Input −
Assume you have a DataFrame, and the result for shifting the first column and fill the missing values are,
one two three 0 1 10 100 1 2 20 200 2 3 30 300 enter the value 15 one two three 0 15 1 10 1 15 2 20 2 15 3 30
Solution
To solve this, we will follow the below approach.
Define a DataFrame
Shift the first column using below code,
data.shift(periods=1,axis=1)
Get the value from user and verify if it is divisible by 3 and 5. If the result is true then fill missing value, otherwise fill NaN. It is defined below,
user_input = int(input("enter the value"))
if(user_input%3==0 and user_input%5==0):
print(data.shift(periods=1,axis=1,fill_value=user_input))
else:
print(data.shift(periods=1,axis=1))Example
Let us see the complete implementation to get better understanding −
import pandas as pd
data= pd.DataFrame({'one': [1,2,3],
'two': [10,20,30],
'three': [100,200,300]})
print(data)
user_input = int(input("enter the value"))
if(user_input%3==0 and user_input%5==0):
print(data.shift(periods=1,axis=1,fill_value=user_input))
else:
print(data.shift(periods=1,axis=1))Output 1
one two three 0 1 10 100 1 2 20 200 2 3 30 300 enter the value 15 one two three 0 15 1 10 1 15 2 20 2 15 3 30
Output 2
one two three 0 1 10 100 1 2 20 200 2 3 30 300 enter the value 3 one two three 0 NaN 1.0 10.0 1 NaN 2.0 20.0 2 NaN 3.0 30.0