pandas.testing.assert_index_equal#

pandas.testing.assert_index_equal(left, right, exact=<no_default>, check_names=True, check_exact=True, check_categorical=True, check_order=True, rtol=1e-05, atol=1e-08, obj=None, *, check_freq=<no_default>)[source]#

Check that left and right Index are equal.

This function compares two Index objects and raises an AssertionError if they are not equal. It provides fine-grained control over which attributes to check, including dtype, names, and categorical properties.

Parameters:
leftIndex

The first index to compare.

rightIndex

The second index to compare.

exactbool or {‘equiv’}, default ‘equiv’

Whether to check the Index class, dtype and inferred_type are identical. If ‘equiv’, then RangeIndex can be substituted for Index with an int64 dtype as well.

Deprecated since version 3.1.0: The default value of ‘equiv’ has been deprecated and will be changed to True in the future.

check_namesbool, default True

Whether to check the names attribute.

check_exactbool, default True

Whether to compare number exactly.

check_categoricalbool, default True

Whether to compare internal Categorical exactly.

check_orderbool, default True

Whether to compare the order of index entries as well as their values. If True, both indexes must contain the same elements, in the same order. If False, both indexes must contain the same elements, but in any order.

rtolfloat, default 1e-5

Relative tolerance. Only used when check_exact is False.

atolfloat, default 1e-8

Absolute tolerance. Only used when check_exact is False.

objstr, default ‘Index’ or ‘MultiIndex’

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

check_freqbool, default True

Whether to check the freq attribute on a DatetimeIndex or TimedeltaIndex. This check is skipped when check_order=False, as sorting does not preserve freq.

Added in version 3.1.0.

Deprecated since version 3.1.0: Currently a freq mismatch only warns; in a future version check_freq=True will be the default and mismatches will raise. Pass check_freq explicitly to silence the warning.

See also

testing.assert_series_equal

Check that two Series are equal.

testing.assert_frame_equal

Check that two DataFrames are equal.

Examples

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