Advanced Custom Lambda

import numpy as np
import pandas as pd
# Check the student passed either math or passed at least in 2 subjects. If no condidition matched, consider them as failed
def pass_math_or_two_subjects(row):
    if(row.maths > 34):
        return 'Pass'
    if(row.language > 34 and row.science > 34):
        return 'Pass'
    return 'Fail'
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['special_result'] = df.apply(pass_math_or_two_subjects, axis=1)
df
student language science maths history special_result
0 kumar 90 56 34 34 Pass
1 kevin 10 34 32 67 Fail
2 sammy 90 23 12 32 Fail
3 janice 20 67 90 45 Pass
4 peter 30 56 45 65 Pass
5 prem 90 45 45 34 Pass
6 carrol 50 90 45 23 Pass 
# Filter those candidates whoever passed the given criteria
df_passed = df[df.apply(pass_math_or_two_subjects, axis=1) == 'Pass']
df_passed
student language science maths history special_result
0 kumar 90 56 34 34 Pass
3 janice 20 67 90 45 Pass
4 peter 30 56 45 65 Pass
5 prem 90 45 45 34 Pass
6 carrol 50 90 45 23 Pass