Assignment - Advanced Regression.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Assignment: Advanced Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Importing the required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import os\n",
    "import warnings\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import StandardScaler,MinMaxScaler\n",
    "from sklearn.model_selection import train_test_split,GridSearchCV,KFold,cross_val_score\n",
    "from sklearn.linear_model import LinearRegression,Ridge,Lasso\n",
    "from sklearn.feature_selection import RFE\n",
    "from sklearn.metrics import r2_score\n",
    "\n",
    "warnings.filterwarnings('ignore')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Performing baisc checks in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "house_price = pd.read_csv('train.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1460, 81)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1460 entries, 0 to 1459\n",
      "Data columns (total 81 columns):\n",
      "Id               1460 non-null int64\n",
      "MSSubClass       1460 non-null int64\n",
      "MSZoning         1460 non-null object\n",
      "LotFrontage      1201 non-null float64\n",
      "LotArea          1460 non-null int64\n",
      "Street           1460 non-null object\n",
      "Alley            91 non-null object\n",
      "LotShape         1460 non-null object\n",
      "LandContour      1460 non-null object\n",
      "Utilities        1460 non-null object\n",
      "LotConfig        1460 non-null object\n",
      "LandSlope        1460 non-null object\n",
      "Neighborhood     1460 non-null object\n",
      "Condition1       1460 non-null object\n",
      "Condition2       1460 non-null object\n",
      "BldgType         1460 non-null object\n",
      "HouseStyle       1460 non-null object\n",
      "OverallQual      1460 non-null int64\n",
      "OverallCond      1460 non-null int64\n",
      "YearBuilt        1460 non-null int64\n",
      "YearRemodAdd     1460 non-null int64\n",
      "RoofStyle        1460 non-null object\n",
      "RoofMatl         1460 non-null object\n",
      "Exterior1st      1460 non-null object\n",
      "Exterior2nd      1460 non-null object\n",
      "MasVnrType       1452 non-null object\n",
      "MasVnrArea       1452 non-null float64\n",
      "ExterQual        1460 non-null object\n",
      "ExterCond        1460 non-null object\n",
      "Foundation       1460 non-null object\n",
      "BsmtQual         1423 non-null object\n",
      "BsmtCond         1423 non-null object\n",
      "BsmtExposure     1422 non-null object\n",
      "BsmtFinType1     1423 non-null object\n",
      "BsmtFinSF1       1460 non-null int64\n",
      "BsmtFinType2     1422 non-null object\n",
      "BsmtFinSF2       1460 non-null int64\n",
      "BsmtUnfSF        1460 non-null int64\n",
      "TotalBsmtSF      1460 non-null int64\n",
      "Heating          1460 non-null object\n",
      "HeatingQC        1460 non-null object\n",
      "CentralAir       1460 non-null object\n",
      "Electrical       1459 non-null object\n",
      "1stFlrSF         1460 non-null int64\n",
      "2ndFlrSF         1460 non-null int64\n",
      "LowQualFinSF     1460 non-null int64\n",
      "GrLivArea        1460 non-null int64\n",
      "BsmtFullBath     1460 non-null int64\n",
      "BsmtHalfBath     1460 non-null int64\n",
      "FullBath         1460 non-null int64\n",
      "HalfBath         1460 non-null int64\n",
      "BedroomAbvGr     1460 non-null int64\n",
      "KitchenAbvGr     1460 non-null int64\n",
      "KitchenQual      1460 non-null object\n",
      "TotRmsAbvGrd     1460 non-null int64\n",
      "Functional       1460 non-null object\n",
      "Fireplaces       1460 non-null int64\n",
      "FireplaceQu      770 non-null object\n",
      "GarageType       1379 non-null object\n",
      "GarageYrBlt      1379 non-null float64\n",
      "GarageFinish     1379 non-null object\n",
      "GarageCars       1460 non-null int64\n",
      "GarageArea       1460 non-null int64\n",
      "GarageQual       1379 non-null object\n",
      "GarageCond       1379 non-null object\n",
      "PavedDrive       1460 non-null object\n",
      "WoodDeckSF       1460 non-null int64\n",
      "OpenPorchSF      1460 non-null int64\n",
      "EnclosedPorch    1460 non-null int64\n",
      "3SsnPorch        1460 non-null int64\n",
      "ScreenPorch      1460 non-null int64\n",
      "PoolArea         1460 non-null int64\n",
      "PoolQC           7 non-null object\n",
      "Fence            281 non-null object\n",
      "MiscFeature      54 non-null object\n",
      "MiscVal          1460 non-null int64\n",
      "MoSold           1460 non-null int64\n",
      "YrSold           1460 non-null int64\n",
      "SaleType         1460 non-null object\n",
      "SaleCondition    1460 non-null object\n",
      "SalePrice        1460 non-null int64\n",
      "dtypes: float64(3), int64(35), object(43)\n",
      "memory usage: 924.0+ KB\n"
     ]
    }
   ],
   "source": [
    "house_price.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0   1          60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "1   2          20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "2   3          60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "3   4          70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "4   5          60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "\n",
       "  LandContour Utilities    ...     PoolArea PoolQC Fence MiscFeature MiscVal  \\\n",
       "0         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "1         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "2         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "3         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "4         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "\n",
       "  MoSold YrSold  SaleType  SaleCondition  SalePrice  \n",
       "0      2   2008        WD         Normal     208500  \n",
       "1      5   2007        WD         Normal     181500  \n",
       "2      9   2008        WD         Normal     223500  \n",
       "3      2   2006        WD        Abnorml     140000  \n",
       "4     12   2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 81 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>...</th>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1201.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1452.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>730.500000</td>\n",
       "      <td>56.897260</td>\n",
       "      <td>70.049958</td>\n",
       "      <td>10516.828082</td>\n",
       "      <td>6.099315</td>\n",
       "      <td>5.575342</td>\n",
       "      <td>1971.267808</td>\n",
       "      <td>1984.865753</td>\n",
       "      <td>103.685262</td>\n",
       "      <td>443.639726</td>\n",
       "      <td>...</td>\n",
       "      <td>94.244521</td>\n",
       "      <td>46.660274</td>\n",
       "      <td>21.954110</td>\n",
       "      <td>3.409589</td>\n",
       "      <td>15.060959</td>\n",
       "      <td>2.758904</td>\n",
       "      <td>43.489041</td>\n",
       "      <td>6.321918</td>\n",
       "      <td>2007.815753</td>\n",
       "      <td>180921.195890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>421.610009</td>\n",
       "      <td>42.300571</td>\n",
       "      <td>24.284752</td>\n",
       "      <td>9981.264932</td>\n",
       "      <td>1.382997</td>\n",
       "      <td>1.112799</td>\n",
       "      <td>30.202904</td>\n",
       "      <td>20.645407</td>\n",
       "      <td>181.066207</td>\n",
       "      <td>456.098091</td>\n",
       "      <td>...</td>\n",
       "      <td>125.338794</td>\n",
       "      <td>66.256028</td>\n",
       "      <td>61.119149</td>\n",
       "      <td>29.317331</td>\n",
       "      <td>55.757415</td>\n",
       "      <td>40.177307</td>\n",
       "      <td>496.123024</td>\n",
       "      <td>2.703626</td>\n",
       "      <td>1.328095</td>\n",
       "      <td>79442.502883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1872.000000</td>\n",
       "      <td>1950.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2006.000000</td>\n",
       "      <td>34900.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>365.750000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>7553.500000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1954.000000</td>\n",
       "      <td>1967.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>2007.000000</td>\n",
       "      <td>129975.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>730.500000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>9478.500000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1973.000000</td>\n",
       "      <td>1994.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>383.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>163000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1095.250000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>11601.500000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>2004.000000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>712.250000</td>\n",
       "      <td>...</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>2009.000000</td>\n",
       "      <td>214000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99%</th>\n",
       "      <td>1445.410000</td>\n",
       "      <td>190.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>37567.640000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>2009.000000</td>\n",
       "      <td>2009.000000</td>\n",
       "      <td>791.920000</td>\n",
       "      <td>1572.410000</td>\n",
       "      <td>...</td>\n",
       "      <td>505.460000</td>\n",
       "      <td>285.820000</td>\n",
       "      <td>261.050000</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>268.050000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>700.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>442567.010000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1460.000000</td>\n",
       "      <td>190.000000</td>\n",
       "      <td>313.000000</td>\n",
       "      <td>215245.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>5644.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>857.000000</td>\n",
       "      <td>547.000000</td>\n",
       "      <td>552.000000</td>\n",
       "      <td>508.000000</td>\n",
       "      <td>480.000000</td>\n",
       "      <td>738.000000</td>\n",
       "      <td>15500.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>755000.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Id   MSSubClass  LotFrontage        LotArea  OverallQual  \\\n",
       "count  1460.000000  1460.000000  1201.000000    1460.000000  1460.000000   \n",
       "mean    730.500000    56.897260    70.049958   10516.828082     6.099315   \n",
       "std     421.610009    42.300571    24.284752    9981.264932     1.382997   \n",
       "min       1.000000    20.000000    21.000000    1300.000000     1.000000   \n",
       "25%     365.750000    20.000000    59.000000    7553.500000     5.000000   \n",
       "50%     730.500000    50.000000    69.000000    9478.500000     6.000000   \n",
       "75%    1095.250000    70.000000    80.000000   11601.500000     7.000000   \n",
       "99%    1445.410000   190.000000   141.000000   37567.640000    10.000000   \n",
       "max    1460.000000   190.000000   313.000000  215245.000000    10.000000   \n",
       "\n",
       "       OverallCond    YearBuilt  YearRemodAdd   MasVnrArea   BsmtFinSF1  \\\n",
       "count  1460.000000  1460.000000   1460.000000  1452.000000  1460.000000   \n",
       "mean      5.575342  1971.267808   1984.865753   103.685262   443.639726   \n",
       "std       1.112799    30.202904     20.645407   181.066207   456.098091   \n",
       "min       1.000000  1872.000000   1950.000000     0.000000     0.000000   \n",
       "25%       5.000000  1954.000000   1967.000000     0.000000     0.000000   \n",
       "50%       5.000000  1973.000000   1994.000000     0.000000   383.500000   \n",
       "75%       6.000000  2000.000000   2004.000000   166.000000   712.250000   \n",
       "99%       9.000000  2009.000000   2009.000000   791.920000  1572.410000   \n",
       "max       9.000000  2010.000000   2010.000000  1600.000000  5644.000000   \n",
       "\n",
       "           ...         WoodDeckSF  OpenPorchSF  EnclosedPorch    3SsnPorch  \\\n",
       "count      ...        1460.000000  1460.000000    1460.000000  1460.000000   \n",
       "mean       ...          94.244521    46.660274      21.954110     3.409589   \n",
       "std        ...         125.338794    66.256028      61.119149    29.317331   \n",
       "min        ...           0.000000     0.000000       0.000000     0.000000   \n",
       "25%        ...           0.000000     0.000000       0.000000     0.000000   \n",
       "50%        ...           0.000000    25.000000       0.000000     0.000000   \n",
