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')[source]

Check that left and right Series are equal.

check_dtypebool, default True

Whether to check the Series dtype is identical.

check_index_typebool / string {‘equiv’}, default ‘equiv’

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

check_series_typebool, default True

Whether to check the Series class is identical.

check_less_precisebool 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.

When comparing two numbers, if the first number has magnitude less than 1e-5, we compare the two numbers directly and check whether they are equivalent within the specified precision. Otherwise, we compare the ratio of the second number to the first number and check whether it is equivalent to 1 within the specified precision.

check_namesbool, default True

Whether to check the Series and Index names attribute.

check_exactbool, default False

Whether to compare number exactly.

check_datetimelike_compatbool, default False

Compare datetime-like which is comparable ignoring dtype.

check_categoricalbool, default True

Whether to compare internal Categorical exactly.

objstr, default ‘Series’

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

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