BUG: obj.loc[listlike] with missing keys and CategoricalIndex

doc/source/whatsnew/v1.2.0.rst

@@ -587,6 +587,7 @@ Indexing
 - Bug in indexing on a :class:`Series` or :class:`DataFrame` with a :class:`CategoricalIndex` using a listlike indexer containing NA values (:issue:`37722`)
 - Bug in :meth:`DataFrame.xs` ignored ``droplevel=False`` for columns (:issue:`19056`)
 - Bug in :meth:`DataFrame.reindex` raising ``IndexingError`` wrongly for empty :class:`DataFrame` with ``tolerance`` not None or ``method="nearest"`` (:issue:`27315`)
+- Bug in indexing on a :class:`Series` or :class:`DataFrame` with a :class:`CategoricalIndex` using listlike indexer that contains elements that are in the index's ``categories`` but not in the index itself failing to raise ``KeyError`` (:issue:`37901`)
 
 Missing
 ^^^^^^^

pandas/core/indexes/category.py

@@ -576,23 +576,11 @@ def _convert_list_indexer(self, keyarr):
         # the categories
 
         if self.categories._defer_to_indexing:
+            # See tests.indexing.interval.test_interval:test_loc_getitem_frame
             indexer = self.categories._convert_list_indexer(keyarr)
             return Index(self.codes).get_indexer_for(indexer)
 
-        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)
+        return self.get_indexer_for(keyarr)
 
     @doc(Index._maybe_cast_slice_bound)
     def _maybe_cast_slice_bound(self, label, side: str, kind):

pandas/core/indexing.py

@@ -1246,9 +1246,7 @@ def _get_listlike_indexer(self, key, axis: int, raise_missing: bool = False):
         indexer, keyarr = ax._convert_listlike_indexer(key)
         # We only act on all found values:
         if indexer is not None and (indexer != -1).all():
-            self._validate_read_indexer(
-                keyarr, indexer, axis, raise_missing=raise_missing
-            )
+            # _validate_read_indexer is a no-op if no -1s, so skip
             return ax[indexer], indexer
 
         if ax._index_as_unique:
@@ -1309,21 +1307,15 @@ def _validate_read_indexer(
                 not_found = list(set(key) - set(ax))
                 raise KeyError(f"{not_found} not in index")
 
-            # we skip the warning on Categorical
-            # as this check is actually done (check for
-            # non-missing values), but a bit later in the
-            # code, so we want to avoid warning & then
-            # just raising
-            if not ax.is_categorical():
-                not_found = key[missing_mask]
-
-                with option_context("display.max_seq_items", 10, "display.width", 80):
-                    raise KeyError(
-                        "Passing list-likes to .loc or [] with any missing labels "
-                        "is no longer supported. "
-                        f"The following labels were missing: {not_found}. "
-                        "See https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike"  # noqa:E501
-                    )
+            not_found = key[missing_mask]
+
+            with option_context("display.max_seq_items", 10, "display.width", 80):
+                raise KeyError(
+                    "Passing list-likes to .loc or [] with any missing labels "
+                    "is no longer supported. "
+                    f"The following labels were missing: {not_found}. "
+                    "See https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike"  # noqa:E501
+                )
 
 
 @doc(IndexingMixin.iloc)

pandas/tests/indexing/test_categorical.py

@@ -1,3 +1,5 @@
+import re
+
 import numpy as np
 import pytest
 
@@ -254,41 +256,45 @@ def test_slicing_doc_examples(self):
         )
         tm.assert_frame_equal(result, expected)
 
-    def test_loc_listlike(self):
-
+    def test_loc_getitem_listlike_labels(self):
         # list of labels
         result = self.df.loc[["c", "a"]]
         expected = self.df.iloc[[4, 0, 1, 5]]
         tm.assert_frame_equal(result, expected, check_index_type=True)
 
-        result = self.df2.loc[["a", "b", "e"]]
-        exp_index = CategoricalIndex(list("aaabbe"), categories=list("cabe"), name="B")
-        expected = DataFrame({"A": [0, 1, 5, 2, 3, np.nan]}, index=exp_index)
-        tm.assert_frame_equal(result, expected, check_index_type=True)
+    def test_loc_getitem_listlike_unused_category(self):
+        # GH#37901 a label that is in index.categories but not in index
+        # listlike containing an element in the categories but not in the values
+        msg = (
+            "The following labels were missing: CategoricalIndex(['e'], "
+            "categories=['c', 'a', 'b', 'e'], ordered=False, name='B', "
+            "dtype='category')"
+        )
+        with pytest.raises(KeyError, match=re.escape(msg)):
+            self.df2.loc[["a", "b", "e"]]
 
+    def test_loc_getitem_label_unused_category(self):
         # element in the categories but not in the values
         with pytest.raises(KeyError, match=r"^'e'$"):
             self.df2.loc["e"]
 