       "75%        ...         168.000000    68.000000       0.000000     0.000000   \n",
       "99%        ...         505.460000   285.820000     261.050000   168.000000   \n",
       "max        ...         857.000000   547.000000     552.000000   508.000000   \n",
       "\n",
       "       ScreenPorch     PoolArea       MiscVal       MoSold       YrSold  \\\n",
       "count  1460.000000  1460.000000   1460.000000  1460.000000  1460.000000   \n",
       "mean     15.060959     2.758904     43.489041     6.321918  2007.815753   \n",
       "std      55.757415    40.177307    496.123024     2.703626     1.328095   \n",
       "min       0.000000     0.000000      0.000000     1.000000  2006.000000   \n",
       "25%       0.000000     0.000000      0.000000     5.000000  2007.000000   \n",
       "50%       0.000000     0.000000      0.000000     6.000000  2008.000000   \n",
       "75%       0.000000     0.000000      0.000000     8.000000  2009.000000   \n",
       "99%     268.050000     0.000000    700.000000    12.000000  2010.000000   \n",
       "max     480.000000   738.000000  15500.000000    12.000000  2010.000000   \n",
       "\n",
       "           SalePrice  \n",
       "count    1460.000000  \n",
       "mean   180921.195890  \n",
       "std     79442.502883  \n",
       "min     34900.000000  \n",
       "25%    129975.000000  \n",
       "50%    163000.000000  \n",
       "75%    214000.000000  \n",
       "99%    442567.010000  \n",
       "max    755000.000000  \n",
       "\n",
       "[9 rows x 38 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price.describe([0.25,0.50,0.75,0.99])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the dataset for the amount of nulls present"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PoolQC          1.00\n",
       "MiscFeature     0.96\n",
       "Alley           0.94\n",
       "Fence           0.81\n",
       "FireplaceQu     0.47\n",
       "LotFrontage     0.18\n",
       "GarageType      0.06\n",
       "GarageCond      0.06\n",
       "GarageYrBlt     0.06\n",
       "GarageFinish    0.06\n",
       "GarageQual      0.06\n",
       "BsmtFinType1    0.03\n",
       "BsmtExposure    0.03\n",
       "BsmtCond        0.03\n",
       "BsmtQual        0.03\n",
       "BsmtFinType2    0.03\n",
       "MasVnrArea      0.01\n",
       "MasVnrType      0.01\n",
       "dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(house_price.isnull().sum()/len(house_price.index),2).sort_values(ascending=False).head(18)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Considering 10% as my threshold and dropping the column having more then the threshold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LotFrontage    0.18\n",
       "Alley          0.94\n",
       "FireplaceQu    0.47\n",
       "PoolQC         1.00\n",
       "Fence          0.81\n",
       "MiscFeature    0.96\n",
       "dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(house_price.isnull().sum()/len(house_price.index),2)[round(house_price.isnull().sum()/\n",
    "                                                                 len(house_price.index),2).values>0.10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "house_price = house_price.drop(['LotFrontage','Alley','FireplaceQu','PoolQC','Fence','MiscFeature','MoSold'],axis='columns')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the columns where the missing values between 0-10%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MasVnrType      0.01\n",
       "MasVnrArea      0.01\n",
       "BsmtQual        0.03\n",
       "BsmtCond        0.03\n",
       "BsmtExposure    0.03\n",
       "BsmtFinType1    0.03\n",
       "BsmtFinType2    0.03\n",
       "GarageType      0.06\n",
       "GarageYrBlt     0.06\n",
       "GarageFinish    0.06\n",
       "GarageQual      0.06\n",
       "GarageCond      0.06\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(house_price.isnull().sum()/len(house_price.index),2)[round(house_price.isnull().sum()/\n",
    "                                                                 len(house_price.index),2).values>0.00]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Before going further we will try to convert the Year columns with the age where we are going to fill these columns with number , And if we query the max year for all these columns these will come out to be 2010 ,EX suppose the YearBuilt=2000 , Then YearBuiltOld = 2010-2000 =10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>YearBuilt_Old</th>\n",
       "      <th>YearRemodAdd_Old</th>\n",
       "      <th>GarageYrBlt_Old</th>\n",
       "      <th>YrSold_Old</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1453</th>\n",
       "      <td>2006</td>\n",
       "      <td>2006</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2006</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1277</th>\n",
       "      <td>1967</td>\n",
       "      <td>1976</td>\n",
       "      <td>1967.0</td>\n",
       "      <td>2009</td>\n",
       "      <td>43</td>\n",
       "      <td>34</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>706</th>\n",
       "      <td>1971</td>\n",
       "      <td>2002</td>\n",
       "      <td>1971.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>39</td>\n",
       "      <td>8</td>\n",
       "      <td>39.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1178</th>\n",
       "      <td>1921</td>\n",
       "      <td>1950</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>2009</td>\n",
       "      <td>89</td>\n",
       "      <td>60</td>\n",
       "      <td>89.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1424</th>\n",
       "      <td>1958</td>\n",
       "      <td>1983</td>\n",
       "      <td>1970.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>52</td>\n",
       "      <td>27</td>\n",
       "      <td>40.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681</th>\n",
       "      <td>1932</td>\n",
       "      <td>2000</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>2009</td>\n",
       "      <td>78</td>\n",
       "      <td>10</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1294</th>\n",
       "      <td>1955</td>\n",
       "      <td>1990</td>\n",
       "      <td>1957.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>55</td>\n",
       "      <td>20</td>\n",
       "      <td>53.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>348</th>\n",
       "      <td>2003</td>\n",
       "      <td>2004</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1024</th>\n",
       "      <td>1976</td>\n",
       "      <td>1976</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>34</td>\n",
       "      <td>34</td>\n",
       "      <td>34.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>958</th>\n",
       "      <td>2003</td>\n",
       "      <td>2003</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      YearBuilt  YearRemodAdd  GarageYrBlt  YrSold  YearBuilt_Old  \\\n",
       "1453       2006          2006          NaN    2006              4   \n",
       "1277       1967          1976       1967.0    2009             43   \n",
       "706        1971          2002       1971.0    2007             39   \n",
       "1178       1921          1950       1921.0    2009             89   \n",
       "1424       1958          1983       1970.0    2007             52   \n",
       "681        1932          2000       1968.0    2009             78   \n",
       "1294       1955          1990       1957.0    2006             55   \n",
       "348        2003          2004       2003.0    2008              7   \n",
       "1024       1976          1976       1976.0    2008             34   \n",
       "958        2003          2003       2003.0    2007              7   \n",
       "\n",
       "      YearRemodAdd_Old  GarageYrBlt_Old  YrSold_Old  \n",
       "1453                 4              NaN           4  \n",
       "1277                34             43.0           1  \n",
       "706                  8             39.0           3  \n",
       "1178                60             89.0           1  \n",
       "1424                27             40.0           3  \n",
       "681                 10             42.0           1  \n",
       "1294                20             53.0           4  \n",
       "348                  6              7.0           2  \n",
       "1024                34             34.0           2  \n",
       "958                  7              7.0           3  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price['YearBuilt_Old'] = house_price.YearBuilt.max()-house_price.YearBuilt\n",
    "house_price['YearRemodAdd_Old'] = house_price.YearRemodAdd.max()-house_price.YearRemodAdd\n",
    "house_price['GarageYrBlt_Old'] = house_price.GarageYrBlt.max()-house_price.GarageYrBlt\n",
    "house_price['YrSold_Old'] = house_price.YrSold.max()-house_price.YrSold\n",
    "house_price[['YearBuilt','YearRemodAdd','GarageYrBlt','YrSold','YearBuilt_Old','YearRemodAdd_Old',\n",
    "             'GarageYrBlt_Old','YrSold_Old']].sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Lets drop the actual Year columns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "house_price = house_price.drop(['YearBuilt','YearRemodAdd','GarageYrBlt','YrSold'],axis='columns')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Imputing missing value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Notice imputing GarageYrBlt_Old with -1 as these house donot have garage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "house_price.MasVnrType.fillna('None',inplace=True)\n",
    "house_price.MasVnrArea.fillna(house_price.MasVnrArea.mean(),inplace=True)\n",
    "house_price.BsmtQual.fillna('TA',inplace=True)\n",
    "house_price.BsmtCond.fillna('TA',inplace=True)\n",
    "house_price.BsmtExposure.fillna('No',inplace=True)\n",
    "house_price.BsmtFinType1.fillna('Unf',inplace=True)\n",
    "house_price.BsmtFinType2.fillna('Unf',inplace=True)\n",
    "house_price.GarageType.fillna('Attchd',inplace=True)\n",
    "house_price.GarageYrBlt_Old.fillna(-1,inplace=True)\n",
    "house_price.GarageFinish.fillna('Unf',inplace=True)\n",
    "house_price.GarageQual.fillna('TA',inplace=True)\n",
    "house_price.GarageCond.fillna('TA',inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### As per the analysis 'Street' & 'Utilities' is explaining the lowest valrience hence dropping these columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "house_price.Street.value_counts()\n",
    "house_price.Utilities.value_counts()\n",
    "house_price = house_price.drop(['Street','Utilities'],axis='columns')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 'Id' column is also of no use for our analysis hence dropping the column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "house_price = house_price.drop('Id',axis='columns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>1stFlrSF</th>\n",
       "      <th>...</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>SalePrice</th>\n",
       "      <th>YearBuilt_Old</th>\n",
       "      <th>YearRemodAdd_Old</th>\n",
       "      <th>GarageYrBlt_Old</th>\n",
       "      <th>YrSold_Old</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>56.897260</td>\n",
       "      <td>10516.828082</td>\n",
       "      <td>6.099315</td>\n",
       "      <td>5.575342</td>\n",
       "      <td>103.685262</td>\n",
       "      <td>443.639726</td>\n",
       "      <td>46.549315</td>\n",
       "      <td>567.240411</td>\n",
       "      <td>1057.429452</td>\n",
       "      <td>1162.626712</td>\n",
       "      <td>...</td>\n",
       "      <td>21.954110</td>\n",
       "      <td>3.409589</td>\n",
       "      <td>15.060959</td>\n",
       "      <td>2.758904</td>\n",
       "      <td>43.489041</td>\n",
       "      <td>180921.195890</td>\n",
       "      <td>38.732192</td>\n",
       "      <td>25.134247</td>\n",
       "      <td>29.691096</td>\n",
       "      <td>2.184247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>42.300571</td>\n",
       "      <td>9981.264932</td>\n",
       "      <td>1.382997</td>\n",
       "      <td>1.112799</td>\n",
       "      <td>180.569112</td>\n",
       "      <td>456.098091</td>\n",
       "      <td>161.319273</td>\n",
       "      <td>441.866955</td>\n",
       "      <td>438.705324</td>\n",
       "      <td>386.587738</td>\n",
       "      <td>...</td>\n",
       "      <td>61.119149</td>\n",
       "      <td>29.317331</td>\n",
       "      <td>55.757415</td>\n",
       "      <td>40.177307</td>\n",
       "      <td>496.123024</td>\n",
       "      <td>79442.502883</td>\n",
       "      <td>30.202904</td>\n",
       "      <td>20.645407</td>\n",
       "      <td>25.121824</td>\n",
       "      <td>1.328095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>334.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>34900.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>7553.500000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>223.000000</td>\n",
