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Currently, some tests in feathub verify a pandas DataFrame as follows.
self.assertTrue(expected_df.equals(result_df)
Such implementation cannot work in certain cases. For example, if an element in the two DataFrames is a dict whose order of entries is different, they are supposed to pass the test, while the current implementation fails in this case.
Thus we should use a better way to verify DataFrames.
The text was updated successfully, but these errors were encountered:
Currently, some tests in feathub verify a pandas DataFrame as follows.
Such implementation cannot work in certain cases. For example, if an element in the two DataFrames is a dict whose order of entries is different, they are supposed to pass the test, while the current implementation fails in this case.
Thus we should use a better way to verify DataFrames.
The text was updated successfully, but these errors were encountered: