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BUG: PeriodIndex fails to handle NA, rather than putting NaT in its place (#46673) #47777

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BUG: PeriodIndex fails to handle NA, rather than putting NaT in its place (#46673) #47777

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.5.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -906,6 +906,7 @@ Indexing
- Bug in :meth:`NDFrame.xs`, :meth:`DataFrame.iterrows`, :meth:`DataFrame.loc` and :meth:`DataFrame.iloc` not always propagating metadata (:issue:`28283`)
- Bug in :meth:`DataFrame.sum` min_count changes dtype if input contains NaNs (:issue:`46947`)
- Bug in :class:`IntervalTree` that lead to an infinite recursion. (:issue:`46658`)
- Bug in :class:`PeriodIndex` raising ``AttributeError`` when indexing on ``NA``, rather than putting ``NaT`` in its place. (:issue:`46673`)
-

Missing
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3 changes: 2 additions & 1 deletion pandas/_libs/tslibs/nattype.pyx
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Expand Up @@ -28,6 +28,7 @@ from numpy cimport int64_t
cnp.import_array()

cimport pandas._libs.tslibs.util as util
from pandas._libs.missing cimport C_NA
from pandas._libs.tslibs.np_datetime cimport (
get_datetime64_value,
get_timedelta64_value,
Expand Down Expand Up @@ -1217,7 +1218,7 @@ cdef inline bint checknull_with_nat(object val):
"""
Utility to check if a value is a nat or not.
"""
return val is None or util.is_nan(val) or val is c_NaT
return val is None or util.is_nan(val) or val is c_NaT or val is C_NA


cdef inline bint is_dt64nat(object val):
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15 changes: 15 additions & 0 deletions pandas/tests/arrays/categorical/test_indexing.py
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@@ -1,12 +1,16 @@
import math

import numpy as np
import pytest

from pandas import (
NA,
Categorical,
CategoricalIndex,
Index,
Interval,
IntervalIndex,
NaT,
PeriodIndex,
Series,
Timedelta,
Expand Down Expand Up @@ -194,6 +198,17 @@ def test_categories_assignments(self):
tm.assert_numpy_array_equal(cat.__array__(), exp)
tm.assert_index_equal(cat.categories, Index([1, 2, 3]))

@pytest.mark.parametrize(
"null_val",
[None, np.nan, NaT, NA, math.nan, "NaT", "nat", "NAT", "nan", "NaN", "NAN"],
)
def test_periodindex_on_null_types(self, null_val):
# GH 46673
result = PeriodIndex(["2022-04-06", "2022-04-07", null_val], freq="D")
expected = PeriodIndex(["2022-04-06", "2022-04-07", "NaT"], dtype="period[D]")
assert type(result[2]) == type(NaT)
tm.assert_index_equal(result, expected)

@pytest.mark.parametrize("new_categories", [[1, 2, 3, 4], [1, 2]])
def test_categories_assignments_wrong_length_raises(self, new_categories):
cat = Categorical(["a", "b", "c", "a"])
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