Nested np.where

Question

I have the following dataframe:

S A
1 1
1 0
2 1
2 0

I wanted to create a new \'Result\' column that is calculated based on the val

Answer 1

I would recommend you using numpy.select if you have very nested operations.

df = pd.DataFrame({
    "S": [1, 1, 2, 2],
    "A": [1, 0, 1, 0]
})

# you could of course combine the clause (1, 4) and (2, 3) with the '|' or operator
df['RESULT'] = np.select([
    (df.S == 1) & (df.A == 1),
    (df.S == 1) & (df.A == 0),
    (df.S == 2) & (df.A == 1),
    (df.S == 2) & (df.A == 0)
], [1, 0, 0, 1])