type *core/base.pyi, remove SelectionMixin

pandas-stubs/core/base.pyi

@@ -1,5 +1,4 @@
 from collections.abc import (
-    Hashable,
     Iterator,
     Sequence,
 )
@@ -11,7 +10,6 @@ from typing import (
     Protocol,
     TypeAlias,
     TypeVar,
-    final,
     overload,
     type_check_only,
 )
@@ -42,7 +40,6 @@ from pandas._typing import (
     GenericT_co,
     Just,
     ListLike,
-    NDFrameT,
     Scalar,
     SupportsDType,
     np_1darray,
@@ -54,22 +51,12 @@ from pandas._typing import (
     np_ndarray_float,
     np_ndarray_td,
 )
-from pandas.util._decorators import cache_readonly
 
 T_INTERVAL_NP = TypeVar("T_INTERVAL_NP", bound=np.bytes_ | np.str_)
 
 class NoNewAttributesMixin:
     def __setattr__(self, key: str, value: Any) -> None: ...
 
-class SelectionMixin(Generic[NDFrameT]):
-    obj: NDFrameT
-    exclusions: frozenset[Hashable]
-    @final
-    @cache_readonly
-    def ndim(self) -> int: ...
-    def __getitem__(self, key): ...
-    def aggregate(self, func, *args: Any, **kwargs: Any): ...
-
 class IndexOpsMixin(OpsMixin, Generic[S1, GenericT_co]):
     __array_priority__: int = ...
     @property

pandas-stubs/core/groupby/groupby.pyi

@@ -18,7 +18,6 @@ from typing import (
 )
 
 import numpy as np
-from pandas.core.base import SelectionMixin
 from pandas.core.frame import DataFrame
 from pandas.core.groupby import generic
 from pandas.core.groupby.indexing import (
@@ -350,7 +349,7 @@ class GroupByPlot(PlotAccessor, Generic[_GroupByT]):
     # def __call__(self, *args: Any, **kwargs: Any): ...
     # def __getattr__(self, name: str): ...
 
-class BaseGroupBy(SelectionMixin[NDFrameT], GroupByIndexingMixin):
+class BaseGroupBy(GroupByIndexingMixin, Generic[NDFrameT]):
     @final
     def __len__(self) -> int: ...
     @final

pandas-stubs/core/window/rolling.pyi

@@ -7,6 +7,7 @@ from collections.abc import (
 import datetime as dt
 from typing import (
     Any,
+    Generic,
     overload,
 )
 
@@ -15,7 +16,6 @@ from pandas import (
     Index,
     Series,
 )
-from pandas.core.base import SelectionMixin
 from pandas.core.indexers import BaseIndexer
 from typing_extensions import Self
 
@@ -34,7 +34,7 @@ from pandas._typing import (
     WindowingRankType,
 )
 
-class BaseWindow(SelectionMixin[NDFrameT]):
+class BaseWindow(Generic[NDFrameT]):
     on: str | Index | None
     closed: IntervalClosedType | None
     step: int | None

pyproject.toml

@@ -217,10 +217,6 @@ ignore = [
   # TODO: remove when array is fully typed
   "ANN001", "ANN201", "ANN204", "ANN206",
 ]
-"*core/base.pyi" = [
-  # TODO: remove when core/base.pyi is fully typed
-  "ANN001", "ANN201", "ANN204", "ANN206",
-]
 "*excel/_base.pyi" = [
   # TODO: remove when excel/_base.pyi is fully typed
   "ANN001", "ANN201", "ANN204", "ANN206",

tests/__init__.py

@@ -139,7 +139,7 @@ def check(
     elif isinstance(actual, pd.Index):
         value = actual[index_to_check_for_type]
     elif isinstance(actual, BaseGroupBy):
-        value = actual.obj
+        value = actual.obj  # type: ignore[attr-defined]  # pyright: ignore[reportAttributeAccessIssue]
     elif hasattr(actual, "__iter__"):
         value = next(
             iter(actual)  # pyright: ignore[reportArgumentType,reportCallIssue]

tests/test_groupby.py

@@ -70,9 +70,6 @@ def test_frame_groupby_resample() -> None:
         DataFrame,
     )
 
