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# pandas.testing.assert_extension_array_equal

pandas.testing.assert_extension_array_equal(left, right, check_dtype=True, index_values=None, check_exact=<no_default>, rtol=<no_default>, atol=<no_default>, obj='ExtensionArray')

  Check that left and right ExtensionArrays are equal.

  Parameters:
    left, right ExtensionArray

      The two arrays to compare.

    check_dtype bool, default True

      Whether to check if the ExtensionArray dtypes are identical.

    index_values Index | numpy.ndarray, default None

      Optional index (shared by both left and right), used in output.

    check_exact bool, default False

      Whether to compare number exactly.

      Changed in version 2.2.0: Defaults to True for integer dtypes if none of `check_exact`, `rtol` and `atol` are specified.

    rtol float, default 1e-5

      Relative tolerance. Only used when check_exact is False.

    atol float, default 1e-8

      Absolute tolerance. Only used when check_exact is False.

    obj str, default ‘ExtensionArray’

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

      Added in version 2.0.0.

  Notes

  Missing values are checked separately from valid values. A mask of missing values is computed for each and checked to match. The remaining all-valid values are cast to object dtype and checked.

  Examples

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