How Can I Apply a Function Element-Wise to Multiple Pandas DataFrame Columns?

Pandas: Applying Functions to Multiple Columns

Problem:

Given a function and a Pandas DataFrame with multiple columns, how can we apply the function element-wise to each pair of corresponding values in the columns?

Solution:

There is an efficient way to achieve this using Pandas' lambda function and apply method:

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)

This applies the get_sublist function to each row of the DataFrame, using the values in the 'col_1' and 'col_2' columns as inputs. The result is a new column, 'col_3', containing the calculated sublists.

Usage:

Consider the following example:

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

# Apply the function and create a new column
df['col_3'] = df.apply(lambda x: get_sublist(x.col_1, x.col_2), axis=1)

print(df)

Output:

  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']

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