Python: Why Is Np.where Not Working With Two Conditions?

I have the following data frame: >>> import pandas as pd >>> import numpy as np >>> df_test = pd.DataFrame({'id': [100, 101, 102, 103, 104], 'drive': ['4

Solution 1:

Add parentheses because priority precedence of | operator (bitwise OR):

df_test['is_4x4'] = np.where(pd.isnull(df_test['drive']) | (df_test['drive'] == '2WD'), 0, 1)

Or use Series.eq:

df_test['is_4x4'] = np.where(df_test['drive'].isna() | df_test['drive'].eq('2WD'), 0, 1)

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You can check docs - 6.16. Operator precedence where see | have higher priority as ==:

Operator                                Description

lambda                                  Lambda expression
if – else                               Conditional expression
or                                      Boolean OR
and                                     Boolean AND
not x                                   Boolean NOT
in, not in, is, is not,                 Comparisons, including membership tests    
<, <=, >, >=, !=, ==                    and identity tests
|                                       Bitwise OR
^                                       Bitwise XOR
&                                       Bitwise AND

(expressions...), [expressions...],     Binding or tuple display, list display,       
{key: value...}, {expressions...}       dictionary display, set display