BUG: loc.__getitem__[[na_value]] with CategoricalIndex containing NAs

doc/source/whatsnew/v1.2.0.rst

@@ -469,6 +469,7 @@ Indexing
 - Bug in :meth:`Index.where` incorrectly casting numeric values to strings (:issue:`37591`)
 - Bug in :meth:`Series.loc` and :meth:`DataFrame.loc` raises when numeric label was given for object :class:`Index` although label was in :class:`Index` (:issue:`26491`)
 - Bug in :meth:`DataFrame.loc` returned requested key plus missing values when ``loc`` was applied to single level from :class:`MultiIndex` (:issue:`27104`)
+- Bug in indexing on a :class:`Series` or :class:`DataFrame` with a :class:`CategoricalIndex` using a listlike indexer containing NA values (:issue:`37722`)
 
 Missing
 ^^^^^^^

pandas/core/common.py

@@ -113,7 +113,9 @@ def is_bool_indexer(key: Any) -> bool:
 
             if not lib.is_bool_array(key):
                 na_msg = "Cannot mask with non-boolean array containing NA / NaN values"
-                if isna(key).any():
+                if lib.infer_dtype(key) == "boolean" and isna(key).any():
+                    # Don't raise on e.g. ["A", "B", np.nan], see
+                    #  test_loc_getitem_list_of_labels_categoricalindex_with_na
                     raise ValueError(na_msg)
                 return False
             return True

pandas/core/indexes/category.py

@@ -586,11 +586,18 @@ def _convert_list_indexer(self, keyarr):
             indexer = self.categories._convert_list_indexer(keyarr)
             return Index(self.codes).get_indexer_for(indexer)
 
-        indexer = self.categories.get_indexer(np.asarray(keyarr))
-        if (indexer == -1).any():
-            raise KeyError(
-                "a list-indexer must only include values that are in the categories"
-            )
+        msg = "a list-indexer must only include values that are in the categories"
+        if self.hasnans:
+            msg += " or NA"
+        try:
+            codes = self._data._validate_setitem_value(keyarr)
+        except (ValueError, TypeError) as err:
+            if "Index data must be 1-dimensional" in str(err):
+                # e.g. test_setitem_ndarray_3d
+                raise
+            raise KeyError(msg)
+        if not self.hasnans and (codes == -1).any():
+            raise KeyError(msg)
 
         return self.get_indexer(keyarr)
 

pandas/tests/indexing/test_categorical.py

@@ -285,12 +285,8 @@ def test_loc_listlike(self):
         tm.assert_frame_equal(result, expected, check_index_type=True)
 
         # not all labels in the categories
-        with pytest.raises(
-            KeyError,
-            match=(
-                "'a list-indexer must only include values that are in the categories'"
-            ),
-        ):
+        msg = "a list-indexer must only include values that are in the categories"
+        with pytest.raises(KeyError, match=msg):
             self.df2.loc[["a", "d"]]
 
     def test_loc_listlike_dtypes(self):

pandas/tests/indexing/test_loc.py

@@ -12,6 +12,7 @@
 
 import pandas as pd
 from pandas import (
+    CategoricalIndex,
     DataFrame,
     Index,
     MultiIndex,
@@ -1645,6 +1646,36 @@ def test_loc_setitem_mask_td64_series_value(self):
         tm.assert_frame_equal(df, df_copy)
 
 
+class TestLocListlike:
+    @pytest.mark.parametrize("box", [lambda x: x, np.asarray, list])
+    def test_loc_getitem_list_of_labels_categoricalindex_with_na(self, box):
+        # passing a list can include valid categories _or_ NA values
+        ci = CategoricalIndex(["A", "B", np.nan])
+        ser = Series(range(3), index=ci)
+
+        result = ser.loc[box(ci)]
+        tm.assert_series_equal(result, ser)
+
+        result = ser[box(ci)]
+        tm.assert_series_equal(result, ser)
+
+        result = ser.to_frame().loc[box(ci)]
+        tm.assert_frame_equal(result, ser.to_frame())
+
+        ser2 = ser[:-1]
+        ci2 = ci[1:]
+        # but if there are no NAs present, this should raise KeyError
+        msg = "a list-indexer must only include values that are in the categories"
+        with pytest.raises(KeyError, match=msg):
+            ser2.loc[box(ci2)]
+
+        with pytest.raises(KeyError, match=msg):
+            ser2[box(ci2)]
+
+        with pytest.raises(KeyError, match=msg):
+            ser2.to_frame().loc[box(ci2)]
+
+
 def test_series_loc_getitem_label_list_missing_values():
     # gh-11428
     key = np.array(

pandas/tests/test_common.py

@@ -158,3 +158,11 @@ def test_serializable(obj):
     # GH 35611
     unpickled = tm.round_trip_pickle(obj)
     assert type(obj) == type(unpickled)
+
+
+class TestIsBoolIndexer:
+    def test_non_bool_array_with_na(self):
+        # in particular, this should not raise
+        arr = np.array(["A", "B", np.nan])
+
+        assert not com.is_bool_indexer(arr)