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

I'm sure this isn't as fast as the solutions using Pandas or Numpy operations, but if you don't want to rewrite your function you can use map. Using the original example data -

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'] = list(map(get_sublist,df['col_1'],df['col_2']))
#In Python 2 don't convert above to list

We could pass as many arguments as we wanted into the function this way. The output is what we wanted

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]