Import pandas library.

   Read the sample data.

   Make it as a data frame.

   Use fillna() to replace Nan value.

#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)

print(“Replace the Nan values”)

print(df.fillna(0))