Custom Function as Lambda

import numpy as np
import pandas as pd
def apply_math_special(row):
    return (row.maths *2 + (row.language/2) + (row.history/3) + (row.science/4))
df = pd.read_csv('abc.csv')
df
student language science maths history
0 kumar 90 56 34 34
1 kevin 10 34 32 67
2 sammy 90 23 12 32
3 janice 20 67 90 45
4 peter 30 56 45 65
5 prem 90 45 45 34
6 carrol 50 90 45 23 
df['math_special'] = df.apply(apply_math_special, axis=1).astype(int)
df
student language science maths history math_special
0 kumar 90 56 34 34 138
1 kevin 10 34 32 67 99
2 sammy 90 23 12 32 85
3 janice 20 67 90 45 221
4 peter 30 56 45 65 140
5 prem 90 45 45 34 157
6 carrol 50 90 45 23 145
What did we do?

We just doubled the math marks and reduced the marks of other subjects by 2, 3, 4 and then assigned the new value as a new column