pandas.testing.assert_frame_equal

pandas.testing.assert_frame_equal(left, right, check_dtype=True, check_index_type='equiv', check_column_type='equiv', check_frame_type=True, check_less_precise=False, check_names=True, by_blocks=False, check_exact=False, check_datetimelike_compat=False, check_categorical=True, check_like=False, obj='DataFrame') [source]

Check that left and right DataFrame are equal.

Parameters:

left : DataFrame right : DataFrame check_dtype : bool, default True Whether to check the DataFrame dtype is identical. check_index_type : bool / string {‘equiv’}, default False Whether to check the Index class, dtype and inferred_type are identical. check_column_type : bool / string {‘equiv’}, default False Whether to check the columns class, dtype and inferred_type are identical. check_frame_type : bool, default False Whether to check the DataFrame class is identical. check_less_precise : bool or int, default False Specify comparison precision. Only used when check_exact is False. 5 digits (False) or 3 digits (True) after decimal points are compared. If int, then specify the digits to compare check_names : bool, default True Whether to check the Index names attribute. by_blocks : bool, default False Specify how to compare internal data. If False, compare by columns. If True, compare by blocks. check_exact : bool, default False Whether to compare number exactly. check_datetimelike_compat : bool, default False Compare datetime-like which is comparable ignoring dtype. check_categorical : bool, default True Whether to compare internal Categorical exactly. check_like : bool, default False If true, ignore the order of rows & columns obj : str, default ‘DataFrame’ Specify object name being compared, internally used to show appropriate assertion message