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Fixes #27937. As described in that issue, assigning a mixture of NaN and
Interval values into a slice of a categorical-typed series would raise
an exception. This is no longer the case.

@jreback jreback added this to the 1.4 milestone Oct 1, 2021
@jreback jreback added Categorical Categorical Data Type Indexing Related to indexing on series/frames, not to indexes themselves Interval Interval data type Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate Testing pandas testing functions or related to the test suite labels Oct 1, 2021
expected = Series([NaT, 1, 2], dtype="timedelta64[ns]")
tm.assert_series_equal(series, expected)

def test_setitem_mix_of_nan_and_interval(self):
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can you parameterize on all the cases in the OP

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Thanks, I parametrized the NA and the non-NA value, let me know if I should add more cases.

Fixes pandas-dev#27937. As described in that issue, assigning a mixture of NaN and
Interval values into a slice of a categorical-typed series would raise
an exception.  This is no longer the case.
tm.assert_series_equal(series, expected)

@pytest.mark.parametrize("not_na", [Interval(0, 1), "a", 1.0])
@pytest.mark.parametrize("na", [np.nan, NaT])
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can you use nulls_fixture

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Very cool, yes. Fixed.

@jreback jreback merged commit 4e8b77d into pandas-dev:master Oct 5, 2021
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jreback commented Oct 5, 2021

thanks @ElDeveloper very nice!

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Thanks so much for your feedback!

gasparitiago pushed a commit to gasparitiago/pandas that referenced this pull request Oct 9, 2021
rhshadrach pushed a commit to rhshadrach/pandas that referenced this pull request Oct 10, 2021
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Categorical Categorical Data Type Indexing Related to indexing on series/frames, not to indexes themselves Interval Interval data type Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate Testing pandas testing functions or related to the test suite

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ValueError on assigning multiple NaN/None to Categorial Series when all categories are Intervals

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