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 the isin conditions in &

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

You could also use query function like

c_a = [1, 3]
c_b = [4, 7, 12]
df.query('(B in @c_b) & (A in @c_a)')

   A  B   C
2  3  7  18