Import pandas library, because the data pre processing is mostly done by using pandas function.

  Read the sample data.

  Make it as a data frame.

  Find the missing value and drop those samples using pandas inbuilt functions,df.isnull() and df.dropna().

  Whenever we using isnull(),it finds missing values in the data set.

  Whenever we using dropna(),it drop entire sample in a data set.

#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())

#Drop the missing values(Nan)

print(“Drop missing values”)

print(df.dropna())