BUG: PeriodIndex fails to handle NA, rather than putting NaT in its place (pandas-dev#46673) (pandas-dev#47780)

* BUG: PeriodIndex fails to handle NA, rather than putting NaT in its place (pandas-dev#46673)

* BUG: PeriodIndex fails to handle NA, rather than putting NaT in its place (pandas-dev#46673)

* BUG: Series.astype is unable to handle pd.nan.

* BUG: PeriodIndex fails to handle NA, rather than putting NaT in its place (pandas-dev#46673)

* BUG: Series.astype is unable to handle pd.nan (pandas-dev#46377)

* BUG: PeriodIndex fails to handle NA, rather than putting NaT in its place (pandas-dev#46673)

* BUG: PeriodIndex fails to handle NA, rather than putting NaT in its place (pandas-dev#46673)

* BUG: PeriodIndex fails to handle NA, rather than putting NaT in its place (pandas-dev#46673)

Author: kapiliyer

doc/source/whatsnew/v1.5.0.rst

@@ -912,6 +912,7 @@ 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

pandas/_libs/tslibs/period.pyx

@@ -43,6 +43,7 @@ from libc.time cimport (
 import_datetime()
 
 cimport pandas._libs.tslibs.util as util
+from pandas._libs.missing cimport C_NA
 from pandas._libs.tslibs.np_datetime cimport (
     NPY_DATETIMEUNIT,
     NPY_FR_D,
@@ -1470,7 +1471,7 @@ cdef inline int64_t _extract_ordinal(object item, str freqstr, freq) except? -1:
     cdef:
         int64_t ordinal
 
-    if checknull_with_nat(item):
+    if checknull_with_nat(item) or item is C_NA:
         ordinal = NPY_NAT
     elif util.is_integer_object(item):
         if item == NPY_NAT:

pandas/tests/arrays/categorical/test_indexing.py

@@ -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,
@@ -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 result[2] is 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"])

pandas/tests/series/methods/test_astype.py

@@ -446,7 +446,7 @@ def test_astype_string_to_extension_dtype_roundtrip(
         self, data, dtype, request, nullable_string_dtype
     ):
         if dtype == "boolean" or (
-            dtype in ("period[M]", "datetime64[ns]", "timedelta64[ns]") and NaT in data
+            dtype in ("datetime64[ns]", "timedelta64[ns]") and NaT in data
         ):
             mark = pytest.mark.xfail(
                 reason="TODO StringArray.astype() with missing values #GH40566"