Import pandas library.

  Read the sample data set.

  Find the missing values in the data set.

  Replace the missing values by using pad() and bfill().

#import libraries

import pandas as pd

#Read the sample data

data=pd.read_csv(‘/home/soft27/soft27

/Sathish/Pythonfiles/Houseprice.csv’)

#create data frame

df=pd.DataFrame(data)

print(“Actual data frame is:\n”,df)

#Find the missing values

print(“Find missing values”)

print(df.isnull())

#Replace the missing values(Nan) using forward

print(“Replace the Nan values”)

print(df.fillna(method=’pad’))

#Replace the missing values(Nan) using backward

print(df.fillna(method=’bfill’))