n",
       "                      Seats     Price  \n",
       "Location          -0.001937  0.020010  \n",
       "Year              -0.009259 -0.012938  \n",
       "Kilometers_Driven  0.072391 -0.011493  \n",
       "Fuel_Type         -0.281128 -0.289585  \n",
       "Transmission      -0.063468  0.586025  \n",
       "Owner_Type        -0.009767 -0.095508  \n",
       "Mileage           -0.229486 -0.306191  \n",
       "Engine             0.429117  0.647232  \n",
       "Power              0.162230  0.751724  \n",
       "Seats              1.000000  0.057717  \n",
       "Price              0.057717  1.000000  "
      ]
     },
     "execution_count": 439,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matx = data.corr()\n",
    "corr_matx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 440,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a3b0adf90>"
      ]
     },
     "execution_count": 440,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15,10))\n",
    "sns.heatmap(corr_matx,annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MODEL 1 \n",
    "\n",
    "* didn't remove the outliers \n",
    "* mileage for natural gas and gas weren't separated into two different columns(or dataframe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 441,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a3b34c410>"
      ]
     },
     "execution_count": 441,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#selected on the basis of correlation matrix\n",
    "formodel = data[['Transmission','Mileage','Engine','Power','Price']]\n",
    "sns.heatmap(formodel.corr(), annot = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 442,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.7/site-packages/pandas/core/frame.py:3997: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  errors=errors,\n"
     ]
    }
   ],
   "source": [
    "formodel.drop('Mileage',axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 443,
   "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>Transmission</th>\n",
       "      <th>Engine</th>\n",
       "      <th>Power</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6019.000000</td>\n",
       "      <td>6019.000000</td>\n",
       "      <td>6019.000000</td>\n",
       "      <td>6019.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.285762</td>\n",
       "      <td>1611.579498</td>\n",
       "      <td>110.562372</td>\n",
       "      <td>9.479468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.451814</td>\n",
       "      <td>612.449869</td>\n",
       "      <td>55.956041</td>\n",
       "      <td>11.187917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.440000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1197.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>3.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1493.000000</td>\n",
       "      <td>91.100000</td>\n",
       "      <td>5.640000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1969.000000</td>\n",
       "      <td>138.030000</td>\n",
       "      <td>9.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>5998.000000</td>\n",
       "      <td>560.000000</td>\n",
       "      <td>160.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Transmission       Engine        Power        Price\n",
       "count   6019.000000  6019.000000  6019.000000  6019.000000\n",
       "mean       0.285762  1611.579498   110.562372     9.479468\n",
       "std        0.451814   612.449869    55.956041    11.187917\n",
       "min        0.000000     0.000000     0.000000     0.440000\n",
       "25%        0.000000  1197.000000    74.000000     3.500000\n",
       "50%        0.000000  1493.000000    91.100000     5.640000\n",
       "75%        1.000000  1969.000000   138.030000     9.950000\n",
       "max        1.000000  5998.000000   560.000000   160.000000"
      ]
     },
     "execution_count": 443,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "formodel.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 444,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import preprocessing\n",
    "\n",
    "std_scale = preprocessing.StandardScaler().fit(formodel[['Engine','Power']])\n",
    "df_std = std_scale.transform(formodel[['Engine','Power']])\n",
    "copy = formodel\n",
    "# df = pd.DataFrame({'Engine' :[] ,'Power' : [] })\n",
    "# l = formodel.shape[0]\n",
    "# for i,j in df_std :\n",
    "#     df['Engine'].iloc[-l] = i\n",
    "#     df['Power'].iloc[-l] = j\n",
    "#     l-=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 445,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-1.0019276771968366\n",
      "-0.9365695864138397\n"
     ]
    }
   ],
   "source": [
    "for i, j in df_std:\n",
    "    print(i)\n",
    "    print(j)\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 446,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py:670: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"\n",
      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "copy = formodel\n",
    "l = formodel.shape[0]\n",
    "k = 0\n",
    "for i,j in df_std :\n",
    "    copy['Engine'].iloc[k] = i\n",
    "    copy['Power'].iloc[k] = j\n",
    "    k+=1\n",
    "    if k == l :\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 447,
   "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>Transmission</th>\n",
       "      <th>Engine</th>\n",
       "      <th>Power</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>-1.001928</td>\n",
