BUG: RangeIndex.astype('category')

Author: topper-123

doc/source/whatsnew/v1.3.0.rst

@@ -750,6 +750,7 @@ Indexing
 - Bug in :meth:`DatetimeIndex.insert` when inserting ``np.datetime64("NaT")`` into a timezone-aware index incorrectly treating the timezone-naive value as timezone-aware (:issue:`39769`)
 - Bug in incorrectly raising in :meth:`Index.insert`, when setting a new column that cannot be held in the existing ``frame.columns``, or in :meth:`Series.reset_index` or :meth:`DataFrame.reset_index` instead of casting to a compatible dtype (:issue:`39068`)
 - Bug in :meth:`RangeIndex.append` where a single object of length 1 was concatenated incorrectly (:issue:`39401`)
+- Bug in :meth:`RangeIndex.astype` where when converting to :class:`CategoricalIndex`, the categories became a :class:`Int64Index` instead of a :class:`RangeIndex` (:issue:`xxxxx`)
 - Bug in setting ``numpy.timedelta64`` values into an object-dtype :class:`Series` using a boolean indexer (:issue:`39488`)
 - Bug in setting numeric values into a into a boolean-dtypes :class:`Series` using ``at`` or ``iat`` failing to cast to object-dtype (:issue:`39582`)
 - Bug in :meth:`DataFrame.loc.__setitem__` when setting-with-expansion incorrectly raising when the index in the expanding axis contains duplicates (:issue:`40096`)

pandas/core/indexes/base.py

@@ -907,9 +907,7 @@ def astype(self, dtype, copy=True):
         elif is_categorical_dtype(dtype):
             from pandas.core.indexes.category import CategoricalIndex
 
-            return CategoricalIndex(
-                self._values, name=self.name, dtype=dtype, copy=copy
-            )
+            return CategoricalIndex(self, name=self.name, dtype=dtype, copy=copy)
 
         elif is_extension_array_dtype(dtype):
             return Index(np.asarray(self), name=self.name, dtype=dtype, copy=copy)

pandas/tests/indexes/common.py

@@ -672,19 +672,19 @@ def test_astype_category(self, copy, name, ordered, simple_index):
         # standard categories
         dtype = CategoricalDtype(ordered=ordered)
         result = idx.astype(dtype, copy=copy)
-        expected = CategoricalIndex(idx.values, name=name, ordered=ordered)
+        expected = CategoricalIndex(idx, name=name, ordered=ordered)
         tm.assert_index_equal(result, expected)
 
         # non-standard categories
         dtype = CategoricalDtype(idx.unique().tolist()[:-1], ordered)
         result = idx.astype(dtype, copy=copy)
-        expected = CategoricalIndex(idx.values, name=name, dtype=dtype)
+        expected = CategoricalIndex(idx, name=name, dtype=dtype)
         tm.assert_index_equal(result, expected)
 
         if ordered is False:
             # dtype='category' defaults to ordered=False, so only test once
             result = idx.astype("category", copy=copy)
-            expected = CategoricalIndex(idx.values, name=name)
+            expected = CategoricalIndex(idx, name=name)
             tm.assert_index_equal(result, expected)
 
     def test_is_unique(self, simple_index):