# pandas.testing.assert_series_equal

`pandas.testing.``assert_series_equal`(left, right, check_dtype=True, check_index_type='equiv', check_series_type=True, check_less_precise=False, check_names=True, check_exact=False, check_datetimelike_compat=False, check_categorical=True, obj='Series')

  Check that left and right Series are equal.

  Parameters:

  left : Series

  right : Series

  check_dtype : bool, default True

  > Whether to check the Series dtype is identical.

  check_index_type : bool / string {‘equiv’}, default ‘equiv’

  > Whether to check the Index class, dtype and inferred_type are identical.

  check_series_type : bool, default True

  > Whether to check the Series 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_exact : bool, default False

  > Whether to compare number exactly.

  check_names : bool, default True

  > Whether to check the Series and Index names attribute.

  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.

  obj : str, default ‘Series’

  > Specify object name being compared, internally used to show appropriate assertion message

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