       "      <td>-0.936570</td>\n",
       "      <td>1.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>-0.048301</td>\n",
       "      <td>0.279486</td>\n",
       "      <td>12.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>-0.673710</td>\n",
       "      <td>-0.390739</td>\n",
       "      <td>4.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>-0.593697</td>\n",
       "      <td>-0.389666</td>\n",
       "      <td>6.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0.582007</td>\n",
       "      <td>0.540427</td>\n",
       "      <td>17.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6014</th>\n",
       "      <td>0</td>\n",
       "      <td>-0.593697</td>\n",
       "      <td>-0.653467</td>\n",
       "      <td>4.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6015</th>\n",
       "      <td>0</td>\n",
       "      <td>-0.802711</td>\n",
       "      <td>-0.707085</td>\n",
       "      <td>4.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6016</th>\n",
       "      <td>0</td>\n",
       "      <td>1.447456</td>\n",
       "      <td>0.025694</td>\n",
       "      <td>2.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6017</th>\n",
       "      <td>0</td>\n",
       "      <td>-1.001928</td>\n",
       "      <td>-0.776788</td>\n",
       "      <td>2.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6018</th>\n",
       "      <td>0</td>\n",
       "      <td>-1.103169</td>\n",
       "      <td>-0.946578</td>\n",
       "      <td>2.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6019 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Transmission    Engine     Power  Price\n",
       "0                0 -1.001928 -0.936570   1.75\n",
       "1                0 -0.048301  0.279486  12.50\n",
       "2                0 -0.673710 -0.390739   4.50\n",
       "3                0 -0.593697 -0.389666   6.00\n",
       "4                1  0.582007  0.540427  17.74\n",
       "...            ...       ...       ...    ...\n",
       "6014             0 -0.593697 -0.653467   4.75\n",
       "6015             0 -0.802711 -0.707085   4.00\n",
       "6016             0  1.447456  0.025694   2.90\n",
       "6017             0 -1.001928 -0.776788   2.65\n",
       "6018             0 -1.103169 -0.946578   2.50\n",
       "\n",
       "[6019 rows x 4 columns]"
      ]
     },
     "execution_count": 447,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 448,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = copy[['Engine', 'Power','Transmission']]\n",
    "y = copy[['Price']]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size = .2, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 449,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
      ]
     },
     "execution_count": 449,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = LinearRegression()\n",
    "model.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 450,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_predict = model.predict(X_test)\n",
    "y_test = np.array(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 451,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6082760668955773\n",
      "46.95946376036265\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import r2_score\n",
    "from sklearn.metrics import mean_squared_error\n",
    "score = r2_score(y_test,y_predict)\n",
    "mse = mean_squared_error(y_test,y_predict)\n",
    "print(score)\n",
    "print(mse)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Two models are created below, one for natural gas driven vehicles and one for normal gas\n",
    "\n",
    "* outliers not removed again \n",
    "\n",
    ">> both models have lower r squared score than the previous model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 452,
   "metadata": {},
   "outputs": [],
   "source": [
    "#org is original dataset\n",
    "org = org[['Transmission','Mileage','Engine','Power','Price','Fuel_Type']]\n",
    "org.Transmission = org.Transmission.map({'Manual' : 0,'Automatic' : 1})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 453,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Transmission     0\n",
      "Mileage          2\n",
      "Engine          36\n",
      "Power           36\n",
      "Price            0\n",
      "Fuel_Type        0\n",
      "dtype: int64\n"
     ]
    },
    {
     "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>Transmission</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>Engine</th>\n",
       "      <th>Power</th>\n",
       "      <th>Price</th>\n",
       "      <th>Fuel_Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>26.6 km/kg</td>\n",
       "      <td>998 CC</td>\n",
       "      <td>58.16 bhp</td>\n",
       "      <td>1.75</td>\n",
       "      <td>CNG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>19.67 kmpl</td>\n",
       "      <td>1582 CC</td>\n",
       "      <td>126.2 bhp</td>\n",
       "      <td>12.50</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>18.2 kmpl</td>\n",
       "      <td>1199 CC</td>\n",
       "      <td>88.7 bhp</td>\n",
       "      <td>4.50</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>20.77 kmpl</td>\n",
       "      <td>1248 CC</td>\n",
       "      <td>88.76 bhp</td>\n",
       "      <td>6.00</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>15.2 kmpl</td>\n",
       "      <td>1968 CC</td>\n",
