02.LinearRegression.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# UNDERSTANDING LINEAR REGRESSION WITH HOUSE PRICE PREDICTION DATASET\n",
    "\n",
    "<b>PROBLEM STATEMENT</b>:\n",
    "\n",
    "*Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.*\n",
    "\n",
    "*With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.*\n",
    "\n",
    "**Data Source** - https://www.kaggle.com/c/house-prices-advanced-regression-techniques/overview\n",
    "\n",
    "### DOWNLOAD THE DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading house-prices-advanced-regression-techniques.zip to /Users/nikhilkashyap/Downloads/Learning/Github/11-Projects-to-DataScience/2.LinearRegression\n",
      "100%|████████████████████████████████████████| 199k/199k [00:00<00:00, 1.10MB/s]\n",
      "100%|████████████████████████████████████████| 199k/199k [00:00<00:00, 1.09MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle competitions download -c house-prices-advanced-regression-techniques"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.LinearRegression.ipynb\r\n",
      "house-prices-advanced-regression-techniques.zip\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Archive:  house-prices-advanced-regression-techniques.zip\r\n",
      "  inflating: data_description.txt    \r\n",
      "  inflating: sample_submission.csv   \r\n",
      "  inflating: test.csv                \r\n",
      "  inflating: train.csv               \r\n"
     ]
    }
   ],
   "source": [
    "# unzip the data\n",
    "!unzip house-prices-advanced-regression-techniques.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.LinearRegression.ipynb\r\n",
      "data_description.txt\r\n",
      "house-prices-advanced-regression-techniques.zip\r\n",
      "sample_submission.csv\r\n",
      "test.csv\r\n",
      "train.csv\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### READ THE DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from scipy.stats import norm\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('train.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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 MoSold  \\\n",
       "0         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      2   \n",
       "1         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      5   \n",
       "2         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      9   \n",
       "3         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      2   \n",
       "4         Lvl    AllPub  ...        0    NaN   NaN         NaN       0     12   \n",
       "\n",
       "  YrSold  SaleType  SaleCondition  SalePrice  \n",
       "0   2008        WD         Normal     208500  \n",
       "1   2007        WD         Normal     181500  \n",
       "2   2008        WD         Normal     223500  \n",
       "3   2006        WD        Abnorml     140000  \n",
       "4   2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 81 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DATA DESCRIPTION\n",
    "\n",
    "<b>File descriptions</b>\n",
    "1. train.csv - the training set\n",
    "2. test.csv - the test set\n",
    "3. data_description.txt - full description of each column, originally prepared by Dean De Cock but lightly edited to match the column names used here\n",
    "4. sample_submission.csv - a benchmark submission from a linear regression on year and month of sale, lot square footage, and number of bedrooms\n",
    "\n",
    "\n",
    "<b>Data fields</b>\n",
    "\n",
    "Here's a brief version of what you'll find in the data description file.\n",
    "\n",
    "SalePrice - the property's sale price in dollars. This is the target variable that you're trying to predict.\n",
    "\n",
    "MSSubClass: The building class\n",
    "\n",
    "MSZoning: The general zoning classification\n",
    "\n",
    "LotFrontage: Linear feet of street connected to property\n",
    "\n",
    "LotArea: Lot size in square feet\n",
    "\n",
    "Street: Type of road access\n",
    "\n",
    "Alley: Type of alley access\n",
    "\n",
    "LotShape: General shape of property\n",
    "\n",
    "LandContour: Flatness of the property\n",
    "\n",
    "Utilities: Type of utilities available\n",
    "\n",
    "LotConfig: Lot configuration\n",
    "\n",
    "LandSlope: Slope of property\n",
    "\n",
    "Neighborhood: Physical locations within Ames city limits\n",
    "\n",
    "Condition1: Proximity to main road or railroad\n",
    "\n",
    "Condition2: Proximity to main road or railroad (if a second is present)\n",
    "\n",
    "BldgType: Type of dwelling\n",
    "\n",
    "HouseStyle: Style of dwelling\n",
    "\n",
    "OverallQual: Overall material and finish quality\n",
    "\n",
    "OverallCond: Overall condition rating\n",
    "\n",
    "YearBuilt: Original construction date\n",
    "\n",
    "YearRemodAdd: Remodel date\n",
    "\n",
    "RoofStyle: Type of roof\n",
