pandas indexing using multiple isin clauses

Question

If I want to do is-in testing on multiple columns at once, I can do:

>>> from pandas import DataFrame
>>> df = DataFrame({\'A\': [1, 2, 3]         


        

Answer 1

You could put both conditions in as a mask and use &:

In [12]:

df[(df['A'].isin([1,3])) & (df['B'].isin([4,7,12]))]
Out[12]:
   A  B   C
2  3  7  18

Here the conditions require parentheses () around them due to operator precedence

Slightly more readable is to use query:

In [15]:

df.query('A in [1,3] and B in [4,7,12]')
Out[15]:
   A  B   C
2  3  7  18