       "      <td>140.8 bhp</td>\n",
       "      <td>17.74</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Transmission     Mileage   Engine      Power  Price Fuel_Type\n",
       "0             0  26.6 km/kg   998 CC  58.16 bhp   1.75       CNG\n",
       "1             0  19.67 kmpl  1582 CC  126.2 bhp  12.50    Diesel\n",
       "2             0   18.2 kmpl  1199 CC   88.7 bhp   4.50    Petrol\n",
       "3             0  20.77 kmpl  1248 CC  88.76 bhp   6.00    Diesel\n",
       "4             1   15.2 kmpl  1968 CC  140.8 bhp  17.74    Diesel"
      ]
     },
     "execution_count": 453,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(org.isnull().sum())\n",
    "org.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "metadata": {},
   "outputs": [],
   "source": [
    "org.Power = org.Power.fillna('0 bhp')\n",
    "org.Engine = org.Engine.fillna('0 CC')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 455,
   "metadata": {},
   "outputs": [],
   "source": [
    "org.Power = org.Power.str.strip(' bhp')\n",
    "org.Power = org.Power.replace('null','0').astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 456,
   "metadata": {},
   "outputs": [],
   "source": [
    "org.Engine = org.Engine.str.strip(' CC')\n",
    "org.Engine = org.Engine.replace('null','0').astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 457,
   "metadata": {},
   "outputs": [],
   "source": [
    "org_natgas =  org.loc[(org.Fuel_Type =='CNG') | (org.Fuel_Type == 'LPG') ]\n",
    "org_gas = org.loc[(org.Fuel_Type !='CNG') & (org.Fuel_Type != 'LPG') ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 458,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.7/site-packages/pandas/core/generic.py:5303: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self[name] = value\n"
     ]
    }
   ],
   "source": [
    "org_gas.Mileage = org_gas.Mileage.str.strip(' kmpl')\n",
    "org_gas.Mileage = org_gas.Mileage.str.replace('null','0').astype('float')\n",
    "org_gas = org_gas.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 459,
   "metadata": {},
   "outputs": [],
   "source": [
    "org_gas.drop('Fuel_Type', axis = 1,inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 460,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a3ab5f450>"
      ]
     },
     "execution_count": 460,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(org_gas.corr(), annot = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 461,
   "metadata": {},
   "outputs": [],
   "source": [
    "formodel = org_gas.drop('Engine', axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 462,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py:670: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    }
   ],
   "source": [
    "std_scale = preprocessing.StandardScaler().fit(formodel[['Mileage','Power']])\n",
    "df_std = std_scale.transform(formodel[['Mileage','Power']])\n",
    "                                      \n",
    "l = formodel.shape[0]\n",
    "k = 0\n",
    "for i,j in df_std :\n",
    "    formodel['Mileage'].iloc[k] = i\n",
    "    formodel['Power'].iloc[k] = j\n",
    "    k+=1\n",
    "    if k == l :\n",
    "        break                                      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 463,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = formodel[['Transmission', 'Mileage', 'Power']]\n",
    "y = formodel[['Price']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 464,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size = .3, random_state = 0)\n",
    "model = LinearRegression()\n",
    "model.fit(X_train,y_train)\n",
    "y_predict = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 465,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5904283033899749\n",
      "44.36446038891744\n"
     ]
    }
   ],
   "source": [
    "rsquared= r2_score(y_test,y_predict)\n",
    "score = mean_squared_error(y_test,y_predict)\n",
    "print(rsquared)\n",
    "print(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 466,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.7/site-packages/pandas/core/generic.py:5303: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self[name] = value\n"
     ]
    }
   ],
   "source": [
    "org_natgas.Mileage = org_natgas.Mileage.str.strip(' km/kg')\n",
    "org_natgas.Mileage = org_natgas.Mileage.str.replace('null','0').astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              Transmission   Mileage    Engine     Power     Price\n",
      "Transmission           NaN       NaN       NaN       NaN       NaN\n",
      "Mileage                NaN  1.000000 -0.602603 -0.387968 -0.165428\n",
      "Engine                 NaN -0.602603  1.000000  0.814059  0.395858\n",
      "Power                  NaN -0.387968  0.814059  1.000000  0.381982\n",
      "Price                  NaN -0.165428  0.395858  0.381982  1.000000\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.7/site-packages/pandas/core/frame.py:3997: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  errors=errors,\n",
      "/opt/anaconda3/lib/python3.7/site-packages/pandas/core/frame.py:3997: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  errors=errors,\n"
     ]
    }
   ],
   "source": [
    "org_natgas.drop('Fuel_Type',axis = 1, inplace = True)\n",
    "print(org_natgas.corr())\n",
    "org_natgas.drop('Transmission',axis = 1, inplace = True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  import sys\n",
