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census A and census B that are most likely duplicates. 3. Extract one of the index columns,subsetting its associated DataFrame to filter for duplicates. matches = potential_matches[potential_matches.sum(axis =1) >=3] print(matches) 4. Here we choose the second index column, which represents row