Learn practical skills, build real-world projects, and advance your career

Missing Value Imputation through Simple Imputer , Column Transformer , Pipeline classes of Scikit learn.

import pandas as pd 
import numpy as np
from sklearn.impute import SimpleImputer
from sklearn.compose import ColumnTransformer
from sklearn.pipeline import Pipeline
train=pd.read_csv("E:\\folder\\house-prices-advanced-regression-techniques\\train.csv")
test=pd.read_csv("E:\\folder\\house-prices-advanced-regression-techniques\\test.csv")
train.head()
x_train=train.drop(columns=["SalePrice"])
y_train=train["SalePrice"]
x_test=test.copy()
#Numerical Columns Categorical variables 
is_null_sum=x_train.isnull().sum()
is_null_sum
Id                 0
MSSubClass         0
MSZoning           0
LotFrontage      259
LotArea            0
                ... 
MiscVal            0
MoSold             0
YrSold             0
SaleType           0
SaleCondition      0
Length: 80, dtype: int64