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CBSE Class 12 Informatics Practices Question 20 of 21

Python Pandas — II — Question 9

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Question

Question 9

Given two identical DataFrames Sales16 and Sales17. But Sales17 has some values missing. Write code so that Sales17 fills its missing values from corresponding entries of Sales16.

Solution
import pandas as pd
data_sales16 = {
    'Product': ['A', 'B', 'C', 'D'],
    'Sales': [100, 150, 120, 180]
}
Sales16 = pd.DataFrame(data_sales16)
data_sales17 = {
    'Product': ['A', 'B', 'C', 'D'],
    'Sales': [100, None, 120, None]
}
Sales17 = pd.DataFrame(data_sales17)
Sales17 = Sales16.fillna({'B': 150, 'D': 180})
print("Sales16:")
print(Sales16)
print("\nSales17 (after filling missing values):")
print(Sales17)
Output
Sales16:
  Product  Sales
0       A    100
1       B    150
2       C    120
3       D    180

Sales17 (after filling missing values):
  Product  Sales
0       A    100
1       B    150
2       C    120
3       D    180
Answer

import
pandas
as
pd
data_sales16
=
{
'Product'
: [
'A'
,
'B'
,
'C'
,
'D'
],
'Sales'
: [
100
,
150
,
120
,
180
]
}
Sales16
=
pd
.
DataFrame
(
data_sales16
)
data_sales17
=
{
'Product'
: [
'A'
,
'B'
,
'C'
,
'D'
],
'Sales'
: [
100
,
None
,
120
,
None
]
}
Sales17
=
pd
.
DataFrame
(
data_sales17
)
Sales17
=
Sales16
.
fillna
({
'B'
:
150
,
'D'
:
180
})
print
(
"Sales16:"
)
print
(
Sales16
)
print
(
"
\n
Sales17 (after filling missing values):"
)
print
(
Sales17
)
Output
Sales16:
Product Sales
0 A 100
1 B 150
2 C 120
3 D 180

Sales17 (after filling missing values):
Product Sales
0 A 100
1 B 150
2 C 120
3 D 180