Correctly handle scalar indices in Index.__getitem__

python/cudf/cudf/core/cut.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2021-2022, NVIDIA CORPORATION.
+# Copyright (c) 2021-2023, NVIDIA CORPORATION.
 
 from collections import abc
 
@@ -279,12 +279,8 @@ def cut(
     if labels is not None:
         if labels is not ordered and len(set(labels)) != len(labels):
             # when we have duplicate labels and ordered is False, we
-            # should allow duplicate categories. The categories are
-            # returned in order
-            new_data = [interval_labels[i][0] for i in index_labels.values]
-            return cudf.CategoricalIndex(
-                new_data, categories=sorted(set(labels)), ordered=False
-            )
+            # should allow duplicate categories.
+            return interval_labels[index_labels]
 
     col = build_categorical_column(
         categories=interval_labels,

python/cudf/cudf/core/index.py

@@ -1403,7 +1403,7 @@ def __repr__(self):
     @_cudf_nvtx_annotate
     def __getitem__(self, index):
         res = self._get_elements_from_column(index)
-        if not isinstance(index, int):
+        if isinstance(res, ColumnBase):
             res = as_index(res)
             res.name = self.name
         return res

python/cudf/cudf/tests/test_index.py

@@ -2886,3 +2886,20 @@ def test_index_to_pandas_nullable(data, expected_dtype):
     expected = pd.Index(data, dtype=expected_dtype)
 
     assert_eq(pi, expected)
+
+
+class TestIndexScalarGetItem:
+    @pytest.fixture(
+        params=[range(1, 10, 2), [1, 2, 3], ["a", "b", "c"], [1.5, 2.5, 3.5]]
+    )
+    def index_values(self, request):
+        return request.param
+
+    @pytest.fixture(params=[int, np.int8, np.int32, np.int64])
+    def i(self, request):
+        return request.param(1)
+
+    def test_scalar_getitem(self, index_values, i):
+        index = cudf.Index(index_values)
+
+        assert not isinstance(index[i], cudf.Index)