-        # assign is ok
+    def test_loc_getitem_non_category(self):
+        # not all labels in the categories
+        msg = (
+            "The following labels were missing: Index(['d'], dtype='object', name='B')"
+        )
+        with pytest.raises(KeyError, match=re.escape(msg)):
+            self.df2.loc[["a", "d"]]
+
+    def test_loc_setitem_expansion_label_unused_category(self):
+        # assigning with a label that is in the categories but not in the index
         df = self.df2.copy()
         df.loc["e"] = 20
         result = df.loc[["a", "b", "e"]]
         exp_index = CategoricalIndex(list("aaabbe"), categories=list("cabe"), name="B")
         expected = DataFrame({"A": [0, 1, 5, 2, 3, 20]}, index=exp_index)
         tm.assert_frame_equal(result, expected)
 
-        df = self.df2.copy()
-        result = df.loc[["a", "b", "e"]]
-        exp_index = CategoricalIndex(list("aaabbe"), categories=list("cabe"), name="B")
-        expected = DataFrame({"A": [0, 1, 5, 2, 3, np.nan]}, index=exp_index)
-        tm.assert_frame_equal(result, expected, check_index_type=True)
-
-        # not all labels 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):
         # GH 11586
 
@@ -309,8 +315,8 @@ def test_loc_listlike_dtypes(self):
         exp = DataFrame({"A": [1, 1, 2], "B": [4, 4, 5]}, index=exp_index)
         tm.assert_frame_equal(res, exp, check_index_type=True)
 
-        msg = "a list-indexer must only include values that are in the categories"
-        with pytest.raises(KeyError, match=msg):
+        msg = "The following labels were missing: Index(['x'], dtype='object')"
+        with pytest.raises(KeyError, match=re.escape(msg)):
             df.loc[["a", "x"]]
 
         # duplicated categories and codes
@@ -332,8 +338,7 @@ def test_loc_listlike_dtypes(self):
         )
         tm.assert_frame_equal(res, exp, check_index_type=True)
 
-        msg = "a list-indexer must only include values that are in the categories"
-        with pytest.raises(KeyError, match=msg):
+        with pytest.raises(KeyError, match=re.escape(msg)):
             df.loc[["a", "x"]]
 
         # contains unused category
@@ -347,13 +352,6 @@ def test_loc_listlike_dtypes(self):
         )
         tm.assert_frame_equal(res, exp, check_index_type=True)
 
-        res = df.loc[["a", "e"]]
-        exp = DataFrame(
-            {"A": [1, 3, np.nan], "B": [5, 7, np.nan]},
-            index=CategoricalIndex(["a", "a", "e"], categories=list("abcde")),
-        )
-        tm.assert_frame_equal(res, exp, check_index_type=True)
-
         # duplicated slice
         res = df.loc[["a", "a", "b"]]
         exp = DataFrame(
@@ -362,10 +360,27 @@ def test_loc_listlike_dtypes(self):
         )
         tm.assert_frame_equal(res, exp, check_index_type=True)
 
-        msg = "a list-indexer must only include values that are in the categories"
-        with pytest.raises(KeyError, match=msg):
+        with pytest.raises(KeyError, match=re.escape(msg)):
             df.loc[["a", "x"]]
 
+    def test_loc_getitem_listlike_unused_category_raises_keyerro(self):
+        # key that is an *unused* category raises
+        index = CategoricalIndex(["a", "b", "a", "c"], categories=list("abcde"))
+        df = DataFrame({"A": [1, 2, 3, 4], "B": [5, 6, 7, 8]}, index=index)
+
+        with pytest.raises(KeyError, match="e"):
+            # For comparison, check the scalar behavior
+            df.loc["e"]
+
+        msg = (
+            "Passing list-likes to .loc or [] with any missing labels is no "
+            "longer supported. The following labels were missing: "
+            "CategoricalIndex(['e'], categories=['a', 'b', 'c', 'd', 'e'], "
+            "ordered=False, dtype='category'). See https"
+        )
+        with pytest.raises(KeyError, match=re.escape(msg)):
+            df.loc[["a", "e"]]
+
     def test_ix_categorical_index(self):
         # GH 12531
         df = DataFrame(np.random.randn(3, 3), index=list("ABC"), columns=list("XYZ"))

pandas/tests/indexing/test_loc.py

@@ -1674,7 +1674,12 @@ def test_loc_getitem_list_of_labels_categoricalindex_with_na(self, box):
         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"
+        msg = (
+            r"Passing list-likes to .loc or \[\] with any missing labels is no "
+            "longer supported. The following labels were missing: "
+            r"(Categorical)?Index\(\[nan\], .*\). "
+            "See https"
+        )
         with pytest.raises(KeyError, match=msg):
             ser2.loc[box(ci2)]