       "      <td>795.750000</td>\n",
       "      <td>882.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>129975.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>50.000000</td>\n",
       "      <td>9478.500000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>383.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>477.500000</td>\n",
       "      <td>991.500000</td>\n",
       "      <td>1087.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>163000.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>25.500000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>70.000000</td>\n",
       "      <td>11601.500000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>164.250000</td>\n",
       "      <td>712.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>808.000000</td>\n",
       "      <td>1298.250000</td>\n",
       "      <td>1391.250000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>214000.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>190.000000</td>\n",
       "      <td>215245.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>5644.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>2336.000000</td>\n",
       "      <td>6110.000000</td>\n",
       "      <td>4692.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>552.000000</td>\n",
       "      <td>508.000000</td>\n",
       "      <td>480.000000</td>\n",
       "      <td>738.000000</td>\n",
       "      <td>15500.000000</td>\n",
       "      <td>755000.000000</td>\n",
       "      <td>138.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        MSSubClass        LotArea  OverallQual  OverallCond   MasVnrArea  \\\n",
       "count  1460.000000    1460.000000  1460.000000  1460.000000  1460.000000   \n",
       "mean     56.897260   10516.828082     6.099315     5.575342   103.685262   \n",
       "std      42.300571    9981.264932     1.382997     1.112799   180.569112   \n",
       "min      20.000000    1300.000000     1.000000     1.000000     0.000000   \n",
       "25%      20.000000    7553.500000     5.000000     5.000000     0.000000   \n",
       "50%      50.000000    9478.500000     6.000000     5.000000     0.000000   \n",
       "75%      70.000000   11601.500000     7.000000     6.000000   164.250000   \n",
       "max     190.000000  215245.000000    10.000000     9.000000  1600.000000   \n",
       "\n",
       "        BsmtFinSF1   BsmtFinSF2    BsmtUnfSF  TotalBsmtSF     1stFlrSF  \\\n",
       "count  1460.000000  1460.000000  1460.000000  1460.000000  1460.000000   \n",
       "mean    443.639726    46.549315   567.240411  1057.429452  1162.626712   \n",
       "std     456.098091   161.319273   441.866955   438.705324   386.587738   \n",
       "min       0.000000     0.000000     0.000000     0.000000   334.000000   \n",
       "25%       0.000000     0.000000   223.000000   795.750000   882.000000   \n",
       "50%     383.500000     0.000000   477.500000   991.500000  1087.000000   \n",
       "75%     712.250000     0.000000   808.000000  1298.250000  1391.250000   \n",
       "max    5644.000000  1474.000000  2336.000000  6110.000000  4692.000000   \n",
       "\n",
       "          ...       EnclosedPorch    3SsnPorch  ScreenPorch     PoolArea  \\\n",
       "count     ...         1460.000000  1460.000000  1460.000000  1460.000000   \n",
       "mean      ...           21.954110     3.409589    15.060959     2.758904   \n",
       "std       ...           61.119149    29.317331    55.757415    40.177307   \n",
       "min       ...            0.000000     0.000000     0.000000     0.000000   \n",
       "25%       ...            0.000000     0.000000     0.000000     0.000000   \n",
       "50%       ...            0.000000     0.000000     0.000000     0.000000   \n",
       "75%       ...            0.000000     0.000000     0.000000     0.000000   \n",
       "max       ...          552.000000   508.000000   480.000000   738.000000   \n",
       "\n",
       "            MiscVal      SalePrice  YearBuilt_Old  YearRemodAdd_Old  \\\n",
       "count   1460.000000    1460.000000    1460.000000       1460.000000   \n",
       "mean      43.489041  180921.195890      38.732192         25.134247   \n",
       "std      496.123024   79442.502883      30.202904         20.645407   \n",
       "min        0.000000   34900.000000       0.000000          0.000000   \n",
       "25%        0.000000  129975.000000      10.000000          6.000000   \n",
       "50%        0.000000  163000.000000      37.000000         16.000000   \n",
       "75%        0.000000  214000.000000      56.000000         43.000000   \n",
       "max    15500.000000  755000.000000     138.000000         60.000000   \n",
       "\n",
       "       GarageYrBlt_Old   YrSold_Old  \n",
       "count      1460.000000  1460.000000  \n",
       "mean         29.691096     2.184247  \n",
       "std          25.121824     1.328095  \n",
       "min          -1.000000     0.000000  \n",
       "25%           7.000000     1.000000  \n",
       "50%          25.500000     2.000000  \n",
       "75%          48.000000     3.000000  \n",
       "max         110.000000     4.000000  \n",
       "\n",
       "[8 rows x 35 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price[list(house_price.dtypes[house_price.dtypes!='object'].index)].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sns.boxplot(y = house_price['PoolArea'])\n",
    "# house_price['WoodDeckSF'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Lets plot some graph for the EDA purpose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1d3e540b550>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "plt.subplot(2,3,1)\n",
    "plt.scatter(house_price.MasVnrArea,house_price.SalePrice)\n",
    "plt.subplot(2,3,2)\n",
    "plt.scatter(house_price.TotalBsmtSF,house_price.SalePrice)\n",
    "plt.subplot(2,3,3)\n",
    "plt.scatter(house_price['1stFlrSF'],house_price.SalePrice)\n",
    "plt.subplot(2,3,4)\n",
    "plt.scatter(house_price['GarageArea'],house_price.SalePrice)\n",
    "plt.subplot(2,3,5)\n",
    "plt.scatter(house_price['GrLivArea'],house_price.SalePrice)\n",
    "plt.subplot(2,3,6)\n",
    "plt.scatter(house_price['WoodDeckSF'],house_price.SalePrice)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plotting heatmap to check the corellation between varables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,16))\n",
    "sns.heatmap(house_price[list(house_price.dtypes[house_price.dtypes!='object'].index)].corr(),annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Below function is used for hadling the outliers where i am taking the lower and upper quantile as 0.25 & 0.99 respectively"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1460, 71)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_col = list(house_price.dtypes[house_price.dtypes !='object'].index)\n",
    "num_col = ['LotArea','MasVnrArea','BsmtFinSF1','BsmtFinSF2','TotalBsmtSF','1stFlrSF','GrLivArea','OpenPorchSF',\n",
    "           'EnclosedPorch','3SsnPorch',\n",
    "           'ScreenPorch' ,'PoolArea','MiscVal','SalePrice']\n",
    "def drop_outliers(x):\n",
    "    list = []\n",
    "    for col in num_col:\n",
    "        Q1 = x[col].quantile(.25)\n",
    "        Q3 = x[col].quantile(.99)\n",
    "        IQR = Q3-Q1\n",
    "        x =  x[(x[col] >= (Q1-(1.5*IQR))) & (x[col] <= (Q3+(1.5*IQR)))] \n",
    "    return x   \n",
    "\n",
    "house_price = drop_outliers(house_price)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1441, 71)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price.shape"
   ]
  },
  {
   "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>MSZoning</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>LandSlope</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Condition1</th>\n",
       "      <th>Condition2</th>\n",
       "      <th>BldgType</th>\n",
       "      <th>HouseStyle</th>\n",
       "      <th>...</th>\n",
       "      <th>Electrical</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>Functional</th>\n",
       "      <th>GarageType</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "      <th>PavedDrive</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RL</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>...</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Typ</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RL</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Veenker</td>\n",
       "      <td>Feedr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>1Story</td>\n",
       "      <td>...</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>TA</td>\n",
       "      <td>Typ</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RL</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>...</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Typ</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RL</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>Corner</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Crawfor</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>...</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Typ</td>\n",
       "      <td>Detchd</td>\n",
       "      <td>Unf</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RL</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>NoRidge</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>...</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Typ</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  MSZoning LotShape LandContour LotConfig LandSlope Neighborhood Condition1  \\\n",
       "0       RL      Reg         Lvl    Inside       Gtl      CollgCr       Norm   \n",
       "1       RL      Reg         Lvl       FR2       Gtl      Veenker      Feedr   \n",
       "2       RL      IR1         Lvl    Inside       Gtl      CollgCr       Norm   \n",
       "3       RL      IR1         Lvl    Corner       Gtl      Crawfor       Norm   \n",
       "4       RL      IR1         Lvl       FR2       Gtl      NoRidge       Norm   \n",
       "\n",
       "  Condition2 BldgType HouseStyle      ...      Electrical KitchenQual  \\\n",
       "0       Norm     1Fam     2Story      ...           SBrkr          Gd   \n",
       "1       Norm     1Fam     1Story      ...           SBrkr          TA   \n",
       "2       Norm     1Fam     2Story      ...           SBrkr          Gd   \n",
       "3       Norm     1Fam     2Story      ...           SBrkr          Gd   \n",
       "4       Norm     1Fam     2Story      ...           SBrkr          Gd   \n",
       "\n",
       "  Functional GarageType GarageFinish GarageQual GarageCond PavedDrive  \\\n",
       "0        Typ     Attchd          RFn         TA         TA          Y   \n",
       "1        Typ     Attchd          RFn         TA         TA          Y   \n",
       "2        Typ     Attchd          RFn         TA         TA          Y   \n",
       "3        Typ     Detchd          Unf         TA         TA          Y   \n",
       "4        Typ     Attchd          RFn         TA         TA          Y   \n",
       "\n",
       "  SaleType SaleCondition  \n",
       "0       WD        Normal  \n",
       "1       WD        Normal  \n",
       "2       WD        Normal  \n",
       "3       WD       Abnorml  \n",
       "4       WD        Normal  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price[list(house_price.dtypes[house_price.dtypes=='object'].index)].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Lets check for the below columns here we can clearly see that these are having some kind of order and hence we can say these are ordinal in nature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "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>LandSlope</th>\n",
       "      <th>ExterQual</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>HeatingQC</th>\n",
       "      <th>CentralAir</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "      <th>ExterCond</th>\n",
       "      <th>LotShape</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Gtl</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>Unf</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>Gd</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Reg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Gtl</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>Unf</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>TA</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Reg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Gtl</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Mn</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>Unf</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>Gd</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>IR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Gtl</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>No</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>Unf</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Y</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Unf</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>IR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Gtl</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Av</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>Unf</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>Gd</td>\n",
