Pandas DataFrame create new csv column based on two other columns

Question

I need to create a new column in a csv called BTTS, which is based on two other columns, FTHG and FTAG. If FTHG & FTAG are both greater than zero, BTTS should be 1. Otherwise it should be zero.

What's the best way to do this in pandas / numpys?

Answer 1

I'm not sure, what the best way is. But here is one solution using pandas loc method:

df.loc[((df['FTHG'] > 0) & (df['FTAG'] > 0)),'BTTS'] = 1
df['BTTS'].fillna(0, inplace=True)

Another solution using pandas apply method:

def check_greater_zero(row):
    return 1 if row['FTHG'] > 0 & row['FTAG'] > 0 else 0

df['BTTS'] = df.apply(check_greater_zero, axis=1)

EDIT:

As stated in the comments, the first, vectorized, implementation is more efficient.

Answer 2

I dont know if this is the best way to do it but this works:)

df['BTTS'] = [1 if x == y == 1 else 0 for x, y in zip(df['FTAG'], df['FTHG'])]