Solution

Use pd.concat followed by drop_duplicates(keep=False)

pd.concat([df1, df2, df2]).drop_duplicates(keep=False)

It looks like

   a  b
1  3  4

Explanation

pd.concat adds the two DataFrames together by appending one right after the other. if there is any overlap, it will be captured by the drop_duplicates method. However, drop_duplicates by default leaves the first observation and removes every other observation. In this case, we want every duplicate removed. Hence, the keep=False parameter which does exactly that.

A special note to the repeated df2. With only one df2 any row in df2 not in df1 won’t be considered a duplicate and will remain. This solution with only one df2 only works when df2 is a subset of df1. However, if we concat df2 twice, it is guaranteed to be a duplicate and will subsequently be removed.