       "      <td>RFn</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>IR1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  LandSlope ExterQual BsmtQual BsmtCond BsmtExposure BsmtFinType1  \\\n",
       "0       Gtl        Gd       Gd       TA           No          GLQ   \n",
       "1       Gtl        TA       Gd       TA           Gd          ALQ   \n",
       "2       Gtl        Gd       Gd       TA           Mn          GLQ   \n",
       "3       Gtl        TA       TA       Gd           No          ALQ   \n",
       "4       Gtl        Gd       Gd       TA           Av          GLQ   \n",
       "\n",
       "  BsmtFinType2 HeatingQC CentralAir KitchenQual GarageFinish GarageQual  \\\n",
       "0          Unf        Ex          Y          Gd          RFn         TA   \n",
       "1          Unf        Ex          Y          TA          RFn         TA   \n",
       "2          Unf        Ex          Y          Gd          RFn         TA   \n",
       "3          Unf        Gd          Y          Gd          Unf         TA   \n",
       "4          Unf        Ex          Y          Gd          RFn         TA   \n",
       "\n",
       "  GarageCond ExterCond LotShape  \n",
       "0         TA        TA      Reg  \n",
       "1         TA        TA      Reg  \n",
       "2         TA        TA      IR1  \n",
       "3         TA        TA      IR1  \n",
       "4         TA        TA      IR1  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price[['LandSlope','ExterQual','BsmtQual','BsmtCond','BsmtExposure','BsmtFinType1','BsmtFinType2',\n",
    "            'HeatingQC','CentralAir',  'KitchenQual','GarageFinish','GarageQual','GarageCond',\n",
    "             'ExterCond','LotShape']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "house_price['LandSlope'] = house_price.LandSlope.map({'Gtl':0,'Mod':1,'Sev':2})\n",
    "house_price['ExterQual'] = house_price.ExterQual.map({'Po':0,'Fa':1,'TA':2,'Gd':3,'Ex':4})\n",
    "house_price['BsmtQual'] = house_price.BsmtQual.map({'NA':0,'Po':1,'Fa':2,'TA':3,'Gd':4,'Ex':5})\n",
    "house_price['BsmtCond'] = house_price.BsmtCond.map({'NA':0,'Po':1,'Fa':2,'TA':3,'Gd':4,'Ex':5})\n",
    "house_price['BsmtExposure'] = house_price.BsmtExposure.map({'NA':0,'No':1,'Mn':2,'Av':3,'Gd':4})\n",
    "house_price['BsmtFinType1'] = house_price.BsmtFinType1.map({'NA':0,'Unf':1,'LwQ':2,'Rec':3,'BLQ':4,'ALQ':5,'GLQ':6})\n",
    "house_price['BsmtFinType2'] = house_price.BsmtFinType2.map({'NA':0,'Unf':1,'LwQ':2,'Rec':3,'BLQ':4,'ALQ':5,'GLQ':6})\n",
    "house_price['HeatingQC'] = house_price.HeatingQC.map({'Po':0,'Fa':1,'TA':2,'Gd':3,'Ex':4})\n",
    "house_price['CentralAir'] = house_price.CentralAir.map({'N':0,'Y':1})\n",
    "house_price['KitchenQual'] = house_price.KitchenQual.map({'Po':0,'Fa':1,'TA':2,'Gd':3,'Ex':4})\n",
    "house_price['GarageFinish'] = house_price.GarageFinish.map({'NA':0,'Unf':1,'RFn':2,'Fin':3})\n",
    "house_price['GarageQual'] = house_price.GarageQual.map({'NA':0,'Po':1,'Fa':2,'TA':3,'Gd':4,'Ex':5})\n",
    "house_price['GarageCond'] = house_price.GarageCond.map({'NA':0,'Po':1,'Fa':2,'TA':3,'Gd':4,'Ex':5})\n",
    "house_price['ExterCond'] = house_price.ExterCond.map({'Po':0,'Fa':1,'TA':2,'Gd':3,'Ex':4})\n",
    "house_price['LotShape'] = house_price.LotShape.map({'IR1':0,'IR2':1,'IR3':2,'Reg':3})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Lets take a look into the converted columns"
   ]
  },
  {
   "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>LandSlope</th>\n",
       "      <th>ExterQual</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>HeatingQC</th>\n",
       "      <th>CentralAir</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "      <th>ExterCond</th>\n",
       "      <th>LotShape</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   LandSlope  ExterQual  BsmtQual  BsmtCond  BsmtExposure  BsmtFinType1  \\\n",
       "0          0          3         4         3             1             6   \n",
       "1          0          2         4         3             4             5   \n",
       "2          0          3         4         3             2             6   \n",
       "3          0          2         3         4             1             5   \n",
       "4          0          3         4         3             3             6   \n",
       "\n",
       "   BsmtFinType2  HeatingQC  CentralAir  KitchenQual  GarageFinish  GarageQual  \\\n",
       "0             1          4           1            3             2           3   \n",
       "1             1          4           1            2             2           3   \n",
       "2             1          4           1            3             2           3   \n",
       "3             1          3           1            3             1           3   \n",
       "4             1          4           1            3             2           3   \n",
       "\n",
       "   GarageCond  ExterCond  LotShape  \n",
       "0           3          2         3  \n",
       "1           3          2         3  \n",
       "2           3          2         0  \n",
       "3           3          2         0  \n",
       "4           3          2         0  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price[['LandSlope','ExterQual','BsmtQual','BsmtCond','BsmtExposure','BsmtFinType1','BsmtFinType2',\n",
    "            'HeatingQC','CentralAir',  'KitchenQual','GarageFinish','GarageQual','GarageCond',\n",
    "             'ExterCond','LotShape']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Creating and joining dummy column with the actual dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "dummy_col = pd.get_dummies(house_price[['MSZoning','LandContour','LotConfig','Neighborhood','Condition1','Condition2','BldgType',\n",
    "             'HouseStyle','RoofStyle','RoofMatl','Exterior1st',  'Exterior2nd','MasVnrType','Foundation',\n",
    "             'Heating','Electrical','Functional','GarageType','PavedDrive','SaleType','SaleCondition']],\n",
    "                           drop_first=True)\n",
    "\n",
    "house_price = pd.concat([house_price,dummy_col],axis='columns')\n",
    "\n",
    "house_price = house_price.drop(['MSZoning','LandContour','LotConfig','Neighborhood','Condition1','Condition2','BldgType',\n",
    "             'HouseStyle','RoofStyle','RoofMatl','Exterior1st',  'Exterior2nd','MasVnrType','Foundation',\n",
    "             'Heating','Electrical','Functional','GarageType','PavedDrive','SaleType','SaleCondition'],axis='columns')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let us check the distribution of our target variable before scaling and Splitting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,6))\n",
    "sns.distplot(house_price.SalePrice)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Creating train and test dataset for validation purpose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train,df_test = train_test_split(house_price,train_size=0.7,test_size=0.3,random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "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",
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       "\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>LandSlope</th>\n",
       "      <th>ExterQual</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>HeatingQC</th>\n",
       "      <th>CentralAir</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "      <th>ExterCond</th>\n",
       "      <th>LotShape</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
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       "      <td>2</td>\n",
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       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   LandSlope  ExterQual  BsmtQual  BsmtCond  BsmtExposure  BsmtFinType1  \\\n",
       "0          0          3         4         3             1             6   \n",
       "1          0          2         4         3             4             5   \n",
       "2          0          3         4         3             2             6   \n",
       "3          0          2         3         4             1             5   \n",
       "4          0          3         4         3             3             6   \n",
       "\n",
       "   BsmtFinType2  HeatingQC  CentralAir  KitchenQual  GarageFinish  GarageQual  \\\n",
       "0             1          4           1            3             2           3   \n",
       "1             1          4           1            2             2           3   \n",
       "2             1          4           1            3             2           3   \n",
       "3             1          3           1            3             1           3   \n",
       "4             1          4           1            3             2           3   \n",
       "\n",
       "   GarageCond  ExterCond  LotShape  \n",
       "0           3          2         3  \n",
       "1           3          2         3  \n",
       "2           3          2         0  \n",
       "3           3          2         0  \n",
       "4           3          2         0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_price[['LandSlope','ExterQual','BsmtQual','BsmtCond','BsmtExposure','BsmtFinType1','BsmtFinType2',\n",
    "            'HeatingQC','CentralAir',  'KitchenQual','GarageFinish','GarageQual','GarageCond',\n",
    "             'ExterCond','LotShape']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Scaling the train dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Note as scale of our dependent valriable SalePrice is very different with the independent variable i am scaling the dependent variable "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_col = ['MSSubClass','LotArea','OverallQual','OverallCond',\n",
    "           'MasVnrArea','BsmtFinSF1',\n",
    "           'BsmtFinSF2','BsmtUnfSF','TotalBsmtSF','1stFlrSF','2ndFlrSF',\n",
    "           'LowQualFinSF','GrLivArea','BsmtFullBath','BsmtHalfBath','FullBath','HalfBath','BedroomAbvGr',\n",
    "           'KitchenAbvGr','TotRmsAbvGrd','Fireplaces','GarageCars',\n",
    "           'GarageArea','WoodDeckSF','OpenPorchSF','EnclosedPorch','3SsnPorch',\n",
    "           'ScreenPorch','PoolArea','MiscVal','SalePrice']\n",
    "\n",
    "scaler = StandardScaler()\n",
    "df_train[num_col] = scaler.fit_transform(df_train[num_col])\n",
    "df_test[num_col] = scaler.transform(df_test[num_col])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Lets check the distribution again after scaling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1d3e59c1ba8>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,6))\n",
    "plt.subplot(121)\n",
    "sns.distplot(df_train.SalePrice)\n",
    "plt.subplot(122)\n",
    "sns.distplot(df_test.SalePrice)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Spliting the dependent and independent variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train = df_train.pop('SalePrice')\n",
    "X_train = df_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test = df_test.pop('SalePrice')\n",
    "X_test = df_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now using  RFE  lets try to to find the optimal number of feature"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Note : I cannot use RFE with GridSearchCV as 192 variable with 5 folds will create 960 fit and it will take more then 1 Hour to get the result so i am using RFE directly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "192"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(X_train.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RFE(estimator=LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n",
       "         normalize=False),\n",
       "  n_features_to_select=70, step=1, verbose=0)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lm  = LinearRegression()\n",
    "lm.fit(X_train,y_train)\n",
    "rfe = RFE(lm,70)\n",
    "rfe.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "rfe_scores = pd.DataFrame(list(zip(X_train.columns,rfe.support_,rfe.ranking_)))\n",
    "rfe_scores.columns = ['Column_Names','Status','Rank']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "rfe_sel_columns = list(rfe_scores[rfe_scores.Status==True].Column_Names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Lets filter the train and test set for the RFE selected columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = X_train[rfe_sel_columns]\n",
    "X_test = X_test[rfe_sel_columns]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lets try first with the Lasso regression model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9022070628442351\n",
