Given a dataframe Sales that store sales records of a company of past few years.

Q. Given a data-frame Sales that store sales records of a company of past few years. But the data-frame contains some missing data.

 

 
	 

 
	 
Item Type
 
	 
Sales Channel
 
	 
Order Date
 
	 
Order ID
 
	 
Total Revenue
 
	 
Total Cost
 
	 
Total Profit
 
 
 
	 
0
 
	 
Cosmetics
 
	 
Online
 
	 
5/22/2017
 
	 
8985.0
 
	 
793518.00
 
	 
477943.95
 
	 
315574.85
 
 
 
	 
1
 
	 
Cereal
 
	 
Online
 
	 
5/20/2017
 
	 
5559.0
 
	 
1780539.20
 
	 
1013704.16.
 
	 
766835.84
 
 
 
	 
2
 
	 
Personal Care
 
	 
Offline
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
 
 
	 
3
 
	 
Personal Care
 
	 
Online
 
	 
3/11/2017
 
	 
6992.0
 
	 
246415.95
 
	 
170860.05
 
	 
75555.90
 
 
 
	 
4
 
	 
Snacks
 
	 
Online
 
	 
2/25/2017
 
	 
7562.0
 
	 
1117953.66
 
	 
713942.88
 
	 
404010.78
 
 
 
	 
5
 
	 
Household
 
	 
Offline
 
	 
2/8/2017
 
	 
52284.0
 
	 
5997054.98
 
	 
4509793.96
 
	 
1487261.82
 
 
 
	 
6
 
	 
Meat
 
	 
Online
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
 
 
	 
7
 
	 
Clothes
 
	 
Online
 
	 
1/13/2017
 
	 
1873.0
 
	 
902980.64
 
	 
296145.92
 
	 
606834.72
 
 
 
	 
8
 
	 
Cosmetics
 
	 
Online
 
	 
12/31/2016
 
	 
331438481.0
 
	 
3876652.40
 
	 
2334947.11
 
	 
1541705.29
 
 
 
	 
9
 
	 
Office Supplies
 
	 
Offline
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
 
 
	 
10
 
	 
Cosmetics
 
	 
Offline
 
	 
11/19/2016
 
	 
419123971.0
 
	 
3039414.40
 
	 
1830670.16
 
	 
1208744.24
 
 
 
	 
11
 
	 
Cosmetics
 
	 
Online
 
	 
11/15/2016
 
	 
286959302.0
 
	 
2836990.80
 
	 
1708748.37
 
	 
1128242.43
 
 
 
	 
12
 
	 
Beverages
 
	 
Offline
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
	 
NaN
 
 
 
	 
13
 
	 
Clothes
 
	 
Offline
 
	 
7/25/2016
 
	 
807025039.0
 
	 
600821.44
 
	 
197048.32
 
	 
403773.12
 
 
 
	 
14
 
	 
Snacks
 
	 
Online
 
	 
6/30/2016
 
	 
795490682.0
 
	 
339490.50
 
	 
216804.00
 
	 
122686.50
 
 

Write a script that does the following:-

(i) Lists the presence of missing data in whole data-frame.

(ii) Fills the missing values with 999.

(iii) Print the data-frame after filling missing value.

Answer :-

import pandas as pd
import numpy as np.

# creation or loading of dataframe Sales
# presence of missing data element wise

print("Missing data element wise")
print((Sales.isnull() ) )
Sales Sales.fillna (999)
print("After filling missing values with 999, the dataframe is like:")
print (Sales)