Crib Notes: How to Apply a User Defined Function to Multiple Columns in a Pandas Data Frame

Let’s start with a data frame that has two columns:

import pandas as pd
df = pd.DataFrame({'A' : [1,2,4], 'B' : [2,2,2]})

The data frame df.

Then:

1. We define a function, doSomething, that has two inputs, x and y.

def doSomething(x, y):
     returnValue = float(x*y) + 13
     return returnValue

2. Apply the function to the two columns , A and B, of the data frame df .

df[['A', 'B]].apply(lambda x: doSomething(*x), axis = 1)

3. Save the function output into a new column, column C.

df['C'] = df[['A', 'B]].apply(lambda x: doSomething(*x), axis = 1)

And we end up with the data frame df:

Data Frame df with the New Column, Column C