In this article, I will explain how to return multiple columns from the pandas apply() function.
1. Quick Examples
# Example 1 - Reurn multiple columns from apply()
def multiply(row):
row['A1'] = row[0] * 2
row['B1'] = row[1] * 3
row['C1'] = row[2] * 4
return row
df = df.apply(multiply, axis=1)
print(df)
Let’s create a sample DataFrame to work with some examples.
import pandas as pd
import numpy as np
data = [(3,5,7), (2,4,6),(5,8,9)]
df = pd.DataFrame(data, columns = ['A','B','C'])
print(df)
Yields below output.
A B C
0 3 5 7
1 2 4 6
2 5 8 9
2. Return Multiple Columns from pandas apply()
You can return a Series from the apply() function that contains the new data. pass axis=1 to the apply() function which applies the function multiply to each row of the DataFrame, Returns a series of multiple columns from pandas apply() function. This series, row, contains the new values, as well as the original data.
# Reurn multiple columns from apply()
def multiply(row):
row['A1'] = row[0] * 2
row['B1'] = row[1] * 3
row['C1'] = row[2] * 4
return row
df = df.apply(multiply, axis=1)
print(df)
Yields below output. This returns multiple columns ‘A1’, ‘B1’ and ‘C1’ from pandas apply() function.
A B C A1 B1 C1
0 3 5 7 6 15 28
1 2 4 6 4 12 24
2 5 8 9 10 24 36
Happy Learning !!
