Pandas analogue to SQL MINUS / EXCEPT operator, using multiple columns

Question

I\'m looking for the fastest and idiomatic analog to SQL MINUS (AKA EXCEPT) operator.

Here is what I mean - given two Pandas DataFrames as follows:

I         


        

Answer 1

One possible solution with merge and indicator=True:

df = (d1.reset_index()
        .merge(d2, on=['a','b'], indicator=True, how='outer', suffixes=('','_'))
        .query('_merge == "left_only"')
        .set_index('index')
        .rename_axis(None)
        .reindex(d1.columns, axis=1))
print (df)
   a  b  c
1  0  1  2
2  1  0  3
6  2  2  7

Solution with isin:

df = d1[~d1.set_index(["a", "b"]).index.isin(d2.set_index(["a","b"]).index)]
print (df)
   a  b  c
1  0  1  2
2  1  0  3
6  2  2  7