GH1383 Add support for creating Series/Index with dtype='category'

pandas-stubs/core/indexes/base.pyi

@@ -41,6 +41,7 @@ from pandas.core.base import (
     NumListLike,
     _ListLike,
 )
+from pandas.core.indexes.category import CategoricalIndex
 from pandas.core.strings.accessor import StringMethods
 from typing_extensions import (
     Never,
@@ -57,6 +58,7 @@ from pandas._typing import (
     AnyAll,
     ArrayLike,
     AxesData,
+    CategoryDtypeArg,
     DropKeep,
     Dtype,
     DtypeArg,
@@ -228,6 +230,16 @@ class Index(IndexOpsMixin[S1]):
         tupleize_cols: bool = ...,
     ) -> TimedeltaIndex: ...
     @overload
+    def __new__(
+        cls,
+        data: AxesData,
+        *,
+        dtype: CategoryDtypeArg,
+        copy: bool = ...,
+        name: Hashable = ...,
+        tupleize_cols: bool = ...,
+    ) -> CategoricalIndex: ...
+    @overload
     def __new__(
         cls,
         data: Sequence[Interval[_OrderableT]] | IndexOpsMixin[Interval[_OrderableT]],

pandas-stubs/core/series.pyi

@@ -359,6 +359,16 @@ class Series(IndexOpsMixin[S1], NDFrame):
         copy: bool = ...,
     ) -> Series[Timestamp]: ...
     @overload
+    def __new__(
+        cls,
+        data: _ListLike,
+        index: AxesData | None = ...,
+        *,
+        dtype: CategoryDtypeArg,
+        name: Hashable = ...,
+        copy: bool = ...,
+    ) -> Series[CategoricalDtype]: ...
+    @overload
     def __new__(
         cls,
         data: PeriodIndex | Sequence[Period],

tests/indexes/test_indexes.py

@@ -18,6 +18,7 @@
 from pandas.core.arrays.interval import IntervalArray
 from pandas.core.arrays.timedeltas import TimedeltaArray
 from pandas.core.indexes.base import Index
+from pandas.core.indexes.category import CategoricalIndex
 from typing_extensions import (
     Never,
     assert_type,
@@ -1369,6 +1370,12 @@ def test_index_factorize() -> None:
     check(assert_type(idx_uniques, np_1darray | Index | Categorical), pd.Index)
 
 
+def test_index_categorical() -> None:
+    """Test creating an index with Categorical type GH1383."""
+    sr = pd.Index([1], dtype="category")
+    check(assert_type(sr, CategoricalIndex), CategoricalIndex)
+
+
 def test_disallow_empty_index() -> None:
     # From GH 826
     if TYPE_CHECKING_INVALID_USAGE:

tests/series/test_properties.py

@@ -1,6 +1,5 @@
 from typing import (
     TYPE_CHECKING,
-    cast,
 )
 
 import numpy as np
@@ -54,12 +53,9 @@ def test_dt_property() -> None:
 
 def test_array_property() -> None:
     """Test that Series.array returns ExtensionArray and its subclasses"""
-    # casting due to pandas-dev/pandas-stubs#1383
     check(
         assert_type(
-            cast(
-                "pd.Series[pd.CategoricalDtype]", pd.Series([1], dtype="category")
-            ).array,
+            pd.Series([1], dtype="category").array,
             pd.Categorical,
         ),
         pd.Categorical,

tests/series/test_series.py

@@ -50,6 +50,8 @@
     Scalar,
 )
 
+from pandas.core.dtypes.dtypes import CategoricalDtype  # noqa F401
+
 from tests import (
     PD_LTE_23,
     TYPE_CHECKING_INVALID_USAGE,
@@ -1819,6 +1821,10 @@ def test_categorical_codes():
     cat = pd.Categorical(["a", "b", "a"])
     check(assert_type(cat.codes, np_1darray[np.signedinteger]), np_1darray[np.int8])
 
+    # GH1383
+    sr = pd.Series([1], dtype="category")
+    check(assert_type(sr, "pd.Series[CategoricalDtype]"), pd.Series, np.integer)
+
 
 def test_relops() -> None:
     # GH 175
@@ -2908,8 +2914,6 @@ def test_astype_categorical(cast_arg: CategoryDtypeArg, target_type: type) -> No
         # pandas category
         assert_type(s.astype(pd.CategoricalDtype()), "pd.Series[pd.CategoricalDtype]")
         assert_type(s.astype(cast_arg), "pd.Series[pd.CategoricalDtype]")
-        # pyarrow dictionary
-        # assert_type(s.astype("dictionary[pyarrow]"), "pd.Series[Categorical]")
 
 
 @pytest.mark.parametrize("cast_arg, target_type", ASTYPE_OBJECT_ARGS, ids=repr)