    "\n",
    "RoofMatl: Roof material\n",
    "\n",
    "Exterior1st: Exterior covering on house\n",
    "\n",
    "Exterior2nd: Exterior covering on house (if more than one material)\n",
    "\n",
    "MasVnrType: Masonry veneer type\n",
    "\n",
    "MasVnrArea: Masonry veneer area in square feet\n",
    "\n",
    "ExterQual: Exterior material quality\n",
    "\n",
    "ExterCond: Present condition of the material on the exterior\n",
    "\n",
    "Foundation: Type of foundation\n",
    "\n",
    "BsmtQual: Height of the basement\n",
    "\n",
    "BsmtCond: General condition of the basement\n",
    "\n",
    "BsmtExposure: Walkout or garden level basement walls\n",
    "\n",
    "BsmtFinType1: Quality of basement finished area\n",
    "\n",
    "BsmtFinSF1: Type 1 finished square feet\n",
    "\n",
    "BsmtFinType2: Quality of second finished area (if present)\n",
    "\n",
    "BsmtFinSF2: Type 2 finished square feet\n",
    "\n",
    "BsmtUnfSF: Unfinished square feet of basement area\n",
    "\n",
    "TotalBsmtSF: Total square feet of basement area\n",
    "\n",
    "Heating: Type of heating\n",
    "\n",
    "HeatingQC: Heating quality and condition\n",
    "\n",
    "CentralAir: Central air conditioning\n",
    "\n",
    "Electrical: Electrical system\n",
    "\n",
    "1stFlrSF: First Floor square feet\n",
    "\n",
    "2ndFlrSF: Second floor square feet\n",
    "\n",
    "LowQualFinSF: Low quality finished square feet (all floors)\n",
    "\n",
    "GrLivArea: Above grade (ground) living area square feet\n",
    "\n",
    "BsmtFullBath: Basement full bathrooms\n",
    "\n",
    "BsmtHalfBath: Basement half bathrooms\n",
    "\n",
    "FullBath: Full bathrooms above grade\n",
    "\n",
    "HalfBath: Half baths above grade\n",
    "\n",
    "Bedroom: Number of bedrooms above basement level\n",
    "\n",
    "Kitchen: Number of kitchens\n",
    "\n",
    "KitchenQual: Kitchen quality\n",
    "\n",
    "TotRmsAbvGrd: Total rooms above grade (does not include bathrooms)\n",
    "\n",
    "Functional: Home functionality rating\n",
    "\n",
    "Fireplaces: Number of fireplaces\n",
    "\n",
    "FireplaceQu: Fireplace quality\n",
    "\n",
    "GarageType: Garage location\n",
    "\n",
    "GarageYrBlt: Year garage was built\n",
    "\n",
    "GarageFinish: Interior finish of the garage\n",
    "\n",
    "GarageCars: Size of garage in car capacity\n",
    "\n",
    "GarageArea: Size of garage in square feet\n",
    "\n",
    "GarageQual: Garage quality\n",
    "\n",
    "GarageCond: Garage condition\n",
    "\n",
    "PavedDrive: Paved driveway\n",
    "\n",
    "WoodDeckSF: Wood deck area in square feet\n",
    "\n",
    "OpenPorchSF: Open porch area in square feet\n",
    "\n",
    "EnclosedPorch: Enclosed porch area in square feet\n",
    "\n",
    "3SsnPorch: Three season porch area in square feet\n",
    "\n",
    "ScreenPorch: Screen porch area in square feet\n",
    "\n",
    "PoolArea: Pool area in square feet\n",
    "\n",
    "PoolQC: Pool quality\n",
    "\n",
    "Fence: Fence quality\n",
    "\n",
    "MiscFeature: Miscellaneous feature not covered in other categories\n",
    "\n",
    "MiscVal: $Value of miscellaneous feature\n",
    "\n",
    "MoSold: Month Sold\n",
    "\n",
    "YrSold: Year Sold\n",
    "\n",
    "SaleType: Type of sale\n",
    "\n",
    "SaleCondition: Condition of sale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1460, 81)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<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>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>8 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",
       "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",
       "max       9.000000  2010.000000   2010.000000  1600.000000  5644.000000  ...   \n",
       "\n",
       "        WoodDeckSF  OpenPorchSF  EnclosedPorch    3SsnPorch  ScreenPorch  \\\n",
       "count  1460.000000  1460.000000    1460.000000  1460.000000  1460.000000   \n",
       "mean     94.244521    46.660274      21.954110     3.409589    15.060959   \n",
       "std     125.338794    66.256028      61.119149    29.317331    55.757415   \n",
       "min       0.000000     0.000000       0.000000     0.000000     0.000000   \n",
       "25%       0.000000     0.000000       0.000000     0.000000     0.000000   \n",
       "50%       0.000000    25.000000       0.000000     0.000000     0.000000   \n",
       "75%     168.000000    68.000000       0.000000     0.000000     0.000000   \n",
       "max     857.000000   547.000000     552.000000   508.000000   480.000000   \n",
       "\n",
       "          PoolArea       MiscVal       MoSold       YrSold      SalePrice  \n",
       "count  1460.000000   1460.000000  1460.000000  1460.000000    1460.000000  \n",
       "mean      2.758904     43.489041     6.321918  2007.815753  180921.195890  \n",
