How to apply a function to two columns of Pandas dataframe

Question

Suppose I have a df which has columns of \'ID\', \'col_1\', \'col_2\'. And I define a function :

f = lambda x, y : my_function_expres

Answer 1

There is a clean, one-line way of doing this in Pandas:

df['col_3'] = df.apply(lambda x: f(x.col_1, x.col_2), axis=1)

This allows f to be a user-defined function with multiple input values, and uses (safe) column names rather than (unsafe) numeric indices to access the columns.

Example with data (based on original question):

import pandas as pd

df = pd.DataFrame({'ID':['1', '2', '3'], 'col_1': [0, 2, 3], 'col_2':[1, 4, 5]})
mylist = ['a', 'b', 'c', 'd', 'e', 'f']

def get_sublist(sta,end):
    return mylist[sta:end+1]

df['col_3'] = df.apply(lambda x: get_sublist(x.col_1, x.col_2), axis=1)

Output of print(df):

  ID  col_1  col_2      col_3
0  1      0      1     [a, b]
1  2      2      4  [c, d, e]
2  3      3      5  [d, e, f]

If your column names contain spaces or share a name with an existing dataframe attribute, you can index with square brackets:

df['col_3'] = df.apply(lambda x: f(x['col 1'], x['col 2']), axis=1)