      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "std_scale = preprocessing.StandardScaler().fit(org_natgas[['Mileage','Power']])\n",
    "df_std = std_scale.transform(org_natgas[['Mileage','Power']])\n",
    "                                      \n",
    "l = org_natgas.shape[0]\n",
    "k = 0\n",
    "for i,j in df_std :\n",
    "    org_natgas['Mileage'].iloc[k] = i\n",
    "    org_natgas['Power'].iloc[k] = j\n",
    "    k+=1\n",
    "    if k == l :\n",
    "        break  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 469,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = org_natgas[['Mileage', 'Power']]\n",
    "y = org_natgas[['Price']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 470,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.23627137411612087\n",
      "1.3299053317203018\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size = .3, random_state = 0)\n",
    "model = LinearRegression()\n",
    "model.fit(X_train,y_train)\n",
    "y_predict = model.predict(X_test)\n",
    "rsquared= r2_score(y_test,y_predict)\n",
    "score = mean_squared_error(y_test,y_predict)\n",
    "print(rsquared)\n",
    "print(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 471,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a43209150>"
      ]
     },
     "execution_count": 471,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "formodel = data[['Transmission','Mileage','Engine','Power','Price']]\n",
    "sns.heatmap(formodel.corr(), annot = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 472,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import preprocessing\n",
    "\n",
    "std_scale = preprocessing.StandardScaler().fit(formodel[['Engine','Power','Mileage']])\n",
    "df_std = std_scale.transform(formodel[['Engine','Power','Mileage']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 473,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py:670: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  after removing the cwd from sys.path.\n",
      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"\n",
      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "l = formodel.shape[0]\n",
    "k = 0\n",
    "for i,j,m in df_std :\n",
    "    formodel['Engine'].iloc[k] = i\n",
    "    formodel['Power'].iloc[k] = j\n",
    "    formodel['Mileage'].iloc[k] = m\n",
    "    k+=1\n",
    "    if k == l :\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 474,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = formodel[['Engine', 'Power','Transmission','Mileage']]\n",
    "y = formodel[['Price']]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size = .2, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 475,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6043361042918645\n",
      "47.43178244061271\n"
     ]
    }
   ],
   "source": [
    "model = LinearRegression()\n",
    "model.fit(X_train,y_train)\n",
    "y_predict = model.predict(X_test)\n",
    "rsquared= r2_score(y_test,y_predict)\n",
    "score = mean_squared_error(y_test,y_predict)\n",
    "print(rsquared)\n",
    "print(score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Finally, removing the outliers and creating the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 476,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15,5))\n",
    "plt.subplot(1,4,1)\n",
    "sns.boxplot(formodel.Engine)\n",
    "plt.subplot(1,4,2)\n",
    "sns.boxplot(formodel.Power)\n",
    "plt.subplot(1,4,3)\n",
    "sns.boxplot(formodel.Mileage)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 477,
   "metadata": {},
   "outputs": [],
   "source": [
    "q3 = formodel.Power.quantile(.75)\n",
    "q1 = formodel.Power.quantile(.25)\n",
    "iqr = q3-q1\n",
    "uw = q3+1.5*iqr\n",
    "index = formodel.loc[formodel.Power > uw].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 478,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(238,)"
      ]
     },
     "execution_count": 478,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 479,
   "metadata": {},
   "outputs": [],
   "source": [
    "new = formodel.drop(index, axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 480,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a3e252650>"
      ]
     },
     "execution_count": 480,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(new.Power)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "q3 = new.Power.quantile(.75)\n",
    "q1 = new.Power.quantile(.25)\n",
    "iqr = q3-q1\n",
    "uw = q3+1.5*iqr\n",
    "index = new.loc[new.Power > uw].index\n",
    "new2 = new.drop(index, axis = 0)\n",
    "sns.boxplot(new2.Power)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 482,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50,)"
      ]
     },
     "execution_count": 482,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 483,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5194326539956577\n",
      "26.790413819482392\n"
     ]
    }
   ],
   "source": [
    "X = new2[['Power','Transmission','Mileage']]\n",
    "y = new2[['Price']]\n",
    "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size = .2, random_state = 0)\n",
    "model = LinearRegression()\n",
    "model.fit(X_train,y_train)\n",
    "y_predict = model.predict(X_test)\n",
    "rsquared = r2_score(y_test,y_predict)\n",
    "score = mean_squared_error(y_test,y_predict)\n",
    "print(rsquared)\n",
    "print(score)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}