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=_NoDefault.no_default, check_names=True, check_exact=False, check_datetimelike_compat=False, check_categorical=True, check_category_order=True, check_freq=True, check_flags=True, rtol=1e-05, atol=1e-08, obj='Series', *, check_index=True, check_like=False)

Check that left and right Series are equal.

Parameters

leftSeries

rightSeries

check_dtypebool, default True

Whether to check the Series dtype is identical.

check_index_typebool or {‘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.

Deprecated since version 1.1.0: Use rtol and atol instead to define relative/absolute tolerance, respectively. Similar to math.isclose().

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.

check_category_orderbool, default True

Whether to compare category order of internal Categoricals.

New in version 1.0.2.

check_freqbool, default True

Whether to check the freq attribute on a DatetimeIndex or TimedeltaIndex.

New in version 1.1.0.

check_flagsbool, default True

Whether to check the flags attribute.

New in version 1.2.0.

rtolfloat, default 1e-5

Relative tolerance. Only used when check_exact is False.

New in version 1.1.0.

atolfloat, default 1e-8

Absolute tolerance. Only used when check_exact is False.

New in version 1.1.0.

objstr, default ‘Series’

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

check_indexbool, default True

Whether to check index equivalence. If False, then compare only values.

New in version 1.3.0.

check_likebool, default False

If True, ignore the order of the index. Must be False if check_index is False. Note: same labels must be with the same data.

New in version 1.5.0.

Examples

>>> from pandas import testing as tm
>>> a = pd.Series([1, 2, 3, 4])
>>> b = pd.Series([1, 2, 3, 4])
>>> tm.assert_series_equal(a, b)