      "0.8575605370873767\n"
     ]
    }
   ],
   "source": [
    "lm = Lasso(alpha=0.001)\n",
    "lm.fit(X_train,y_train)\n",
    "\n",
    "y_train_pred = lm.predict(X_train)\n",
    "print(r2_score(y_true=y_train,y_pred=y_train_pred))\n",
    "\n",
    "y_test_pred  = lm.predict(X_test)\n",
    "print(r2_score(y_true=y_test,y_pred=y_test_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('MSSubClass', -1.305),\n",
       " ('LotArea', -0.112),\n",
       " ('LotShape', 0.194),\n",
       " ('LandSlope', 0.142),\n",
       " ('OverallQual', 0.091),\n",
       " ('OverallCond', 0.14),\n",
       " ('MasVnrArea', 0.038),\n",
       " ('ExterQual', -0.0),\n",
       " ('ExterCond', 0.061),\n",
       " ('BsmtQual', 0.0),\n",
       " ('BsmtCond', 0.058),\n",
       " ('BsmtExposure', -0.014),\n",
       " ('BsmtFinType1', 0.324),\n",
       " ('BsmtFinSF1', 0.118),\n",
       " ('BsmtFinType2', 0.091),\n",
       " ('BsmtFinSF2', 0.0),\n",
       " ('BsmtUnfSF', 0.085),\n",
       " ('TotalBsmtSF', -0.082),\n",
       " ('HeatingQC', 0.192),\n",
       " ('CentralAir', 0.0),\n",
       " ('1stFlrSF', 0.108),\n",
       " ('2ndFlrSF', 0.132),\n",
       " ('LowQualFinSF', 0.378),\n",
       " ('GrLivArea', 0.098),\n",
       " ('BsmtFullBath', 0.374),\n",
       " ('BsmtHalfBath', 0.541),\n",
       " ('FullBath', 0.145),\n",
       " ('HalfBath', 0.331),\n",
       " ('BedroomAbvGr', 0.086),\n",
       " ('KitchenAbvGr', 0.05),\n",
       " ('KitchenQual', -0.0),\n",
       " ('TotRmsAbvGrd', 0.0),\n",
       " ('Fireplaces', -1.991),\n",
       " ('GarageFinish', 0.0),\n",
       " ('GarageCars', 0.115),\n",
       " ('GarageArea', -0.0),\n",
       " ('GarageQual', -0.167),\n",
       " ('GarageCond', 0.094),\n",
       " ('WoodDeckSF', 0.0),\n",
       " ('OpenPorchSF', 0.0),\n",
       " ('EnclosedPorch', 0.0),\n",
       " ('3SsnPorch', 0.0),\n",
       " ('ScreenPorch', -0.0),\n",
       " ('PoolArea', -0.237),\n",
       " ('MiscVal', 1.52),\n",
       " ('YearBuilt_Old', -0.0),\n",
       " ('YearRemodAdd_Old', -0.0),\n",
       " ('GarageYrBlt_Old', 0.0),\n",
       " ('YrSold_Old', -0.171),\n",
       " ('MSZoning_FV', -0.0),\n",
       " ('MSZoning_RH', -0.0),\n",
       " ('MSZoning_RL', -0.0),\n",
       " ('MSZoning_RM', -0.0),\n",
       " ('LandContour_HLS', 0.128),\n",
       " ('LandContour_Low', 0.003),\n",
       " ('LandContour_Lvl', 0.08),\n",
       " ('LotConfig_CulDSac', 0.092),\n",
       " ('LotConfig_FR2', -0.0),\n",
       " ('LotConfig_FR3', 0.0),\n",
       " ('LotConfig_Inside', 0.0),\n",
       " ('Neighborhood_Blueste', -0.0),\n",
       " ('Neighborhood_BrDale', -0.0),\n",
       " ('Neighborhood_BrkSide', 0.16),\n",
       " ('Neighborhood_ClearCr', 0.033),\n",
       " ('Neighborhood_CollgCr', -0.0),\n",
       " ('Neighborhood_Crawfor', 0.006),\n",
       " ('Neighborhood_Edwards', -0.0),\n",
       " ('Neighborhood_Gilbert', 0.283),\n",
       " ('Neighborhood_IDOTRR', 0.0),\n",
       " ('Neighborhood_MeadowV', 0.074),\n",
       " ('Neighborhood_Mitchel', 0.0)]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_parameter = list(lm.coef_)\n",
    "model_parameter.insert(0,lm.intercept_)\n",
    "model_parameter = [round(x,3) for x in model_parameter]\n",
    "col = df_train.columns\n",
    "col.insert(0,'Constant')\n",
    "list(zip(col,model_parameter))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now lets try to improve our model with the optimal value of alpha using GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 10 folds for each of 7 candidates, totalling 70 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n",
      "[Parallel(n_jobs=1)]: Done  70 out of  70 | elapsed:    1.2s finished\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=KFold(n_splits=10, random_state=42, shuffle=True),\n",
       "       error_score='raise-deprecating',\n",
       "       estimator=Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,\n",
       "   normalize=False, positive=False, precompute=False, random_state=None,\n",
       "   selection='cyclic', tol=0.0001, warm_start=False),\n",
       "       fit_params=None, iid='warn', n_jobs=None,\n",
       "       param_grid={'alpha': [0.001, 0.01, 0.1, 1.0, 5.0, 10.0, 20.0]},\n",
       "       pre_dispatch='2*n_jobs', refit=True, return_train_score=True,\n",
       "       scoring='r2', verbose=1)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "folds = KFold(n_splits=10,shuffle=True,random_state=42)\n",
    "\n",
    "hyper_param = {'alpha':[0.001, 0.01, 0.1,1.0, 5.0, 10.0,20.0]}\n",
    "\n",
    "model = Lasso()\n",
    "\n",
    "model_cv = GridSearchCV(estimator = model,\n",
    "                        param_grid=hyper_param,\n",
    "                        scoring='r2',\n",
    "                        cv=folds,\n",
    "                        verbose=1,\n",
    "                        return_train_score=True\n",
    "                       )\n",
    "\n",
    "model_cv.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>mean_fit_time</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>param_alpha</th>\n",
       "      <th>params</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>split2_test_score</th>\n",
       "      <th>split3_test_score</th>\n",
       "      <th>...</th>\n",
       "      <th>split2_train_score</th>\n",
       "      <th>split3_train_score</th>\n",
       "      <th>split4_train_score</th>\n",
       "      <th>split5_train_score</th>\n",
       "      <th>split6_train_score</th>\n",
       "      <th>split7_train_score</th>\n",
       "      <th>split8_train_score</th>\n",
       "      <th>split9_train_score</th>\n",
       "      <th>mean_train_score</th>\n",
       "      <th>std_train_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.042187</td>\n",
       "      <td>0.004907</td>\n",
       "      <td>0.002692</td>\n",
       "      <td>0.000780</td>\n",
       "      <td>0.001</td>\n",
       "      <td>{'alpha': 0.001}</td>\n",
       "      <td>0.858411</td>\n",
       "      <td>0.919698</td>\n",
       "      <td>0.823289</td>\n",
       "      <td>0.884340</td>\n",
       "      <td>...</td>\n",
       "      <td>0.909394</td>\n",
       "      <td>0.903553</td>\n",
       "      <td>0.900062</td>\n",
       "      <td>0.903985</td>\n",
       "      <td>0.898896</td>\n",
       "      <td>0.914493</td>\n",
       "      <td>0.902321</td>\n",
       "      <td>0.900008</td>\n",
       "      <td>0.903734</td>\n",
       "      <td>0.004663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.011370</td>\n",
       "      <td>0.003546</td>\n",
       "      <td>0.002194</td>\n",
       "      <td>0.000598</td>\n",
       "      <td>0.010</td>\n",
       "      <td>{'alpha': 0.01}</td>\n",
       "      <td>0.823570</td>\n",
       "      <td>0.882420</td>\n",
       "      <td>0.833992</td>\n",
       "      <td>0.851971</td>\n",
       "      <td>...</td>\n",
       "      <td>0.858367</td>\n",
       "      <td>0.854028</td>\n",
       "      <td>0.850813</td>\n",
       "      <td>0.852697</td>\n",
       "      <td>0.849232</td>\n",
       "      <td>0.880529</td>\n",
       "      <td>0.853551</td>\n",
       "      <td>0.849515</td>\n",
       "      <td>0.855800</td>\n",
       "      <td>0.008767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.007282</td>\n",
       "      <td>0.000898</td>\n",
       "      <td>0.001994</td>\n",
       "      <td>0.000446</td>\n",
       "      <td>0.100</td>\n",
       "      <td>{'alpha': 0.1}</td>\n",
       "      <td>0.734416</td>\n",
       "      <td>0.819997</td>\n",
       "      <td>0.769757</td>\n",
       "      <td>0.762736</td>\n",
       "      <td>...</td>\n",
       "      <td>0.789923</td>\n",
       "      <td>0.794550</td>\n",
       "      <td>0.790287</td>\n",
       "      <td>0.794322</td>\n",
       "      <td>0.783940</td>\n",
       "      <td>0.823288</td>\n",
       "      <td>0.791661</td>\n",
       "      <td>0.788672</td>\n",
       "      <td>0.794309</td>\n",
       "      <td>0.010282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.006484</td>\n",
       "      <td>0.000668</td>\n",
       "      <td>0.001993</td>\n",
       "      <td>0.000446</td>\n",
       "      <td>1.000</td>\n",
       "      <td>{'alpha': 1.0}</td>\n",
       "      <td>-0.006496</td>\n",
       "      <td>-0.021566</td>\n",
       "      <td>-0.018063</td>\n",
       "      <td>-0.001154</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.006084</td>\n",
       "      <td>0.000537</td>\n",
       "      <td>0.002094</td>\n",
       "      <td>0.000299</td>\n",
       "      <td>5.000</td>\n",
       "      <td>{'alpha': 5.0}</td>\n",
       "      <td>-0.006496</td>\n",
       "      <td>-0.021566</td>\n",
       "      <td>-0.018063</td>\n",
       "      <td>-0.001154</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_fit_time  std_fit_time  mean_score_time  std_score_time  param_alpha  \\\n",
       "0       0.042187      0.004907         0.002692        0.000780        0.001   \n",
       "1       0.011370      0.003546         0.002194        0.000598        0.010   \n",
       "2       0.007282      0.000898         0.001994        0.000446        0.100   \n",
       "3       0.006484      0.000668         0.001993        0.000446        1.000   \n",
       "4       0.006084      0.000537         0.002094        0.000299        5.000   \n",
       "\n",
       "             params  split0_test_score  split1_test_score  split2_test_score  \\\n",
       "0  {'alpha': 0.001}           0.858411           0.919698           0.823289   \n",
       "1   {'alpha': 0.01}           0.823570           0.882420           0.833992   \n",
       "2    {'alpha': 0.1}           0.734416           0.819997           0.769757   \n",
       "3    {'alpha': 1.0}          -0.006496          -0.021566          -0.018063   \n",
       "4    {'alpha': 5.0}          -0.006496          -0.021566          -0.018063   \n",
       "\n",
       "   split3_test_score       ...         split2_train_score  split3_train_score  \\\n",
       "0           0.884340       ...                   0.909394            0.903553   \n",
       "1           0.851971       ...                   0.858367            0.854028   \n",
       "2           0.762736       ...                   0.789923            0.794550   \n",
       "3          -0.001154       ...                   0.000000            0.000000   \n",
       "4          -0.001154       ...                   0.000000            0.000000   \n",
       "\n",
       "   split4_train_score  split5_train_score  split6_train_score  \\\n",
       "0            0.900062            0.903985            0.898896   \n",
       "1            0.850813            0.852697            0.849232   \n",
       "2            0.790287            0.794322            0.783940   \n",
       "3            0.000000            0.000000            0.000000   \n",
       "4            0.000000            0.000000            0.000000   \n",
       "\n",
       "   split7_train_score  split8_train_score  split9_train_score  \\\n",
       "0            0.914493            0.902321            0.900008   \n",
       "1            0.880529            0.853551            0.849515   \n",
       "2            0.823288            0.791661            0.788672   \n",
       "3            0.000000            0.000000            0.000000   \n",
       "4            0.000000            0.000000            0.000000   \n",
       "\n",
       "   mean_train_score  std_train_score  \n",
       "0          0.903734         0.004663  \n",
       "1          0.855800         0.008767  \n",
       "2          0.794309         0.010282  \n",
       "3          0.000000         0.000000  \n",
       "4          0.000000         0.000000  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv_result_l = pd.DataFrame(model_cv.cv_results_)\n",
    "cv_result_l['param_alpha'] = cv_result_l['param_alpha'].astype('float32')\n",
    "cv_result_l.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "plt.plot(cv_result_l['param_alpha'],cv_result_l['mean_train_score'])\n",
    "plt.plot(cv_result_l['param_alpha'],cv_result_l['mean_test_score'])\n",
    "plt.xscale('log')\n",
    "plt.ylabel('R2 Score')\n",
    "plt.xlabel('Alpha')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'alpha': 0.001}"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the best parameter(Alpha value)\n",
    "model_cv.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9022070628442351\n",
      "0.8575605370873767\n"
     ]
    }
   ],
   "source": [
    "lasso = Lasso(alpha=0.001)\n",
    "lasso.fit(X_train,y_train)\n",
    "\n",
    "y_train_pred = lasso.predict(X_train)\n",
    "y_test_pred = lasso.predict(X_test)\n",
    "\n",
    "print(r2_score(y_true=y_train,y_pred=y_train_pred))\n",
    "print(r2_score(y_true=y_test,y_pred=y_test_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_param = list(lasso.coef_)\n",