       "std      40.177307    496.123024     2.703626     1.328095   79442.502883  \n",
       "min       0.000000      0.000000     1.000000  2006.000000   34900.000000  \n",
       "25%       0.000000      0.000000     5.000000  2007.000000  129975.000000  \n",
       "50%       0.000000      0.000000     6.000000  2008.000000  163000.000000  \n",
       "75%       0.000000      0.000000     8.000000  2009.000000  214000.000000  \n",
       "max     738.000000  15500.000000    12.000000  2010.000000  755000.000000  \n",
       "\n",
       "[8 rows x 38 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DATA CLEANING\n",
    "Check for missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['LotFrontage',\n",
       " 'Alley',\n",
       " 'MasVnrType',\n",
       " 'MasVnrArea',\n",
       " 'BsmtQual',\n",
       " 'BsmtCond',\n",
       " 'BsmtExposure',\n",
       " 'BsmtFinType1',\n",
       " 'BsmtFinType2',\n",
       " 'Electrical',\n",
       " 'FireplaceQu',\n",
       " 'GarageType',\n",
       " 'GarageYrBlt',\n",
       " 'GarageFinish',\n",
       " 'GarageQual',\n",
       " 'GarageCond',\n",
       " 'PoolQC',\n",
       " 'Fence',\n",
       " 'MiscFeature']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# find columns with missing values\n",
    "mis_cols = df.columns[df.isna().any()].tolist()\n",
    "mis_cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing values percentage in\n",
      "LotFrontage is \n",
      " 17.73972602739726\n",
      "Alley is \n",
      " 93.76712328767123\n",
      "MasVnrType is \n",
      " 0.547945205479452\n",
      "MasVnrArea is \n",
      " 0.547945205479452\n",
      "BsmtQual is \n",
      " 2.5342465753424657\n",
      "BsmtCond is \n",
      " 2.5342465753424657\n",
      "BsmtExposure is \n",
      " 2.6027397260273974\n",
      "BsmtFinType1 is \n",
      " 2.5342465753424657\n",
      "BsmtFinType2 is \n",
      " 2.6027397260273974\n",
      "Electrical is \n",
      " 0.0684931506849315\n",
      "FireplaceQu is \n",
      " 47.26027397260274\n",
      "GarageType is \n",
      " 5.5479452054794525\n",
      "GarageYrBlt is \n",
      " 5.5479452054794525\n",
      "GarageFinish is \n",
      " 5.5479452054794525\n",
      "GarageQual is \n",
      " 5.5479452054794525\n",
      "GarageCond is \n",
      " 5.5479452054794525\n",
      "PoolQC is \n",
      " 99.52054794520548\n",
      "Fence is \n",
      " 80.75342465753424\n",
      "MiscFeature is \n",
      " 96.30136986301369\n"
     ]
    }
   ],
   "source": [
    "print(\"Missing values percentage in\")\n",
    "for item in mis_cols:\n",
    "    print(\"{} is \\n\".format(item),(df[item].isnull().sum()/df.shape[0])*100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that columns \"Alley\", \"FireplaceQu\", \"PoolQC\", \"Fence\", \"MiscFeature\" have lot of missing values and it's not wise to fill NaN values with any statistical methods. Hence, we'll drop those columns as it doesn't contain any substantial information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop([\"Alley\", \"FireplaceQu\", \"PoolQC\", \"Fence\", \"MiscFeature\"], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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",
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       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
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       "      <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>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>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <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>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
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       "      <td>181500</td>\n",
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       "    <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>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>272</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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 × 76 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street LotShape LandContour  \\\n",
       "0   1          60       RL         65.0     8450   Pave      Reg         Lvl   \n",
       "1   2          20       RL         80.0     9600   Pave      Reg         Lvl   \n",
       "2   3          60       RL         68.0    11250   Pave      IR1         Lvl   \n",
       "3   4          70       RL         60.0     9550   Pave      IR1         Lvl   \n",
       "4   5          60       RL         84.0    14260   Pave      IR1         Lvl   \n",
       "\n",
       "  Utilities LotConfig  ... EnclosedPorch 3SsnPorch ScreenPorch PoolArea  \\\n",
       "0    AllPub    Inside  ...             0         0           0        0   \n",
       "1    AllPub       FR2  ...             0         0           0        0   \n",
       "2    AllPub    Inside  ...             0         0           0        0   \n",
