Applying function with multiple arguments to create a new pandas column

Question

I want to create a new column in a pandas data frame by applying a function to two existing columns. Following this answer I've been able to create a new column when I only need one column as an argument:

import pandas as pd df = pd.DataFrame({"A": [10,20,30], "B": [20, 30, 10]})  def fx(x):     return x * x  print(df) df['newcolumn'] = df.A.apply(fx) print(df) 

However, I cannot figure out how to do the same thing when the function requires multiple arguments. For example, how do I create a new column by passing column A and column B to the function below?

def fxy(x, y):     return x * y 

Answer 1

You can go with @greenAfrican example, if it's possible for you to rewrite your function. But if you don't want to rewrite your function, you can wrap it into anonymous function inside apply, like this:

>>> def fxy(x, y): ...     return x * y  >>> df['newcolumn'] = df.apply(lambda x: fxy(x['A'], x['B']), axis=1) >>> df     A   B  newcolumn 0  10  20        200 1  20  30        600 2  30  10        300