Aniruddha Bhandari aniruddha27

Data Engineer

aniruddha27 / House_Price_14.py

Last active March 16, 2020 09:54

	# Ordinal features
	#NA means no Pool
	train['PoolQC'].replace(['Ex','Gd','TA','Fa',np.nan],[4,3,2,1,0],inplace=True)

	# NA means no fence
	train['Fence'].replace(['GdPrv','MnPrv','GdWo','MnWw',np.nan],[4,3,2,1,0],inplace=True)

	# NA means no fireplace
	train['FireplaceQu'].replace(['Ex','Gd','TA','Fa','Po',np.nan],[5,4,3,2,1,0],inplace=True)

aniruddha27 / House_Price_15.py

Created March 16, 2020 09:55

	# Ordinal features
	for i in ['GarageCond','GarageQual']:
	train[i].replace(['Ex','Gd','TA','Fa','Po',np.nan],[5,4,3,2,1,0],inplace=True)

	# Nominal features
	for i in ['GarageFinish','GarageType']:
	train[i].fillna('None',inplace=True)

	# Numerical features
	for i in ['GarageYrBlt','GarageCars','GarageArea']:

aniruddha27 / House_Price_16.py

Created March 16, 2020 09:58

	# Ordinal features
	for i in ['BsmtCond','BsmtQual']:
	train[i].replace(['Ex','Gd','TA','Fa','Po',np.nan],[5,4,3,2,1,0],inplace=True)

	train['BsmtExposure'].replace(['Gd','Av','Mn','No',np.nan],[4,3,2,1,0],inplace=True)

	for i in ['BsmtFinType1','BsmtFinType2']:
	train[i].replace(['GLQ','ALQ','BLQ','Rec','LwQ','Unf',np.nan],[6,5,4,3,2,1,0],inplace=True)

	# Numerical features

aniruddha27 / House_Price_17.py

Created March 16, 2020 10:00

	#NA means no masonary work
	train['MasVnrType'].fillna('None',inplace=True)

	#If no masonary work, then area is 0
	train['MasVnrArea'].fillna(0,inplace=True)

	#Replace with the most common value
	for i in ['MSZoning','Utilities']:
	train[i].fillna(train[i].mode()[0],inplace=True)

aniruddha27 / House_Price_18.py

Created March 16, 2020 10:02

	# Ordinal features
	train['CentralAir'].replace(['N','Y'],[0,1],inplace=True)
	# Nominal features
	for i in ['HeatingQC','ExterCond','ExterQual']:
	train[i].replace(['Ex','Gd','TA','Fa','Po'],[4,3,2,1,0],inplace=True)

aniruddha27 / House_Price_19.py

Created March 16, 2020 10:03

	train['HasPool'] = train['PoolArea'].apply(lambda x: 1 if x>0 else 0)
	train['HasFirePlace'] = train['FireplaceQu'].apply(lambda x: 1 if x>0 else 0)
	train['HasFence'] = train['Fence'].apply(lambda x: 1 if x>0 else 0)
	train['HasMsonary'] = train['MasVnrArea'].apply(lambda x: 1 if x>0 else 0)
	train['HasGarage'] = train['GarageArea'].apply(lambda x: 1 if x>0 else 0)
	train['HasBsmt'] = train['TotalBsmtSF'].apply(lambda x: 1 if x>0 else 0)

aniruddha27 / House_Price_20.py

Created March 16, 2020 10:04

	# Total surface area of house
	train['TotalSF'] = train.apply(lambda x: x['1stFlrSF'] + x['2ndFlrSF'] + x['TotalBsmtSF'], axis=1)

aniruddha27 / House_Price_21.py

Last active March 16, 2020 10:05

	# Total number of bathrooms in the house
	train['TotalBath'] = train.apply(lambda x: x['FullBath'] + 0.5x['HalfBath'] + x['BsmtFullBath'] + 0.5x['BsmtHalfBath'], axis=1)

aniruddha27 / House_Price_22.py

Last active March 16, 2020 11:12

	# One-Hot encoding
	train = pd.get_dummies(train,drop_first=True)
	train.head()

aniruddha27 / House_Price_23.py

Created March 16, 2020 11:13