       "3    AllPub    Corner  ...           272         0           0        0   \n",
       "4    AllPub       FR2  ...             0         0           0        0   \n",
       "\n",
       "  MiscVal MoSold  YrSold  SaleType  SaleCondition  SalePrice  \n",
       "0       0      2    2008        WD         Normal     208500  \n",
       "1       0      5    2007        WD         Normal     181500  \n",
       "2       0      9    2008        WD         Normal     223500  \n",
       "3       0      2    2006        WD        Abnorml     140000  \n",
       "4       0     12    2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 76 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['LotFrontage',\n",
       " 'MasVnrType',\n",
       " 'MasVnrArea',\n",
       " 'BsmtQual',\n",
       " 'BsmtCond',\n",
       " 'BsmtExposure',\n",
       " 'BsmtFinType1',\n",
       " 'BsmtFinType2',\n",
       " 'Electrical',\n",
       " 'GarageType',\n",
       " 'GarageYrBlt',\n",
       " 'GarageFinish',\n",
       " 'GarageQual',\n",
       " 'GarageCond']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mis_cols = df.columns[df.isna().any()].tolist()\n",
    "mis_cols"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's impute the missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#LotFrontage\n",
    "df[\"LotFrontage\"] = df.groupby(\"Neighborhood\")[\"LotFrontage\"].transform(lambda x: x.fillna(x.median()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#MasVnrType\n",
    "df[\"MasVnrType\"] = df[\"MasVnrType\"].fillna(\"None\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#MasVnrArea\n",
    "df[\"MasVnrArea\"] = df[\"MasVnrArea\"].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#BsmtQual,BsmtCond,BsmtExposure,BsmtFinType1,BsmtFinType2\n",
    "for col in ('BsmtQual', 'BsmtCond', 'BsmtExposure', 'BsmtFinType1', 'BsmtFinType2'):\n",
    "    df[col] = df[col].fillna('None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Electrical\n",
    "df['Electrical'] = df['Electrical'].fillna(df['Electrical'].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#GarageType,GarageFinish,GarageQual,GarageCond\n",
    "for col in ('GarageType', 'GarageFinish','GarageYrBlt', 'GarageQual', 'GarageCond'):\n",
    "    df[col] = df[col].fillna('None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    2003\n",
       "1    1976\n",
       "2    2001\n",
       "3    1998\n",
       "4    2000\n",
       "Name: GarageYrBlt, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['GarageYrBlt'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"GarageYrBlt\"] = df[\"GarageYrBlt\"].fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EDA\n",
    "\n",
    "Let's analyze the target varibale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "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",
       "max      755000.000000\n",
       "Name: SalePrice, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Getting Description\n",
    "df['SalePrice'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " mu = 180921.20 and sigma = 79415.29\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skewness: 1.882876\n",
      "Kurtosis: 6.536282\n"
     ]
    }
   ],
   "source": [
    "# Plot Histogram\n",
    "sns.distplot(df['SalePrice'] , fit=norm);\n",
    "\n",
    "# Get the fitted parameters used by the function\n",
    "(mu, sigma) = norm.fit(df['SalePrice'])\n",
    "print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
    "plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
    "            loc='best')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('SalePrice distribution')\n",
    "\n",
    "fig = plt.figure()\n",
    "res = stats.probplot(df['SalePrice'], plot=plt)\n",
    "plt.show()\n",
    "\n",
    "print(\"Skewness: %f\" % df['SalePrice'].skew())\n",
    "print(\"Kurtosis: %f\" % df['SalePrice'].kurt())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multivariate Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['MSZoning', 'Street', 'LotShape', 'LandContour', 'Utilities',\n",
       "       'LotConfig', 'LandSlope', 'Neighborhood', 'Condition1', 'Condition2',\n",
       "       'BldgType', 'HouseStyle', 'RoofStyle', 'RoofMatl', 'Exterior1st',\n",
       "       'Exterior2nd', 'MasVnrType', 'ExterQual', 'ExterCond', 'Foundation',\n",
       "       'BsmtQual', 'BsmtCond', 'BsmtExposure', 'BsmtFinType1', 'BsmtFinType2',\n",
       "       'Heating', 'HeatingQC', 'CentralAir', 'Electrical', 'KitchenQual',\n",
       "       'Functional', 'GarageType', 'GarageYrBlt', 'GarageFinish', 'GarageQual',\n",
       "       'GarageCond', 'PavedDrive', 'SaleType', 'SaleCondition'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking Categorical Data\n",
    "df.select_dtypes(include=['object']).columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Id', 'MSSubClass', 'LotFrontage', 'LotArea', 'OverallQual',\n",