    "model_param.insert(0,lasso.intercept_)\n",
    "cols = df_train.columns\n",
    "cols.insert(0,'const')\n",
    "lasso_coef = pd.DataFrame(list(zip(cols,model_param)))\n",
    "lasso_coef.columns = ['Featuere','Coef']"
   ]
  },
  {
   "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>Featuere</th>\n",
       "      <th>Coef</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>MiscVal</td>\n",
       "      <td>1.520128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>BsmtHalfBath</td>\n",
       "      <td>0.541487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>LowQualFinSF</td>\n",
       "      <td>0.378263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>BsmtFullBath</td>\n",
       "      <td>0.373994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>HalfBath</td>\n",
       "      <td>0.331081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>BsmtFinType1</td>\n",
       "      <td>0.324486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Neighborhood_Gilbert</td>\n",
       "      <td>0.282619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LotShape</td>\n",
       "      <td>0.194391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>HeatingQC</td>\n",
       "      <td>0.192283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Neighborhood_BrkSide</td>\n",
       "      <td>0.160200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Featuere      Coef\n",
       "44               MiscVal  1.520128\n",
       "25          BsmtHalfBath  0.541487\n",
       "22          LowQualFinSF  0.378263\n",
       "24          BsmtFullBath  0.373994\n",
       "27              HalfBath  0.331081\n",
       "12          BsmtFinType1  0.324486\n",
       "67  Neighborhood_Gilbert  0.282619\n",
       "2               LotShape  0.194391\n",
       "18             HeatingQC  0.192283\n",
       "62  Neighborhood_BrkSide  0.160200"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lasso_coef.sort_values(by='Coef',ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Now lets use the ridge regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9078417854243198\n",
      "0.8431546903792685\n"
     ]
    }
   ],
   "source": [
    "ridge = Ridge(alpha=0.001)\n",
    "ridge.fit(X_train,y_train)\n",
    "\n",
    "y_train_pred = ridge.predict(X_train)\n",
    "print(r2_score(y_train,y_train_pred))\n",
    "y_test_pred = ridge.predict(X_test)\n",
    "print(r2_score(y_test,y_test_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### As we can see the above alpha value is not optimal for ridge there are sign of overfitting the clear difference we can see in the train and test score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now lets try to improve our model with the optimal value of alpha using GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 10 folds for each of 10 candidates, totalling 100 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n",
      "[Parallel(n_jobs=1)]: Done 100 out of 100 | elapsed:    0.8s finished\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=KFold(n_splits=10, random_state=42, shuffle=True),\n",
       "       error_score='raise-deprecating',\n",
       "       estimator=Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,\n",
       "   normalize=False, random_state=None, solver='auto', tol=0.001),\n",
       "       fit_params=None, iid='warn', n_jobs=None,\n",
       "       param_grid={'alpha': [0.001, 0.01, 0.1, 0.2, 0.5, 0.9, 1.0, 5.0, 10.0, 20.0]},\n",
       "       pre_dispatch='2*n_jobs', refit=True, return_train_score=True,\n",
       "       scoring='r2', verbose=1)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "folds  = KFold(n_splits=10,shuffle=True,random_state=42)\n",
    "\n",
    "hyper_param = {'alpha':[0.001,0.01,0.1,0.2,0.5,0.9,1.0, 5.0, 10.0,20.0]}\n",
    "\n",
    "model = Ridge()\n",
    "\n",
    "model_cv = GridSearchCV(estimator=model,\n",
    "                        param_grid=hyper_param,\n",
    "                        scoring='r2',\n",
    "                        cv=folds,\n",
    "                        verbose=1,\n",
    "                        return_train_score=True)\n",
    "\n",
    "model_cv.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>mean_fit_time</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>param_alpha</th>\n",
       "      <th>params</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>split2_test_score</th>\n",
       "      <th>split3_test_score</th>\n",
       "      <th>...</th>\n",
       "      <th>split2_train_score</th>\n",
       "      <th>split3_train_score</th>\n",
       "      <th>split4_train_score</th>\n",
       "      <th>split5_train_score</th>\n",
       "      <th>split6_train_score</th>\n",
       "      <th>split7_train_score</th>\n",
       "      <th>split8_train_score</th>\n",
       "      <th>split9_train_score</th>\n",
       "      <th>mean_train_score</th>\n",
       "      <th>std_train_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.006782</td>\n",
       "      <td>0.001984</td>\n",
       "      <td>0.001893</td>\n",
       "      <td>0.000536</td>\n",
       "      <td>0.001</td>\n",
       "      <td>{'alpha': 0.001}</td>\n",
       "      <td>0.857227</td>\n",
       "      <td>0.921110</td>\n",
       "      <td>0.784247</td>\n",
       "      <td>0.888754</td>\n",
       "      <td>...</td>\n",
       "      <td>0.916101</td>\n",
       "      <td>0.909313</td>\n",
       "      <td>0.905491</td>\n",
       "      <td>0.909927</td>\n",
       "      <td>0.904539</td>\n",
       "      <td>0.919577</td>\n",
       "      <td>0.907990</td>\n",
       "      <td>0.905931</td>\n",
       "      <td>0.909453</td>\n",
       "      <td>0.004661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.005286</td>\n",
       "      <td>0.001002</td>\n",
       "      <td>0.001695</td>\n",
       "      <td>0.000457</td>\n",
       "      <td>0.010</td>\n",
       "      <td>{'alpha': 0.01}</td>\n",
       "      <td>0.857575</td>\n",
       "      <td>0.921076</td>\n",
       "      <td>0.787061</td>\n",
       "      <td>0.888717</td>\n",
       "      <td>...</td>\n",
       "      <td>0.916096</td>\n",
       "      <td>0.909311</td>\n",
       "      <td>0.905490</td>\n",
       "      <td>0.909925</td>\n",
       "      <td>0.904538</td>\n",
       "      <td>0.919576</td>\n",
       "      <td>0.907988</td>\n",
       "      <td>0.905930</td>\n",
       "      <td>0.909451</td>\n",
       "      <td>0.004660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.005483</td>\n",
       "      <td>0.001279</td>\n",
       "      <td>0.001796</td>\n",
       "      <td>0.000870</td>\n",
       "      <td>0.100</td>\n",
       "      <td>{'alpha': 0.1}</td>\n",
       "      <td>0.860001</td>\n",
       "      <td>0.920751</td>\n",
       "      <td>0.809467</td>\n",
       "      <td>0.888356</td>\n",
       "      <td>...</td>\n",
       "      <td>0.915691</td>\n",
       "      <td>0.909194</td>\n",
       "      <td>0.905370</td>\n",
       "      <td>0.909782</td>\n",
       "      <td>0.904416</td>\n",
       "      <td>0.919531</td>\n",
       "      <td>0.907858</td>\n",
       "      <td>0.905810</td>\n",
       "      <td>0.909308</td>\n",
       "      <td>0.004637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.005386</td>\n",
       "      <td>0.000799</td>\n",
       "      <td>0.001695</td>\n",
       "      <td>0.000639</td>\n",
       "      <td>0.200</td>\n",
       "      <td>{'alpha': 0.2}</td>\n",
       "      <td>0.861470</td>\n",
       "      <td>0.920400</td>\n",
       "      <td>0.826262</td>\n",
       "      <td>0.887979</td>\n",
       "      <td>...</td>\n",
       "      <td>0.914888</td>\n",
       "      <td>0.908941</td>\n",
       "      <td>0.905113</td>\n",
       "      <td>0.909515</td>\n",
       "      <td>0.904155</td>\n",
       "      <td>0.919430</td>\n",
       "      <td>0.907577</td>\n",
       "      <td>0.905550</td>\n",
       "      <td>0.909009</td>\n",
       "      <td>0.004601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.005187</td>\n",
       "      <td>0.000870</td>\n",
       "      <td>0.001694</td>\n",
       "      <td>0.000457</td>\n",
       "      <td>0.500</td>\n",
       "      <td>{'alpha': 0.5}</td>\n",
       "      <td>0.863293</td>\n",
       "      <td>0.919315</td>\n",
       "      <td>0.853065</td>\n",
       "      <td>0.886984</td>\n",
       "      <td>...</td>\n",
       "      <td>0.912117</td>\n",
       "      <td>0.907923</td>\n",
       "      <td>0.904085</td>\n",
       "      <td>0.908512</td>\n",
       "      <td>0.903113</td>\n",
       "      <td>0.918988</td>\n",
       "      <td>0.906440</td>\n",
       "      <td>0.904497</td>\n",
       "      <td>0.907857</td>\n",
       "      <td>0.004556</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_fit_time  std_fit_time  mean_score_time  std_score_time  param_alpha  \\\n",
       "0       0.006782      0.001984         0.001893        0.000536        0.001   \n",
       "1       0.005286      0.001002         0.001695        0.000457        0.010   \n",
       "2       0.005483      0.001279         0.001796        0.000870        0.100   \n",
       "3       0.005386      0.000799         0.001695        0.000639        0.200   \n",
       "4       0.005187      0.000870         0.001694        0.000457        0.500   \n",
       "\n",
       "             params  split0_test_score  split1_test_score  split2_test_score  \\\n",
       "0  {'alpha': 0.001}           0.857227           0.921110           0.784247   \n",
       "1   {'alpha': 0.01}           0.857575           0.921076           0.787061   \n",
       "2    {'alpha': 0.1}           0.860001           0.920751           0.809467   \n",
       "3    {'alpha': 0.2}           0.861470           0.920400           0.826262   \n",
       "4    {'alpha': 0.5}           0.863293           0.919315           0.853065   \n",
       "\n",
       "   split3_test_score       ...         split2_train_score  split3_train_score  \\\n",
       "0           0.888754       ...                   0.916101            0.909313   \n",
       "1           0.888717       ...                   0.916096            0.909311   \n",
       "2           0.888356       ...                   0.915691            0.909194   \n",
       "3           0.887979       ...                   0.914888            0.908941   \n",
       "4           0.886984       ...                   0.912117            0.907923   \n",
       "\n",
       "   split4_train_score  split5_train_score  split6_train_score  \\\n",
       "0            0.905491            0.909927            0.904539   \n",
       "1            0.905490            0.909925            0.904538   \n",
       "2            0.905370            0.909782            0.904416   \n",
       "3            0.905113            0.909515            0.904155   \n",
       "4            0.904085            0.908512            0.903113   \n",
       "\n",
       "   split7_train_score  split8_train_score  split9_train_score  \\\n",
       "0            0.919577            0.907990            0.905931   \n",
       "1            0.919576            0.907988            0.905930   \n",
       "2            0.919531            0.907858            0.905810   \n",
       "3            0.919430            0.907577            0.905550   \n",
       "4            0.918988            0.906440            0.904497   \n",
       "\n",
       "   mean_train_score  std_train_score  \n",
       "0          0.909453         0.004661  \n",
       "1          0.909451         0.004660  \n",
       "2          0.909308         0.004637  \n",
       "3          0.909009         0.004601  \n",
       "4          0.907857         0.004556  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv_result_r = pd.DataFrame(model_cv.cv_results_)\n",
    "cv_result_r['param_alpha'] = cv_result_r['param_alpha'].astype('float32')\n",
