more debugging

        total_rows = len(sparse_df.index)

        sparse_flag = False

        colIndex = 0

        for col in sparse_df:

            column = sparse_df[col] #get series representation

            zero_count = column.value_counts()[0]

            if zero_count == total_rows:

                print("good -- one column doesn't have results")

                print("it was column %d") % (colIndex)

                sparse_flag = True

                assert NaN_count == total_rows

                assert zero_count == total_rows

                break

        colIndex+=1

        if not sparse_flag:

            print("dataset isn't sparse")

            assert sparse_flag is True