       "       'OverallCond', 'YearBuilt', 'YearRemodAdd', 'MasVnrArea', 'BsmtFinSF1',\n",
       "       'BsmtFinSF2', 'BsmtUnfSF', 'TotalBsmtSF', '1stFlrSF', '2ndFlrSF',\n",
       "       'LowQualFinSF', 'GrLivArea', 'BsmtFullBath', 'BsmtHalfBath', 'FullBath',\n",
       "       'HalfBath', 'BedroomAbvGr', 'KitchenAbvGr', 'TotRmsAbvGrd',\n",
       "       'Fireplaces', 'GarageCars', 'GarageArea', 'WoodDeckSF', 'OpenPorchSF',\n",
       "       'EnclosedPorch', '3SsnPorch', 'ScreenPorch', 'PoolArea', 'MiscVal',\n",
       "       'MoSold', 'YrSold', 'SalePrice'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking Numerical Data\n",
    "df.select_dtypes(include=['int64','float64']).columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Features:  39 categorical + 37 numerical = 76 features\n"
     ]
    }
   ],
   "source": [
    "cat = len(df.select_dtypes(include=['object']).columns)\n",
    "num = len(df.select_dtypes(include=['int64','float64']).columns)\n",
    "print('Total Features: ', cat, 'categorical', '+',\n",
    "      num, 'numerical', '=', cat+num, 'features')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's use Correlation Matrix to extract the useful features to help with our prediction model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Correlation Matrix Heatmap\n",
    "corrmat = df.corr()\n",
    "f, ax = plt.subplots(figsize=(12, 9))\n",
    "sns.heatmap(corrmat, vmax=.8, square=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Top 10 Heatmap\n",
    "k = 10 #number of variables for heatmap\n",
    "cols = corrmat.nlargest(k, 'SalePrice')['SalePrice'].index\n",
    "cm = np.corrcoef(df[cols].values.T)\n",
    "sns.set(font_scale=1.25)\n",
    "hm = sns.heatmap(cm, cbar=True, annot=True, square=True, fmt='.2f', annot_kws={'size': 10}, yticklabels=cols.values, xticklabels=cols.values)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Most Correlated Features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SalePrice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OverallQual</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>GrLivArea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>GarageCars</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>GarageArea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>TotalBsmtSF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1stFlrSF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>FullBath</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>TotRmsAbvGrd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>YearBuilt</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Most Correlated Features\n",
       "0                SalePrice\n",
       "1              OverallQual\n",
       "2                GrLivArea\n",
       "3               GarageCars\n",
       "4               GarageArea\n",
       "5              TotalBsmtSF\n",
       "6                 1stFlrSF\n",
       "7                 FullBath\n",
       "8             TotRmsAbvGrd\n",
       "9                YearBuilt"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most_corr = pd.DataFrame(cols)\n",
    "most_corr.columns = ['Most Correlated Features']\n",
    "most_corr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ofcourse most correlated feature of SalePrice is SalePrice. Let's visualize the rest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Overall Quality vs Sale Price\n",
    "var = 'OverallQual'\n",
    "data = pd.concat([df['SalePrice'], df[var]], axis=1)\n",
    "f, ax = plt.subplots(figsize=(8, 6))\n",
    "fig = sns.boxplot(x=var, y=\"SalePrice\", data=data)\n",
    "fig.axis(ymin=0, ymax=800000);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Better quality houses fetch better prices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7ff22a25dd10>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Living Area vs Sale Price\n",
    "sns.jointplot(x=df['GrLivArea'], y=df['SalePrice'], kind='reg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We shall remove the outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing outliers\n",
    "df = df.drop(df[(df['GrLivArea']>4000) \n",
    "                         & (df['SalePrice']<300000)].index).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7ff22a8452d0>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Living Area vs Sale Price\n",
    "sns.jointplot(x=df['GrLivArea'], y=df['SalePrice'], kind='reg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff22acd02d0>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Garage Area vs Sale Price\n",
    "sns.boxplot(x=df['GarageCars'], y=df['SalePrice'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4-car garages result in less Sale Price? That doesn't make much sense. Let's remove those outliers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing outliers \n",
    "df = df.drop(df[(df['GarageCars']>3) \n",