    "cv_result_r.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dStKhXQNcH2N8etA9VcDuGGNvCOEfgJ4Y4/9MDZ5aByxO3bqeZPDU7mN9PwdPaazZ1nGQb69u4TuPb2H3/k7mVJdy0/IGrl5cy4TCdP7+SZIkSRp7RsU5uSGEdwL/DOQC34wx/kMI4dPA2hjjPSGE9wOfIVmK/CjwkRjj4dRnfw/4q9SX+ocY47eO970MuRqrDnX1cN+T21mxspkn2vYwoTCP9y+p5YameuZUT8h0eZIkSdKoMCpC7kgy5CobbNzSwYqVzdy7aRtdPZEL5lZxU1MDl5wxhdwclzJLkiRp/DLkSmPYzn2HuevxVu5Y3cKOvYeZOamYG86r55rGmVSUFGS6PEmSJGnEGXKlLNDV08uDT+9gxapmHn95N0X5ObxnYQ03LW9g/vTyTJcnSZIkjRhDrpRlntm2l9sfa+aHG7ZyqKuXpQ2TuGl5A5efOZX83HSeBiZJkiRlniFXylIdBzr53to2bnusmS27DzKtvIgPLqvj2qV1VJcVZro8SZIkKS0MuVKW6+mNPPLcq9y6splfvLCLgtwc3nX2dG5sqmdRXWWmy5MkSZJOqeGGXA/jlMao3JzApfOncun8qby083VuX9XC99e18cMNWzmndiI3NjXwrrOnU5Sfm+lSJUmSpBFjJ1fKIq8f7uYH69tYsbKZl3buZ3JpAdcunckHl9Uzo6I40+VJkiRJb5jLlaVxLMbIr158jRWrmnno2R2EELh8wVRuWt7AslmTCMEzdyVJkjS2uFxZGsdCCJw/t4rz51axZfcB7ljdwt1rtnD/U69wxrQybmxq4D2LZlBS4F8BkiRJyi52cqVx4lBXD/ds3MatK5t5ZvteyovyuKZxJjc01VM/uTTT5UmSJEnH5XJlSUOKMbKupZ0Vq1q4/8nt9MTIJfOmcGNTPRfOrSYnx6XMkiRJGn0MuZJOaMfeQ9y5upU7H29l577DzKoq5Ybz6nl/Yy3lRfmZLk+SJEnqZ8iVNGyd3b3c/9R2VqxsZn1rByUFuVy9uIYbmxo4fWpZpsuTJEmSDLmS3pgn2/awYlUz9zyxjc7uXpbPmcyNTQ1cNn8Kebk5mS5PkiRJ45QhV9Kbsnt/J3etaeWOVS1s23OImopiPnheHdeeW8ek0oJMlydJkqRxxpAr6ZTo7unloV+/yoqVzax86TUK8nK48pwZ3Ly8gbNqJma6PEmSJI0ThlxJp9wLO/axYlUzP1i/lQOdPSyuq+Cm5Q2846zpFOS5lFmSJEnpY8iVlDZ7D3Xx/bVt3P5YCy/v2k91WSHXL63j+mV1TC0vynR5kiRJykKGXElp19sbefSFndy2qoWHn3uV3BC44qxp3Ly8gSX1lYTgmbuSJEk6NYYbcvNGohhJ2SknJ3DxvClcPG8Kzbv2c8djLdy9dgv3btrOgunl3Ly8gSsXzqAoPzfTpUqSJGmcsJMr6ZQ60NnNf2zYxoqVzTy3Yx8VJfl84NyZ/O6yemZOKsl0eZIkSRqjXK4sKaNijKx+eTe3rWrmgad3EGPk0vlTuampgbeeNtmlzJIkSTopLleWlFEhBM6bPZnzZk9mW8dB7lzdynceb+Unz+xgTnUpNy1v4OrFtUwo9K8hSZIknTp2ciWNmENdPdz35HZWrGzmibY9TCjM4/1LarmhqZ451RMyXZ4kSZJGMZcrSxrVNm7pYMXKZu7dtI2unsgFc6u4qamBS86YQm6OS5klSZJ0JEOupDFh577D3PV4K3esbmHH3sPMnFTMu8+ewZK6ShbVVTB5QmGmS5QkSdIoYMiVNKZ09fTy4NM7uP2xZtY2t9Pdm/zd1DC5hMV1lSyqr2RxXQXzppaRl5uT4WolSZI00gy5ksasg509PLl1D+tb21nf0s761nZ2vd4JQElBLufUVrC4voIl9ZUsmllJZWlBhiuWJElSujldWdKYVVyQy9JZk1g6axKQHEe0ZffBJPSmHv/28830pLq9s6tKWVRXyeL6ChbXVXL61DL39UqSJI1TdnIljUkHOrvZ1NbX7e1gQ2s7r+1Pur0TCvM4Z+ZEFtdVJkud6yqoKLHbK0mSNJbZyZWU1UoK8vrP4YWk29u6+wDrUsub17d08OWHXyTV7GVOdWkSeuuT4Dt3ygRy7PZKkiRlHTu5krLW/sPdPNHWwYbWjv69ve0HugAoK8xjYV1Fssw59efE4vwMVyxJkqRjsZMradwrLcxj+Zwqls+pApJub/NrB/oD7/rWDr70sxf6u72nTZnA4rpkX++S+krmVNvtlSRJGmvs5Eoa114/3M2mLR2sb21nXUs7G7Z00JHq9pYX5bEw1eldXFfJwroKyovs9kqSJGWCnVxJGoYJhXksP62K5acNdHs379qf6vYmA62++NALxAghwNwpE/oHWi2ur2B2ld1eSZKk0cROriSdwL5DXTyxZU//8UUbWjvYczDp9k4szmdRqtO7uK6Sc2ZOpMxuryRJ0ilnJ1eSTpGyonzOn1vF+XOTbm9vb2TzrtdZ39LRH3x//vzO/m7vvKll/QOtFtdXMruqlBDs9kqSJI0EO7mSdArsPdTFxtaO/oFWG1rb2XeoG4CKknwWzazoP8LonJkVTCj0d4ySJEknw06uJI2g8qJ8Ljy9mgtPrwaSbu9LO1/vH2i1vrWDh5/bCUBOgHnTyvsHWi2ur6RhcondXkmSpFPATq4kjZA9B7rYsGWg07uxtYN9h5Nu76TSgqTbW1/JoroKzqmtoNRuryRJUj87uZI0ykwsyefieVO4eN4UAHp6Iy++mnR7+87ufejXrwKQmxOYN7WMJfXJFOfFdZXUTbLbK0mSdCJ2ciVpFOk40MmG1oGBVhtbO9jf2QPA5NKCZKBVKvSeU1tBcUFuhiuWJEkaGXZyJWkMqigp4JIzpnDJGQPd3ud37Et1e5Nlzj99dgeQdHvnTy8bOLe3rpKZk4rt9kqSpHHNTq4kjTHt+zuTvb0tHaxraeeJtg4OpLq9VRMK+48uWlxXydm1EynKt9srSZLGPju5kpSlKksLeNsZU3nbGVMB6O7p5bkd+5KBVqm9vQ8+k3R783ICC2aUs7guGWi1uK6S2kq7vZIkKXvZyZWkLPTa64eP2Nv7xJY9HOxKur3VZYVHHF/0lhq7vZIkafSzkytJ49jkCYVctmAqly0Y6Pb++pV9gyY5d/DA00m3Nz83sGDGxCOC74yJRXZ7JUnSmGQnV5LGqZ37DrOhNQm861vb2dTWwaGuXgCmlhcODLSqr+DMGXZ7JUlSZtnJlSQdV3VZIZefOY3Lz5wGQFdPL7/evq9/ifO6lnbuf+oVAApyc/r39vad3Tt9YnEmy5ckSRqSnVxJ0jG9uu9Q/9FFSbd3D4e7k27v9IlFAwOt6is5c0Y5hXl2eyVJUnrYyZUkvWlTyoq44qxpXHFW0u3t7O7l2e17U93eDta3tPPjJ7cDUJCXw1mpbm/fEUbTJhZlsnxJkjQO2cmVJL0pO/YeYkNqefP61g6e3LqHzlS3d8bEov7Au7i+kgXTyynIy8lwxZIkaSwabifXkCtJOqU6u3t5etue/oFWG1ra2bbnEACFeTm8pWZiKvgm05ynlNvtlSRJJ2bIlSSNGq/sOTTo+KJ2ntq6l86epNtbU1HcH3qX1Fcyf3o5+bl2eyVJ0pFGRcgNIVwBfBHIBb4RY/zsUdfrgBVAReqeT8YY7wshFABfBRqBXuBPYoyPHO97GXIlaew43N3DU1v39g+0Wt/SwSt7k25vUX4OZ9dUsKi+ov8Yo+qywgxXLEmSMi3jITeEkAs8D7wdaAPWANfFGJ8ZdM/XgA0xxq+EEBYA98UYG0IIHwEaY4wfCiFMAe4Hzo0x9h7r+xlyJWls29ZxsD/wrm9t5+lte+jqSf4dNXNS8cC5vXWVnDG9zG6vJEnjzGiYrrwUeDHGuDlV0F3AVcAzg+6JQHnq+URgW+r5AuAhgBjjqyGEDpKu7uNprFeSlEEzKoqZUVHMu8+eAcChrp5kb29LB+ta2ln10mv8aGPyr4ni/FzeUjsxObO3LlnqPHmC3V5JkpTekFsDbBn0ug1YdtQ9fwc8GEL4GFAKXJZ6/wngqlQwngksSf15RMgNIdwC3AJQV1d3isuXJGVSUX4uS+onsaR+En8AxBjZ2nGw/+iiDa3tfP3RzXT3Jt3e+skl/YF3UV0lZ0wrI89uryRJ4046Q24Y4r2j10ZfB9waY/x8CKEJuD2EcBbwTWA+sBZoAVYC3b/xxWL8GvA1SJYrn8LaJUmjTAiB2soSaitLuPKcgW7vk1v39A+0+uWLu/jhhq0AlBTkcnbtxIFlzvWVTCotyOSPIEmSRkA6Q24bSfe1Ty0Dy5H7fBi4AiDGuCqEUARUxRhfBT7ed1MIYSXwQhprlSSNQUX5uZzbMIlzGyYBSbe3rf3goEnOHXz10c30pLq9s6pKWVQ3MNBq3rQycnOG+p2sJEkaq9IZctcAc0MIs4CtwLXA9Ufd0wpcCtwaQpgPFAE7QwglJEOx9ocQ3g50Dx5YJUnSUEIIzJxUwsxJJVy1sAaAg509bGrr6D+399Hnd/KD9Um3t7Qgl3NmpkJvfQWLZlZSabdXkqQxLW0hN8bYHUL4KPAAyfFA34wxPh1C+DSwNsZ4D/AJ4OshhI+TLGW+OcYYUxOVHwgh9JIE5BvSVackKbsVF+SybPZkls2eDCTd3i27U93e1nbWtbTzlZ+/1N/tnV1VyqK6ymSoVX0Fc6fY7ZUkaSxJ6zm5I8kjhCRJb9SBzm6e2LKH9a3tqbN7O9i9vxOACYV5LJxZkQy0qq9k8cxKJpbkZ7hiSZLGn9FwhJAkSWNCSUEeTXMm0zRnoNvb8tqB/m7v+pYOvvTwi6SavcypLu0fZrW4rpK5UyaQY7dXkqRRwU6uJEnDsP9wN09s6UgF3w42tLbTfqALgLKivm5vEnwXzqxgYrHdXkmSTiU7uZIknUKlhXksP62K5adVAUm39+Vd+/sHWq1vaedffvYCvRFCgNOqJ/QPtFpcV8mcaru9kiSNBDu5kiSdIq/3dXtT5/aub+1gz8Gk21telMfCukoW11WwJNXtLSuy2ytJ0nDZyZUkaYRNKMzjradV8dZUt7e3N7J51/6BgVYtHXzxoReIqW7v6VPKkqOLUuf2zq4qtdsrSdKbZCdXkqQRtPdQV6rb29Effvce6gZgYnE+i+pSe3vrKjln5kS7vZIkpdjJlSRpFCovyueCudVcMLca6Ov2vs66lvb+4PvIczuBpNs7b2pZ/xTnxXUVzKoqJQS7vZIkHYudXEmSRpk9B7vYOGhv78bWDvYdTrq9lSX5qeXNFcydWkZtZTG1FSWUF+cZfiVJWc1OriRJY9TE4nwuOr2ai04f6Pa+uPP1IwZa/ezXrx7xmQmFedRWFlNTUUxNZXHqeUn/88mlBYZgSdK4YMiVJGmUy8kJnD61jNOnlnHt0jog6fa2vLafre0H2dpxkLb25LG14yCPN+9mX2qfb5+i/BxmVBRTW1lCTUUSfAeH4illReQ69EqSlAUMuZIkjUETi/M5u7aCs2srhry+91AXW/uCb/uB/gC8teMgT23dw+79nUfcn58bmD6xuD8A11T2PS+htrKYaROLyM/NGYkfTZKkN8WQK0lSFiovyqd8ej7zp5cPef1AZzfbOg6ypf3gEd3gre0HePSFnezYe/iI+3MCTCsvOiL8DjwvZkZFMUX5uSPxo0mSdFyGXEmSxqGSgjxOm1LGaVPKhrx+uLuH7R2HUuH3QNIVTgXhNc3t/Oem7fT0Hjm8srqs8Ig9wbX9z5Ml0qWF/t8OSVL6+W8bSZL0GwrzcmmoKqWhqnTI6909vbyy99BRXeDk+dNb9/CTp3fQ2dN7xGcqSvIH9gFXlByxLHpmpROiJUmnhiFXkiSdtLzcnNR+3ZIhr/f2Rna9fjhZDt1xMLU/+ABbOw6yeed+Hn1+Fwe7eo74zITCvCH3BPc9r5rghGhJ0okZciVJ0imXkxOYUl7ElPIiltRX/sb1GCPtB7qOCL/DnRA9eCDW4FDshGhJEhhyJUlSBoQQmFRawKTSAt5SO3HIe46eEN2/LLrjIM9se4XXjjMhumbQEUlOiJak8cWQK0mSRqXhToge3AHu6wz/4oWdvLrvMHHQbCwnREvS+GD/MyIbAAAgAElEQVTIlSRJY9LJTIjuC79tqefHmhBdNaGwf/lz7RH7g5NAPMEJ0ZI06vk3tSRJykrDmRC9Y99h2nYfGBSE+5ZD7z3mhOj+fcCp4Dt4b/DE4nyHY0lShhlyJUnSuJSXm5M6zqh4yOtvZkL04PA7+KxgJ0RLUvoZciVJkobwZidEr23ezd6jJkQX5uUcsSfYCdGSdOoZciVJkt6Ak5kQPTgI94XhoSZE5+WE/mOSju4Gz6wscUK0JA2DIVeSJClNTmZCdP8RSannx5oQPbW8aMil0H0dYidESxrvDLmSJEkZMpwJ0a/sOdQffts6Uh3hE0yI7usC1x7REXZCtKTxwb/lJEmSRqnCvFzqJ5dSP/nUT4ge6qxgJ0RLygaGXEmSpDFquBOi245YCn2AtvaDvLxrP798cRcHOo+cEF1akNsffp0QLWksMuRKkiRlqcETohfXHX9CdF/4Hbw/+MQToo/cE1zrhGhJo4AhV5IkaZw62QnRWzsGTYluP8iD2/YOOSF6ekURtRVHLoWuqSymtqKE6RVOiJaUXoZcSZIkHdOJJkQf7Ow5IvwOd0L04PBbU1Ey6LkToiW9OYZcSZIkvWHFBbmcNmUCp02ZMOT1zu5etu85OOSE6LUtJ5gQfUQQHhiU5YRoScfj3xCSJElKm4K8nGFNiE4mQx8YtCz6IM9s38tPnt1BZ7cToiUNnyFXkiRJGTN4QvTSWZN+4/rgCdEDRyQlYXg4E6JrhugGOyFaym6GXEmSJI1aw5kQ3XGgqz/8Dp4QvfV4E6IHTYQe3BF2QrQ09hlyJUmSNGaFEKgsLaDyOBOi9x3qSpZA73ZCtDQeGHIlSZKU1cqK8jljWj5nTBvehOitg7rBv3xhFzv2HXJCtDSGGHIlSZI0rg13QnRf+B3YH3zACdHSKOQ/XZIkSdJxnMyE6K0dB/qXRW/tOPaE6InF+f37gZO9wCVOiJZOEUOuJEmS9CYMnhANx5gQvf9w/1nBWwedFdz82rEnRA8Ov0cPyXJCtHRshlxJkiQpjXJyAlPKiphSNjITomsqipla7oRojV+GXEmSJCmD3siE6MHd4J9s38uu14eeEN0ffgcF4tqKEqZNLKIgzwnRyk6GXEmSJGmUG+6E6MHhN3k+9IToEGBaakL0QDe45IjOsBOiNVYZciVJkqQx7qQmRKfCb9+grHUt7dw75IToAmoqS6g9all0315hJ0RrtPJ/mZIkSVKWO9GE6J7eyI69h/r3BQ8+K/h4E6IHnxXshGiNFoZcSZIkaZzLzQnMqChmxghNiK6pLKZ6QqEhWGlhyJUkSZJ0XMOdEN0XftsG7Qne2n6QdS3t7DnYdcRnhpoQPTgUOyFab5QhV5IkSdKbMnhC9Fk1x58QvfWoI5La2g+ccEJ0TUXJwLLo1MRoJ0TrWAy5kiRJktLuZCZE94Xfvue/enHoCdFTy4r6w+/RZwXXVjoherwy5EqSJEnKuOFMiH5lz6FkOfQQE6J/vGk73ScxIbqmopiyovyR+NE0wk4YckMIU4F/BGbEGN8RQlgANMUY/0/aq5MkSZIkkgnRdZNLqJtcMuT1402IfnaYE6L7usF9YbiixAnRY9FwOrm3At8C/kfq9fPA3YAhV5IkSdKoMNwJ0UPtCW5+bT+/enEX+48xIXqopdBOiB69hhNyq2KM3w0hfAogxtgdQug50YckSZIkabQYPCF60QknRB+5J7it/SDrWzt+Y0J0QV5O/1LoIzvCSTfYCdGZMZyQuz+EMBmIACGE84A9aa1KkiRJkkbQyU6IHnxEUlvHQZ59dseQE6KnTUwNx6oo6d8X7ITo9BpOyP0z4B5gTgjhV0A18P7hfPEQwhXAF4Fc4Bsxxs8edb0OWAFUpO75ZIzxvhBCPvANYHGqxttijJ8Z3o8kSZIkSafeiSZEH+rqOTL8OiE6I44bckMIOUARcBEwDwjAczHGruN9LvXZXODLwNuBNmBNCOGeGOMzg277a+C7McavpAZa3Qc0AL8DFMYY3xJCKAGeCSF8J8bYfLI/oCRJkiSNhKL8XOZUT2BO9fAmRA/sDz7A+tbjTIg+xp5gJ0QP7bghN8bYG0L4fIyxCXj6JL/2UuDFGONmgBDCXcBVwOCQG4G+X4NMBLYNer80hJAHFAOdwN6T/P6SJEmSNGoMd0J00g0+cMSy6BNNiB58RFJtZSoUj9MJ0cNZrvxgCOF9wA9ijPGEdw+oAbYMet0GLDvqnr9Lff2PAaXAZan3v08SiLcDJcDHY4y7T+J7S5IkSdKYMnhC9LkNx58QvfWIs4IP0vLaflYOMSG6pCD3iPOB+8JvXyjOxgnRw92TWwr0hBAOkixZjjHGoReiDxjqP6mjQ/J1wK0xxs+HEJqA20MIZ5F0gXuAGUAl8IsQwk/7usL93yCEW4BbAOrq6obxo0iSJEnS2DScCdF7DnalpkMf/I2O8LEmRPd1f29e3sCl86eO1I+TNicMuTHGsjf4tduAmYNe1zKwHLnPh4ErUt9nVQihCKgCrgf+K7X399XUwKtG4IiQG2P8GvA1gMbGxpPpMkuSJElSVgkhUFFSQEXJ8CdE9+0Lbus4yOGjlkKPVcPp5BJCuBK4MPXykRjjvcP42BpgbghhFrAVuJYkvA7WClwK3BpCmE8y5Gpn6v23hRDuIFmufB7wz8OpVZIkSZI0tBNNiM4GJzyUKYTwWeBPSAZGPQP8Seq944oxdgMfBR4AniWZovx0COHTqdAM8AngD0IITwDfAW5O7fv9MjABeIokLH8rxrjppH86SZIkSdK4Ek40SyqEsAlYGGPsTb3OBTbEGM8egfqGrbGxMa5duzbTZUiSJEmS0iCEsC7G2Hii+07YyU2pGPR86MXdkiRJkiRl2HD25H4G2BBCeJhkYvKFwKfSWpUkSZIkSW/AcKYrfyeE8AhwLknI/csY4yvpLkySJEmSpJM1nMFT7wUOxBjviTH+CDgUQnhP+kuTJEmSJOnkDGdP7t/GGPf0vYgxdgB/m76SJEmSJEl6Y4YTcoe6Z1jn60qSJEmSNJKGE3LXhhD+KYQwJ4QwO4TwBWBduguTJEmSJOlkDSfkfgzoBO4GvgccAj6SzqIkSZIkSXojhjNdeT/wSYAQQiXQEWOM6S5MkiRJkqSTdcxObgjhf4YQzkg9Lwwh/Ax4EdgRQrhspAqUJEmSJGm4jrdc+QPAc6nnN6XunQJcBPxjmuuSJEmSJOmkHS/kdg5alvxbwHdijD0xxmdxurIkSZIkaRQ6Xsg9HEI4K4RQDVwCPDjoWkl6y5IkSZIk6eQdryP7J8D3gWrgCzHGlwFCCO8ENoxAbZIkSZIknZRjhtwY42rgjCHevw+4L51FSZIkSZL0RgznnFxJkiRJksYEQ64kSZIkKWsYciVJkiRJWeO4ITeEUB5CmDPE+2enryRJkiRJkt6YY4bcEMI1wK+Bfw8hPB1COHfQ5VvTXZgkSZIkSSfreJ3cvwKWxBgXAh8Cbg8hXJ26FtJemSRJkiRJJ+l45+Tmxhi3A8QYHw8hXALcG0KoBeKIVCdJkiRJ0kk4Xid33+D9uKnAezFwFXBmmuuSJEmSJOmkHa+T+984KgTHGPeFEK4ArklrVZIkSZIkvQHHDLkxxieOcak3TbVIkiRJkvSmHG+6cnkI4VMhhC+FEC4PiY8Bm7GTK0mSJEkahY63XPl2oB1YBfw+8N+BAuCqGOPGEahNkiRJkqSTcryQOzvG+BaAEMI3gF1AXYxx34hUJkmSJEnSSTredOWuvicxxh7gZQOuJEmSJGk0O14n95wQwt7U8wAUp14HIMYYy9NenSRJkiRJJ+F405VzR7IQSZIkSZLerOMtV5YkSZIkaUwx5EqSJEmSsoYhV5IkSZKUNQy5kiRJkqSsYciVJEmSJGUNQ64kSZIkKWsYciVJkiRJWcOQK0mSJEnKGoZcSZIkSVLWMORKkiRJkrKGIVeSJEmSlDUMuZIkSZKkrGHIlSRJkiRlDUOuJEmSJClrGHIlSZIkSVnDkCtJkiRJyhqGXEmSJElS1jDkSpIkSZKyhiFXkiRJkpQ1DLmSJEmSpKxhyJUkSZIkZQ1DriRJkiQpaxhyJUmSJElZI60hN4RwRQjhuRDCiyGETw5xvS6E8HAIYUMIYVMI4Z2p9z8YQtg46NEbQliYzlolSZIkSWNf2kJuCCEX+DLwDmABcF0IYcFRt/018N0Y4yLgWuBfAWKM344xLowxLgRuAJpjjBvTVaskSZIkKTuks5O7FHgxxrg5xtgJ3AVcddQ9EShPPZ8IbBvi61wHfCdtVUqSJEmSskZeGr92DbBl0Os2YNlR9/wd8GAI4WNAKXDZEF/nA/xmOAYghHALcAtAXV3dmyxXkiRJkjTWpbOTG4Z4Lx71+jrg1hhjLfBO4PYQQn9NIYRlwIEY41NDfYMY49dijI0xxsbq6upTVbckSZIkaYxKZ8htA2YOel3Lby5H/jDwXYAY4yqgCKgadP1aXKosSZIkSRqmdIbcNcDcEMKsEEIBSWC956h7WoFLAUII80lC7s7U6xzgd0j28kqSJEmSdEJpC7kxxm7go8ADwLMkU5SfDiF8OoRwZeq2TwB/EEJ4gqRje3OMsW9J84VAW4xxc7pqlCRJkiRllzCQKce2xsbGuHbt2kyXIUmSJElKgxDCuhhj44nuS+dyZUmSJEmSRpQhV5IkSZKUNQy5kiRJkqSsYciVJEmSJGUNQ64kSZIkKWsYciVJkiRJWcOQK0mSJEnKGoZcSZIkSVLWMORKkiRJkrKGIVeSJEmSlDUMuZIkSZKkrGHIlSRJkiRlDUOuJEmSJClrGHIlSZIkSVnDkCtJkiRJyhqGXEmSJElS1jDkSpIkSZKyhiFXkiRJkpQ1DLmSJEmSpKxhyJUkSZIkZQ1DriRJkiQpaxhyJUmSJElZw5ArSZIkScoahlxJkiRJUtYw5EqSJEmSsoYhV5IkSZKUNQy5kiRJkqSsYciVJEmSJGUNQ64kSZIkKWsYciVJkiRJWcOQK0mSJEnKGoZcSZIkSVLWMORKkiRJkrKGIVeSJEmSlDXyMl2ARliMsHszbH4E2tZAT2fqQoCcPJh2FtQth+lnQ25+JiuVJEmSpJNmyB0P9u+Cl3+eBNuXHoE9rcn7E6ZCwYSB+7oPwaa7kuf5JVDbmATe+iaoPRcKSke6ckmSJEk6KYbcbNR1EFpWJqF28yPwyqbk/cKJMOsCeOsfw+xLYPIcCOHIz+57BVpXQcsqaF0JP/9/gQghF6afA/XLoa4peZROHuEfTJIkSZKOL8QYM13DKdHY2BjXrl2b6TIyo7cHtj+RCrUPQ+tq6DkMOfkwcxnMvhjmXALTF0LuSf5e49Ae2PJ4EppbH4Ot65KvDVA1L+ny9oXeirrfDM2SJEmSdAqEENbFGBtPeJ8hd4zq3A+b7k6C7cuPwsH25P2pZyWhdvbFSdf1VC8x7joE2zYkXd6WVbBlNRzem1wrr0nCbn1Tssy5+gzIcbaZJEmSpDdvuCHX5cpjUfdh+PY10PLLJFjOe1cq2F4EE6ak93vnFyUhtr4JLiDpIr/6zMDy5uZfwlPfT+4tqoC681LBd3nSSc4rSG99kiRJksY1Q+5YEyP86CNJwH3Pv8E512Z2iXBOLkx7S/JYdktSX3tzal/vyuTP5/8ruTevCGoaB5Y4z1wKhWWZq12SJElS1jHkjjU/+1/w5PfgbX8DC6/LdDW/KQSYNCt5LLw+ee/1V5Ow2/pYEnx/8XmIvRByYNrZRy5xnlCd2folSZIkjWnuyR1L1n4L7v1TWHwT/PYXx+6Qp8P7kmFWfcG3bU1yfBHA5NMGljfXnQeVs8buzylJkiTplHFPbrZ5/kH48SfgtMvgXf80toNfYRmcdmnyAOjuhO0bB5Y3P/ufsOH25NqEaQNd3vommLIgWSItSZIkSUMw5I4F2zbC926GqWfC79x68scAjXZ5Bcn+3JlLgT+F3l7Y+euBCc6tq+DpHyb3Fk5M7usLvjWLIa8wo+VLkiRJGj2yLC1loY5WuPMaKJkE1393fAxqysmBqQuSx7m/nwyz6mhNljb3Bd8Xf5Lcm1sINUuSpc31y5MAXDQxs/VLkiRJyhj35I5mBzvgm78Fe7fDhx+AKfMzXdHosf+11J7e1GPbRog9yTCrqWcmXd6+4Fs2LdPVSpIkSXqT3JM71nUfhrt/F157CW74gQH3aKWTYf67kwdA5/5kgFXf8uYNt8PjX02uVc5KDbJKDbSaNHts72mWJEmSdEyG3NEoRvjRR6H5F3D112HWhZmuaPQrKIXZFycPgJ4u2L5pYHnzc/fDxm8n10qnDHR565qSM34dZiVJkiRlBUPuaPSzv4cnvwtv+2s4+5pMVzM25eZD7ZLksfxjyTCr114YmODcsgqevSe5t6As2cvbd15vzRLIL85s/ZIkSZLeEEPuaLPuVvjF52DxjXDBn2e6muyRkwPV85JH44eS9/a0JcOs+oLvw3+fujc/mdpc15R6LIPiyszVLkmSJGnYHDw1mrzwE7jzAzDnErjurqQbqZFzYDdsWZ0KvY/Btg3Q2wWE5Hze+qaB4DuxJtPVSpIkSePKcAdPGXJHi+2b4FvvgEmz4EP3j4+jgka7zgOwdV1qefPKZLBV5+vJtYq6ZIJz33m9VXMdZiVJkiSlkdOVx5r7/yIJttd/z4A7WhSUwKwLkgdATzfseDI1wXklvPhT2HRXcq1k8kCXt74Jpp0Duf7jJUmSJI20tP6/8BDCFcAXgVzgGzHGzx51vQ5YAVSk7vlkjPG+1LWzga8C5UAvcG6M8VA6682YV55KuoWX/wOUT890NTqW3DyYsSh5NP0/yRTs114cGGTVuhJ+fW9yb34p1DYOTHCuPTcJzZIkSZLSKm0hN4SQC3wZeDvQBqwJIdwTY3xm0G1/DXw3xviVEMIC4D6gIYSQB9wB3BBjfCKEMBnoSletGbf2/0BeESy8PtOV6GSEkCxTrpqbDAoD2Ls9CbutjyXB95HPAhFy8mD6wiP39ZZMymj5kiRJUjZKZyd3KfBijHEzQAjhLuAqYHDIjSSdWoCJwLbU88uBTTHGJwBijK+lsc7MOrQXnrgbznqfoScblE9P/rs8633J64MdsOXxgfN6V38VVv5Lcq36jNTy5lS3t2Jm5uqWJEmSskQ6Q24NsGXQ6zZg2VH3/B3wYAjhY0ApcFnq/dOBGEJ4AKgG7oox/n9Hf4MQwi3ALQB1dXWntPgRs+lu6NoP534405UoHYor4PTLkwdA1yHYtn7g2KKn/h3WfSu5Vl470OmtXw5V85KjjyRJkiQNWzpD7lCjZo8e5XwdcGuM8fMhhCbg9hDCWam6zgfOBQ4AD6UmaT10xBeL8WvA1yCZrnyqf4C0ixHWfCPZ41mzJNPVaCTkFyUBtn558rq3B3Y8PTDB+eVH4cnvJdeKK2HmeQMTnKefA3kFmatdkiRJGgPSGXLbgMHrL2sZWI7c58PAFQAxxlUhhCKgKvXZn8cYdwGEEO4DFgMPkU1aVsLOX8OVX8p0JcqUnFyYfnbyWPaHyS8+dm9OQm/fQKvn70/uzStOhln1TXCuXQqFEzJbvyRJkjTKpDPkrgHmhhBmAVuBa4GjJyu1ApcCt4YQ5gNFwE7gAeAvQgglQCdwEfCFNNaaGWu+AUUTB/ZvSiHA5DnJY9HvJu/t2zEQeltXwS8+B4/2QkgF5L7zemeeBxOqM1u/JEmSlGFpC7kxxu4QwkdJAmsu8M0Y49MhhE8Da2OM9wCfAL4eQvg4yVLmm2OMEWgPIfwTSVCOwH0xxh+nq9aM2LcDnr0Hlv6hR8vo+MqmwpnvSR6QDCtrezx1bNGq5Jclj305uTZ57sDy5vomqKhPgrMkSZI0ToQkU459jY2Nce3atZkuY/h+/r/h4b+Hj66DqtMyXY3Gsu7DsG3jwATnLY/BoT3JtbIZUHfewATnKQscZiVJkqQxKTWnqfFE96VzubKO55kfJd02A67erLxCqFuWPM7/OPT2ws5nByY4t6yCp3+Q3Fs0MVnW3Bd8ZyxKPi9JkiRlCUNuJuzfBTuehLf9TaYrUTbKyYGpZyaPpX+QDLPqaBlY3ty6Cl54ILk3ryiZ7F2XOrpo5lIoKj/+15ckSZJGMUNuJrz8aPLn7IszWYXGixCgsiF5LLwueW//roEub+sq+OUXIH4OQg5MPWtgeXNdU7InWJIkSRojDLmZsPkRKCyH6QszXYnGq9IqmP/byQPg8OvQtmbgvN51K2D1vyXXJs0eGGRV15S8dpiVJEmSRilDbia8/HNoOB9y/Y9fo0ThBJhzSfIA6O6EVzYN7Ot97sew8Y7k2oSpA13e+qak85uTm7naJUmSpEFMWSOtvQXam2HZf8t0JdKx5RVAbWPyeOsfJ8Osdj135BLnZ/4jubewPNnL2xd8a5ZAflFm65ckSdK4ZcgdaS//PPlz9sWZrEI6OTk5MGV+8mj8veS9ji0Dy5tbH4Of/a/k/dwCmLF44LzemUuhuCJztUuSJGlcMeSOtM0/hwnToHpepiuR3pyKmcnj7GuS1wd2J2G377zelf+SDLQiJJOe+5Y31y2H8ukZLV2SJEnZy5A7kmJMOrmzL3Fwj7JPySQ4453JA6DzAGxdm1revBI23glrvp5cq6gfmOBcvxwmn+Y/E5IkSTolDLkj6dVnYP9OmH1RpiuR0q+gBGZdmDwAerqSYVatjyVLnF94EJ74TnKttBrqzhvY1zvtLZCbn7naJUmSNGYZckfS5tR+3FmGXI1DufnJUKqaJdD0kWRlw64Xki5vX/B99j+Te3PyYNIcqD4dqs+AqnnJ88lzk/AsSdL/be/ug+yq7/uOv7+7Wj0/awUG9MSDJAyu7dgKxHXjofFDMOPGdmu30ExrWrcuaZ1pOs1M0jRtPPQft6k7k3bSdOzE44c6BrsYm3YIhjZpnXgMg5B5MCCJJxmEFLSSAKEHJO3q2z/OWe7Zu/furpb7tHffr5kze/ec365+l8O593z2e+73SFIThtxOeu7/FSfuqzd2eyZS90WUIXYbvPvmYt2xA0XYfelxGNkDh56E3XdDjo3/EKzeVHymff32Mvxuh+FtNreSJEkSYMjtnLFR2PdDePsnuz0TqXetvBj+yieKZdzoaTjyTHELo5G9MLIbDu8trowYO10bt/wtlcrvtjIIX1lcCu3nfSVJkuYNQ26nHNgFZ17zUmXpfC1YBBdeVSxV58aKe04f3ltUfUf2FEH44W8Wx9q4xasnV37Xb4eVG4pbI0mSJKmvGHI75YUHiq+b39vdeUj9YmAQ1l1eLNs/XFufWVz2XF/53X03nPxabdzQUhjeOrnyu+ZSGPSlUZIkaa7yTK5TDvwYVm2E5eu7PROpv0XAqkuK5fJfmLjtxJEy/FYqv/t+CI/eXhszMFQE5/rK77orYGhJZ5+LJEmSzpsht1MuuArWbOn2LKT5bdk6WPZXi3vzVp1+rbzsuVL5/cufFN2e81w5KGDN5smV3+FtsHhlx5+KJEmSGjPkdsr7fr3bM5DUzKIVtdsbVZ19HY4+M7HyO7IXnvlTGDtTG7fiokrlt3Lbo2XDNr2SJEnqMEOuJDUztBguvLpYqsZG4ZWfluF3d6351cPfgDPHa+OWrKmr/JZBeNUGw68kSVKbGHIl6XwNLqg1vbryhtr6TDj24uTK75P/E3Z9tTZuaFlR8a2v/K7ZYtMrSZKkN8mzKUlqlYiiSrtqA1zx/onbThyeXPl97gfw6G21MYMLiwZX9ZXfdVcUVWVJkiRNy5ArSZ2wbLhYttTdRuz1Y3D4qTL8lpXfg4/AE98DshgTA0WVt9rtebwKvGhFp5+JJElSTzPkSlI3LV4JG95dLFVnX4cjT0+s/I7sgaf/N5w7Wxu38pKy8ntl5RLoK4tO0pIkSfOQIVeSetHQYnjL24qlamwUXt43sfI7sht2fQ3OnqiNW7qurvJbBuGVF9v0SpIk9TVDriTNJYMLYPiKYuEjtfXnzsGx/UXoPbynVvl94rtw6uXauIUrYHhrXeW3bHo1MNjpZyNJktRyhlxJ6gcDA7B6U7Fs/UBtfWbZ9Kqu8vvsn8Ejf1wbN7ioaHBVX/lddzksWNT55yNJkjRLhlxJ6mcRsHx9sVz68xO3vf7q5MrvgV3w+J3Uml4NFlXe+srv8DZYtLzTz0aSJGlahlxJmq8Wr4KNP1ssVWdPFR2f32h4VTa/eur7cG60Nm7lhsmV3/XbYenazj4PSZKkCkOuJGmioSVw0duLpWrsLBx9rqz87q5VgR/6EZw9WRu3dHhy5Xf9dlhxkU2vJElS2xlyJUkzMzhUBNf12+Ctf6O2/tw5ePWFsvK7u6j+Ht4LP7mjuCR63KKVZcV3+8TbHq3ebNMrSZLUMoZcSdKbMzAAazYXy9YP1tZnwvFDEz/ze3gPPP1/4OFv1MYtWAzrtk6u/K69HBYs7PzzkSRJc5ohV5LUHhGw4sJiufR9E7edemVy5Xf/g0X1942fH4S1l02u/A5vg4XLOvtcJEnSnGHIlSR13pLVsPGaYqk6cxKOPDWx8juyB/beM7Hp1apNkyu/w9tseiVJkgy5kqQesnApXPSOYqkaOwtHn53Y8GpkN+z7IYyeqo1bdkEl9G4vP0N8JSy/0KZXkiTNE4ZcSVLvGxyqhdeqc+fg1ecnV34f/Tacrja9WlUG3u0Tq7+rNhWfKZYkSX3DkCtJmrsGBmDNlmLZ9ou19Zlw/KW6yu8e2Hsv/Pi/18YtWALDVxTV3mrld+1lRbCWJElzjiFXktR/ImDFW4rlsusmbjt5tGx6tafW/Or5B+Cxb9fGDCyoNL2qVH7XbS0uqZYkST3LkCtJml+WroVNP1csVWdOlKG3Uvk9tBt23w05Vg4KWL2xrPyWlz+PP16yuuNPRZIkTWbIlSQJitsSXfwzxVI1egaOPjOx8juyF577AYy+Xhu3/MLJlXRmz6cAAA/WSURBVN/h7bD8ApteSZLUQYZcSZKmsmAhXPDWYqk6Nwav/HRi5XdkDzx6O5w+Vhu3eFXjyu+qjTa9kiSpDQy5kiTNxsBg8bndtZfB9utr6zPhtYOTK79774Eff702bmgpDG+d2PBqeDusvdSmV5IkvQmGXEmSWikCVl5cLJf/9YnbTh6deKujkT3w/I/gsW/VxgwMwbrLJ1d+h7fC0JLOPhdJkuYgQ64kSZ2ydC1sfk+xVJ0+XlR9q5XfQ0/A7v8Fea4cFLBm88TK76oNsOwCWLa++N0Dgx1/SpIk9RpDriRJ3bZoOVzyrmKpGj0NR56ZWPk9vBee/b8wdnri2BiApevK0DtcBN/l44/LILx8ffF12QUwtLhjT0+SpE4y5EqS1KsWLIILryqWqnNj8PK+4rO/J0bg+Ejx9cQhOHEYjh+CFx8qHp95rfHvXriiEnorS6NgvHi1HaIlSXOGIVeSpLlmYLD43O66y6cfe+YknDxcF4TrgvHRZ+H5++HkESAb/HtDZQgeLkPw+uYV4mXDNs6SJHWVIVeSpH62cCks3ASrN00/9txY0RyrURCufj+yp6gW118yPW7JmplViJeth4XLrRJLklrKkCtJkgoDg0X4XL5++rGZcOZ4EXZPHG4SjA8XDbSOH4LXX2n8exYsqasSV4Nw3fc215IkzYAhV5Iknb8IWLSiWGZy2fTomeKy6akqxMcOwMFHisfnRhv8m+PNtWZQIV623lsuSdI8ZciVJEntt2Bh7f7B08mEUy9PXSE+MTKz5loTPkdscy1Jmg8MuZIkqbdEFJcmL11b3BN4OtM21xopmmu98EARips21xqeQYXY5lqS1OsMuZIkaW5rZXOt8VswHX6qWDf6euPfs3j1zCrENteSpI4z5EqSpPmjpc21ysXmWpLUUwy5kiRJjbSyudZ4hdjmWpLUdm0NuRFxPfB7wCDwh5n5+brtm4CvAqvLMb+ZmXdHxBbgSWBPOfT+zLylnXOVJEl6U1rWXKuytKq51rLh4v7FXjYtaR5oW8iNiEHg94EPAvuBByPirsx8ojLst4FvZeYfRMRVwN3AlnLbM5n5znbNT5IkqWvOt7nW2VMNgvChWoW42lzr5BHIc5N/x4yba5WLzbUkzVHtrOReAzydmc8CRMRtwEeBashNYGX5eBVwoI3zkSRJmpuGlhSNtWbTXKsahKvBuBXNtcaryDbXktRD2hlyLwFeqHy/H7i2bszngHsj4leBZcAHKtsujYgfA8eA387MP6//ByLiM8BnADZtmsGLviRJUr97U821GlSIZ9Rca3Ht9kpNm2uVt2CyuZakNmtnyG3057z6G9PdBHwlM78QEe8Bvh4RbwMOApsy80hEvBv4bkRcnZnHJvyyzC8CXwTYsWNHg5veSZIkqak301xrUoOtFjbXql4+bXMtSeepnSF3P7Cx8v0GJl+O/GngeoDM/FFELAaGM/MQcLpc/1BEPANsA3a2cb6SJEmayqybazWpELekudb6WhXZ5lqSaG/IfRDYGhGXAi8CNwJ/t27M88D7ga9ExFuBxcBIRKwHjmbmWERcBmwFnm3jXCVJktRKs22u1axCPKPmWgtmXiG2uZbUt9oWcjNzNCI+C3yf4vZAX87MxyPiVmBnZt4F/EvgSxHxLyguZb45MzMi3gfcGhGjwBhwS2YebddcJUmS1GWzaq7VqELcquZalQqxzbWkOSUy++OjrDt27MidO72aWZIkSRXjzbWmqhBXl1MvN/49UzXXmlAhtrmW1C4R8VBm7phuXDsvV5YkSZK6q9pca+1l048fPVNcDj1+C6ZWNdeqD8I215LaxpArSZIkjVuwEFZeVCzTySxuqzRdhfi8m2sNTw7CNteSZsyQK0mSJM1GRBE6l6xpYXOt52bZXKtBhdjmWpqnDLmSJElSJ/RKc61GFWKba6mPGHIlSZKkXjMwWATR5euBq6YeO6PmWofh0BOzaK7VqEJscy31NkOuJEmSNJe1urnWiZGyudajZXOtsw3+TZtrqXcZciVJkqT5pB3NtQ7sKsZM11xrwueIba6l9jDkSpIkSWqslc21TowU4fh8m2tNVSG2uZYaMORKkiRJao2WNdeqLDNprjWTCrHNteYNQ64kSZKkzmtVc63xCvGJw3DoSTjxg2maa82kQmxzrbnMkCtJkiSpt7WsuVZlee0g/OVjM2yu1axCbHOtXmTIlSRJktRfWtFc640K8Uybay2vVIhtrtVNhlxJkiRJ89ebaa7V6HPE59VcawYV4qXDRWjXjBlyJUmSJGmmZt1cqy4It6O51rL1xSXd87xKbMiVJEmSpHaY0FxrGg2ba9UHY5trzYQhV5IkSZK6bdbNtaa4BdN0zbWIornWeIX42l+BK29o+VPrNEOuJEmSJM01s2mu1ewzxOOPGwbhuceQK0mSJEn9rNpca3hrt2fTdgPdnoAkSZIkSa1iyJUkSZIk9Q1DriRJkiSpbxhyJUmSJEl9w5ArSZIkSeobhlxJkiRJUt8w5EqSJEmS+oYhV5IkSZLUNwy5kiRJkqS+YciVJEmSJPUNQ64kSZIkqW8YciVJkiRJfcOQK0mSJEnqG4ZcSZIkSVLfMORKkiRJkvqGIVeSJEmS1DcMuZIkSZKkvmHIlSRJkiT1jcjMbs+hJSJiBPhpt+cxjWHgcLcnoQncJ73J/dJ73Ce9yf3Se9wnvcn90nvcJ72p1/fL5sxcP92gvgm5c0FE7MzMHd2eh2rcJ73J/dJ73Ce9yf3Se9wnvcn90nvcJ72pX/aLlytLkiRJkvqGIVeSJEmS1DcMuZ31xW5PQJO4T3qT+6X3uE96k/ul97hPepP7pfe4T3pTX+wXP5MrSZIkSeobVnIlSZIkSX3DkCtJkiRJ6huG3DaIiOsjYk9EPB0Rv9lg+6KIuL3c/kBEbOn8LOePiNgYEX8WEU9GxOMR8c8bjLkuIl6NiIfL5d92Y67zTUTsi4jHyv/mOxtsj4j4z+Wx8mhEvKsb85wvImJ75Rh4OCKORcSv1Y3xWOmAiPhyRByKiJ9U1q2NiPsi4qny65omP/upcsxTEfGpzs26vzXZJ78bEbvL16c7I2J1k5+d8rVOs9dkv3wuIl6svE7d0ORnpzxf0+w02Se3V/bHvoh4uMnPeqy0QbNz4X5+X/EzuS0WEYPAXuCDwH7gQeCmzHyiMuafAm/PzFsi4kbg45n5d7oy4XkgIi4CLsrMXRGxAngI+FjdPrkO+PXM/EiXpjkvRcQ+YEdmNrzpeHli8qvADcC1wO9l5rWdm+H8Vb6WvQhcm5k/ray/Do+VtouI9wHHga9l5tvKdf8BOJqZny9PyNdk5m/U/dxaYCewA0iK17t3Z+bLHX0CfajJPvkQ8KeZORoR/x6gfp+U4/YxxWudZq/JfvkccDwz/+MUPzft+Zpmp9E+qdv+BeDVzLy1wbZ9eKy0XLNzYeBm+vR9xUpu610DPJ2Zz2bmGeA24KN1Yz4KfLV8/D+A90dEdHCO80pmHszMXeXj14AngUu6OyvN0Ecp3iQzM+8HVpcv1Gq/9wPPVAOuOiczfwAcrVtdfe/4KsUJSr1fBO7LzKPlCch9wPVtm+g80mifZOa9mTlafns/sKHjE5vnmhwrMzGT8zXNwlT7pDzf/dvANzs6qXluinPhvn1fMeS23iXAC5Xv9zM5UL0xpnxzfBVY15HZzXNRXBr+M8ADDTa/JyIeiYg/iYirOzqx+SuBeyPioYj4TIPtMzme1B430vwkxGOlOy7MzINQnLAAFzQY4zHTPf8Q+JMm26Z7rVPrfba8jPzLTS7B9Fjpjp8HXsrMp5ps91hps7pz4b59XzHktl6jimz9NeEzGaMWi4jlwB3Ar2XmsbrNu4DNmfkO4L8A3+30/Oap92bmu4APA/+svMSpymOlCyJiIfBLwLcbbPZY6W0eM10QEf8aGAW+0WTIdK91aq0/AC4H3gkcBL7QYIzHSnfcxNRVXI+VNprmXLjpjzVY1/PHiiG39fYDGyvfbwAONBsTEQuAVczuUhvNUEQMURzU38jM79Rvz8xjmXm8fHw3MBQRwx2e5ryTmQfKr4eAOykuH6uayfGk1vswsCszX6rf4LHSVS+NX65ffj3UYIzHTIeVTVg+AvxyNml0MoPXOrVQZr6UmWOZeQ74Eo3/e3usdFh5zvs3gdubjfFYaZ8m58J9+75iyG29B4GtEXFpWQ25EbirbsxdwHhnsk9QNK3o+b+IzFXl5z/+CHgyM/9TkzFvGf9cdERcQ3FsHOncLOefiFhWNj8gIpYBHwJ+UjfsLuDvR+HnKBpVHOzwVOejpn9p91jpqup7x6eA7zUY833gQxGxprxE80PlOrVBRFwP/AbwS5l5ssmYmbzWqYXqejd8nMb/vWdyvqbW+gCwOzP3N9rosdI+U5wL9+37yoJuT6DflB0WP0ux8weBL2fm4xFxK7AzM++i+J/s6xHxNEUF98buzXheeC/w94DHKi3rfwvYBJCZ/43ijw2/EhGjwCngRv/w0HYXAneWeWkB8MeZeU9E3AJv7Je7KTorPw2cBP5Bl+Y6b0TEUopuo/+ksq66TzxWOiAivglcBwxHxH7gd4DPA9+KiE8DzwOfLMfuAG7JzH+UmUcj4t9RnMAD3JqZXinUAk32yb8CFgH3la9l95d3TrgY+MPMvIEmr3VdeAp9qcl+uS4i3klxSeU+ytez6n5pdr7WhafQdxrtk8z8Ixr0evBY6Zhm58J9+77iLYQkSZIkSX3Dy5UlSZIkSX3DkCtJkiRJ6huGXEmSJElS3zDkSpIkSZL6hiFXkiRJktQ3DLmSJPWIiPh4RGREXFl+vyUiprxP5EzGSJI0nxhyJUnqHTcBf4H3T5ckadYMuZIk9YCIWA68F/g0DUJuRNwcEd+LiHsiYk9E/E5l82BEfCkiHo+IeyNiSfkz/zgiHoyIRyLijohY2plnI0lS9xhyJUnqDR8D7snMvcDRiHhXgzHXAL8MvBP4ZETsKNdvBX4/M68GXgH+Vrn+O5n5s5n5DuBJigAtSVJfM+RKktQbbgJuKx/fVn5f777MPJKZp4DvAH+tXP9cZj5cPn4I2FI+fltE/HlEPEYRjq9uy8wlSeohC7o9AUmS5ruIWAf8AkUoTWAQSOC/1g3NJt+frqwbA5aUj78CfCwzH4mIm4HrWjdrSZJ6k5VcSZK67xPA1zJzc2ZuycyNwHPAhrpxH4yIteVnbj8G/HCa37sCOBgRQxSVXEmS+p4hV5Kk7rsJuLNu3R3Ab9Wt+wvg68DDwB2ZuXOa3/tvgAeA+4DdLZinJEk9LzLrr3ySJEm9przceEdmfrbbc5EkqZdZyZUkSZIk9Q0ruZIkSZKkvmElV5IkSZLUNwy5kiRJkqS+YciVJEmSJPUNQ64kSZIkqW8YciVJkiRJfeP/A2zWZ3Q3XlF+AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "plt.plot(cv_result_r['param_alpha'],cv_result_r['mean_train_score'])\n",
    "plt.plot(cv_result_r['param_alpha'],cv_result_r['mean_test_score'])\n",
    "plt.xlabel('Alpha')\n",
    "# plt.xscale('log')\n",
    "plt.ylabel('R2 Score')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### On the basis of above graph lets create the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'alpha': 0.9}"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the best parameter(Alpha value)\n",
    "model_cv.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.905199009080942\n",
      "0.851741176450402\n"
     ]
    }
   ],
   "source": [
    "ridge = Ridge(alpha = 0.9)\n",
    "ridge.fit(X_train,y_train)\n",
    "\n",
    "y_pred_train = ridge.predict(X_train)\n",
    "print(r2_score(y_train,y_pred_train))\n",
    "\n",
    "y_pred_test = ridge.predict(X_test)\n",
    "print(r2_score(y_test,y_pred_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_parameter = list(ridge.coef_)\n",
    "model_parameter.insert(0,ridge.intercept_)\n",
    "cols = df_train.columns\n",
    "cols.insert(0,'constant')\n",
    "ridge_coef = pd.DataFrame(list(zip(cols,model_parameter)))\n",
    "ridge_coef.columns = ['Feaure','Coef']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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>Feaure</th>\n",
       "      <th>Coef</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>MiscVal</td>\n",
       "      <td>1.482910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>BsmtHalfBath</td>\n",
       "      <td>0.574493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>HalfBath</td>\n",
       "      <td>0.421184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>LowQualFinSF</td>\n",
       "      <td>0.419674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>BsmtFullBath</td>\n",
       "      <td>0.399218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Neighborhood_Gilbert</td>\n",
       "      <td>0.338057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>EnclosedPorch</td>\n",
       "      <td>0.335071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>TotRmsAbvGrd</td>\n",
       "      <td>0.286967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>GrLivArea</td>\n",
       "      <td>0.266793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Neighborhood_IDOTRR</td>\n",
       "      <td>0.261202</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Feaure      Coef\n",
       "44               MiscVal  1.482910\n",
       "25          BsmtHalfBath  0.574493\n",
       "27              HalfBath  0.421184\n",
       "22          LowQualFinSF  0.419674\n",
       "24          BsmtFullBath  0.399218\n",
       "67  Neighborhood_Gilbert  0.338057\n",
       "40         EnclosedPorch  0.335071\n",
       "31          TotRmsAbvGrd  0.286967\n",
       "23             GrLivArea  0.266793\n",
       "68   Neighborhood_IDOTRR  0.261202"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ridge_coef.sort_values(by='Coef',ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### After creating model in both Ridge and Lasso we can see that the r2_scores are almost same for both of them but as lasso will penalize more on the dataset and can also help in feature elemination i am goint to consider that as my final model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Final Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9022070628442351\n",
      "0.8575605370873767\n"
     ]
    }
   ],
   "source": [
    "lasso = Lasso(alpha=0.001)\n",
    "lasso.fit(X_train,y_train)\n",
    "\n",
    "y_train_pred = lasso.predict(X_train)\n",
    "y_test_pred = lasso.predict(X_test)\n",
    "\n",
    "print(r2_score(y_true=y_train,y_pred=y_train_pred))\n",
    "print(r2_score(y_true=y_test,y_pred=y_test_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### After compairing both the model we can see that the below Features are best explaining the DataSet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "#MiscVal      : $Value of miscellaneous feature \n",
    "#BsmtHalfBath : Basement half bathrooms\n",
    "#LowQualFinSF : Low quality finished square feet (all floors)\n",
    "#BsmtFullBath : Basement full bathrooms\n",
    "#HalfBath     : Half baths above grade"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Best alpha value for Lasso : {'alpha': 0.001}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Best alpha value for Ridge : {'alpha': 0.9}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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