    "                         & (df['SalePrice']<300000)].index).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff22ad79350>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Garage Area vs Sale Price\n",
    "sns.boxplot(x=df['GarageCars'], y=df['SalePrice'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7ff22ad6f650>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Garage Area vs Sale Price\n",
    "sns.jointplot(x=df['GarageArea'], y=df['SalePrice'], kind='reg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again with the bottom two data-points. Let's remove those outliers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing outliers manually (More than 1000 sqft, less than $300k)\n",
    "df = df.drop(df[(df['GarageArea']>1000) \n",
    "                         & (df['SalePrice']<300000)].index).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7ff22ad81b50>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Garage Area vs Sale Price\n",
    "sns.jointplot(x=df['GarageArea'], y=df['SalePrice'], kind='reg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7ff229060110>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Basement Area vs Sale Price\n",
    "sns.jointplot(x=df['TotalBsmtSF'], y=df['SalePrice'], kind='reg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7ff22b629150>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# First Floor Area vs Sale Price\n",
    "sns.jointplot(x=df['1stFlrSF'], y=df['SalePrice'], kind='reg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff22bad2b50>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Total Rooms vs Sale Price\n",
    "sns.boxplot(x=df['TotRmsAbvGrd'], y=df['SalePrice'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " Houses with more than 11 room seems like an outlier due to lesser price than 11 room house. Let's fix that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing outliers \n",
    "df = df.drop(df[(df['TotRmsAbvGrd']>11)].index).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff22bde1950>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Total Rooms vs Sale Price\n",
    "sns.boxplot(x=df['TotRmsAbvGrd'], y=df['SalePrice'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### FEATURE ENGINEERING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1438 entries, 0 to 1437\n",
      "Data columns (total 76 columns):\n",
      "Id               1438 non-null int64\n",
      "MSSubClass       1438 non-null int64\n",
      "MSZoning         1438 non-null object\n",
      "LotFrontage      1438 non-null float64\n",
      "LotArea          1438 non-null int64\n",
      "Street           1438 non-null object\n",
      "LotShape         1438 non-null object\n",
      "LandContour      1438 non-null object\n",
      "Utilities        1438 non-null object\n",
      "LotConfig        1438 non-null object\n",
      "LandSlope        1438 non-null object\n",
      "Neighborhood     1438 non-null object\n",
      "Condition1       1438 non-null object\n",
      "Condition2       1438 non-null object\n",
      "BldgType         1438 non-null object\n",
      "HouseStyle       1438 non-null object\n",
      "OverallQual      1438 non-null int64\n",
      "OverallCond      1438 non-null int64\n",
      "YearBuilt        1438 non-null int64\n",
      "YearRemodAdd     1438 non-null int64\n",
      "RoofStyle        1438 non-null object\n",
      "RoofMatl         1438 non-null object\n",
      "Exterior1st      1438 non-null object\n",
      "Exterior2nd      1438 non-null object\n",
      "MasVnrType       1438 non-null object\n",
      "MasVnrArea       1438 non-null float64\n",
      "ExterQual        1438 non-null object\n",
      "ExterCond        1438 non-null object\n",
      "Foundation       1438 non-null object\n",
      "BsmtQual         1438 non-null object\n",
      "BsmtCond         1438 non-null object\n",
      "BsmtExposure     1438 non-null object\n",
      "BsmtFinType1     1438 non-null object\n",
      "BsmtFinSF1       1438 non-null int64\n",
      "BsmtFinType2     1438 non-null object\n",
      "BsmtFinSF2       1438 non-null int64\n",
      "BsmtUnfSF        1438 non-null int64\n",
      "TotalBsmtSF      1438 non-null int64\n",
      "Heating          1438 non-null object\n",
      "HeatingQC        1438 non-null object\n",
      "CentralAir       1438 non-null object\n",
      "Electrical       1438 non-null object\n",
      "1stFlrSF         1438 non-null int64\n",
      "2ndFlrSF         1438 non-null int64\n",
      "LowQualFinSF     1438 non-null int64\n",
      "GrLivArea        1438 non-null int64\n",
      "BsmtFullBath     1438 non-null int64\n",
      "BsmtHalfBath     1438 non-null int64\n",
      "FullBath         1438 non-null int64\n",
      "HalfBath         1438 non-null int64\n",
      "BedroomAbvGr     1438 non-null int64\n",
      "KitchenAbvGr     1438 non-null int64\n",
      "KitchenQual      1438 non-null object\n",
      "TotRmsAbvGrd     1438 non-null int64\n",
      "Functional       1438 non-null object\n",
      "Fireplaces       1438 non-null int64\n",
      "GarageType       1438 non-null object\n",
      "GarageYrBlt      1438 non-null object\n",
      "GarageFinish     1438 non-null object\n",
      "GarageCars       1438 non-null int64\n",
      "GarageArea       1438 non-null int64\n",
      "GarageQual       1438 non-null object\n",
      "GarageCond       1438 non-null object\n",
      "PavedDrive       1438 non-null object\n",
      "WoodDeckSF       1438 non-null int64\n",
      "OpenPorchSF      1438 non-null int64\n",
      "EnclosedPorch    1438 non-null int64\n",
      "3SsnPorch        1438 non-null int64\n",
      "ScreenPorch      1438 non-null int64\n",
      "PoolArea         1438 non-null int64\n",
      "MiscVal          1438 non-null int64\n",
      "MoSold           1438 non-null int64\n",
      "YrSold           1438 non-null int64\n",
      "SaleType         1438 non-null object\n",
      "SaleCondition    1438 non-null object\n",
      "SalePrice        1438 non-null int64\n",
      "dtypes: float64(2), int64(35), object(39)\n",
      "memory usage: 853.9+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "#MSSubClass =The building class\n",
    "df['MSSubClass'] = df['MSSubClass'].apply(str)\n",
    "\n",
    "#Changing OverallCond into a categorical variable\n",
    "df['OverallCond'] = df['OverallCond'].astype(str)\n",
    "\n",
    "#Year and month sold are transformed into categorical features.\n",
    "df['YrSold'] = df['YrSold'].astype(str)\n",
    "df['MoSold'] = df['MoSold'].astype(str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's do LabelEncoding for categorical variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape all_data: (1438, 76)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "cols = ('BsmtQual', 'BsmtCond', 'GarageQual', 'GarageCond', \n",
    "        'ExterQual', 'ExterCond','HeatingQC', 'KitchenQual', 'BsmtFinType1', \n",
    "        'BsmtFinType2', 'Functional', 'BsmtExposure', 'GarageFinish', 'LandSlope',\n",
    "        'LotShape', 'PavedDrive', 'Street', 'CentralAir', 'MSSubClass', 'OverallCond', \n",
    "        'YrSold', 'MoSold')\n",
    "# Process columns and apply LabelEncoder to categorical features\n",
    "for c in cols:\n",
    "    lbl = LabelEncoder() \n",
    "    lbl.fit(list(df[c].values)) \n",
    "    df[c] = lbl.transform(list(df[c].values))\n",
    "\n",
    "# Check shape        \n",
    "print('Shape all_data: {}'.format(df.shape))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Adding Total Square Feet feature \n",
    "df['TotalSF'] = df['TotalBsmtSF'] + df['1stFlrSF'] + df['2ndFlrSF']"
   ]
  },
  {
   "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>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>...</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>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "      <th>TotalSF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "      <td>2566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "      <td>2524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "      <td>2706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "      <td>2473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "      <td>3343</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 77 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea  Street  LotShape  \\\n",
       "0   1           9       RL         65.0     8450       1         3   \n",
       "1   2           4       RL         80.0     9600       1         3   \n",
       "2   3           9       RL         68.0    11250       1         0   \n",
       "3   4          10       RL         60.0     9550       1         0   \n",
       "4   5           9       RL         84.0    14260       1         0   \n",
       "\n",
       "  LandContour Utilities LotConfig  ...  3SsnPorch ScreenPorch PoolArea  \\\n",
       "0         Lvl    AllPub    Inside  ...          0           0        0   \n",
       "1         Lvl    AllPub       FR2  ...          0           0        0   \n",
       "2         Lvl    AllPub    Inside  ...          0           0        0   \n",
       "3         Lvl    AllPub    Corner  ...          0           0        0   \n",
       "4         Lvl    AllPub       FR2  ...          0           0        0   \n",
       "\n",
       "  MiscVal MoSold YrSold  SaleType  SaleCondition  SalePrice  TotalSF  \n",
       "0       0      4      2        WD         Normal     208500     2566  \n",
       "1       0      7      1        WD         Normal     181500     2524  \n",
       "2       0     11      2        WD         Normal     223500     2706  \n",
       "3       0      4      0        WD        Abnorml     140000     2473  \n",
       "4       0      3      2        WD         Normal     250000     3343  \n",
       "\n",
       "[5 rows x 77 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " mu = 12.02 and sigma = 0.40\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skewness: 0.102676\n",
      "Kurtosis: 0.790010\n"
     ]
    }
   ],
   "source": [
    "# We use the numpy fuction log1p which  applies log(1+x) to all elements of the column\n",
    "df[\"SalePrice\"] = np.log1p(df[\"SalePrice\"])\n",
    "\n",
    "#Check the new distribution \n",
    "sns.distplot(df['SalePrice'] , fit=norm);\n",
    "\n",
    "# Get the fitted parameters used by the function\n",
    "(mu, sigma) = norm.fit(df['SalePrice'])\n",
    "print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
    "plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
    "            loc='best')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('SalePrice distribution')\n",
    "\n",
    "fig = plt.figure()\n",
    "res = stats.probplot(df['SalePrice'], plot=plt)\n",
    "plt.show()\n",
    "\n",
    "y_train = df.SalePrice.values\n",
    "\n",
    "print(\"Skewness: %f\" % df['SalePrice'].skew())\n",
    "print(\"Kurtosis: %f\" % df['SalePrice'].kurt())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>Skewed Features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MiscVal</th>\n",
       "      <td>29.601711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PoolArea</th>\n",
       "      <td>17.317532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LotArea</th>\n",
       "      <td>12.809535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SsnPorch</th>\n",
       "      <td>10.213800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <td>10.034758</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Skewed Features\n",
       "MiscVal             29.601711\n",
       "PoolArea            17.317532\n",
       "LotArea             12.809535\n",
       "3SsnPorch           10.213800\n",
       "LowQualFinSF        10.034758"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import skew\n",
    "\n",
    "numeric_feats = df.dtypes[df.dtypes != \"object\"].index\n",
    "\n",
    "# Check the skew of all numerical features\n",
    "skewed_feats = df[numeric_feats].apply(lambda x: skew(x.dropna())).sort_values(ascending=False)\n",
    "skewness = pd.DataFrame({'Skewed Features' :skewed_feats})\n",
    "skewness.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 56 skewed numerical features to Box Cox transform\n"
     ]
    }
   ],
   "source": [
    "skewness = skewness[abs(skewness) > 0.75]\n",
    "print(\"There are {} skewed numerical features to Box Cox transform\".format(skewness.shape[0]))\n",
    "\n",
    "from scipy.special import boxcox1p\n",
    "skewed_features = skewness.index\n",
    "lam = 0.15\n",
    "for feat in skewed_features:\n",
    "    df[feat] = boxcox1p(df[feat], lam)\n",
    "    df[feat] += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1438, 311)\n"
     ]
    }
   ],
   "source": [
    "df = pd.get_dummies(df)\n",
    "print(df.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MODEL BUILDING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Let's drop ID\n",
    "df.drop(\"Id\", axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's split SalePrice from the dataframe as we have to predict that"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop('SalePrice',axis=1)\n",
    "y = df['SalePrice']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import KFold, cross_val_score, train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "lm = LinearRegression()\n",
    "lm.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = lm.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 16977666.266394697\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "print('RMSE:', np.sqrt(mean_squared_error(y_test, predictions)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We shall consider lesser columns and see how it performs.\n",
    "\n",
    "Let's consider only the top 10 features we established before."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = df[most_corr['Most Correlated Features']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = train.drop('SalePrice',axis=1)\n",
    "y = train['SalePrice']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import KFold, cross_val_score, train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "lm = LinearRegression()\n",
    "lm.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = lm.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.01823439885815228\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "print('RMSE:', np.sqrt(mean_squared_error(y_test, predictions)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, LinearRegression Model performs poorly for higher dimension data. We can use Ensemble learning methods to tackle this problem which you'll see in the next notebook."
   ]
  }
 ],
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