-    # props
-    check(assert_type(GB_DF.resample("ME").obj, DataFrame), DataFrame)
-
     # agg funcs
     with pytest_warns_bounded(
         FutureWarning,
@@ -312,9 +309,6 @@ def test_series_groupby_resample() -> None:
         Series,
     )
 
-    # props
-    check(assert_type(GB_S.resample("ME").obj, "Series[float]"), Series, float)
-
     # agg funcs
     check(assert_type(GB_S.resample("ME").sum(), "Series[float]"), Series, float)
     check(assert_type(GB_S.resample("ME").prod(), "Series[float]"), Series, float)
@@ -471,7 +465,6 @@ def test_frame_groupby_rolling() -> None:
     )
 
     # props
-    check(assert_type(GB_DF.rolling(1).obj, DataFrame), DataFrame)
     check(assert_type(GB_DF.rolling(1).on, str | Index | None), type(None))
     check(assert_type(GB_DF.rolling(1).method, Literal["single", "table"]), str)
     if PD_LTE_23:
@@ -596,9 +589,6 @@ def test_series_groupby_rolling() -> None:
         Series,
     )
 
-    # props
-    check(assert_type(GB_S.rolling(1).obj, "Series[float]"), Series, float)
-
     # agg funcs
     check(assert_type(GB_S.rolling(1).sum(), "Series[float]"), Series, float)
     check(assert_type(GB_S.rolling(1).min(), "Series[float]"), Series, float)
@@ -666,7 +656,6 @@ def test_frame_groupby_expanding() -> None:
     )
 
     # props
-    check(assert_type(GB_DF.expanding(1).obj, DataFrame), DataFrame)
     check(assert_type(GB_DF.expanding(1).on, str | Index | None), type(None))
     check(assert_type(GB_DF.expanding(1).method, Literal["single", "table"]), str)
     if PD_LTE_23:
@@ -795,9 +784,6 @@ def test_series_groupby_expanding() -> None:
         Series,
     )
 
-    # props
-    check(assert_type(GB_S.expanding(1).obj, "Series[float]"), Series, float)
-
     # agg funcs
     check(assert_type(GB_S.expanding(1).sum(), "Series[float]"), Series, float)
     check(assert_type(GB_S.expanding(1).min(), "Series[float]"), Series, float)
@@ -865,7 +851,6 @@ def test_frame_groupby_ewm() -> None:
     )
 
     # props
-    check(assert_type(GB_DF.ewm(1).obj, DataFrame), DataFrame)
     check(assert_type(GB_DF.ewm(1).on, str | Index | None), type(None))
     check(assert_type(GB_DF.ewm(1).method, Literal["single", "table"]), str)
     if PD_LTE_23:
@@ -973,9 +958,6 @@ def test_series_groupby_ewm() -> None:
         Series,
     )
 
-    # props
-    check(assert_type(GB_S.ewm(1).obj, "Series[float]"), Series, float)
-
     # agg funcs
     check(assert_type(GB_S.ewm(1).sum(), "Series[float]"), Series, float)
     check(assert_type(GB_S.ewm(1).mean(), "Series[float]"), Series, float)

tests/test_resampler.py

@@ -40,10 +40,6 @@
 _AggRetType = DataFrame | Series
 
 
-def test_props() -> None:
-    check(assert_type(DF.resample("ME").obj, DataFrame), DataFrame)
-
-
 def test_iter() -> None:
     assert_type(iter(DF.resample("ME")), Iterator[tuple[Hashable, DataFrame]])
     for v in DF.resample("ME"):
@@ -203,7 +199,7 @@ def j(
         kw: tuple[int],
     ) -> DataFrame:
         assert isinstance(res, DatetimeIndexResampler)
-        return res.obj
+        return DataFrame({"a": [1, 2, 3]})
 
     check(
         assert_type(DF.resample("ME").pipe(j, 1, [1.0], arg2="hi", kw=(1,)), DataFrame),
@@ -263,7 +259,7 @@ def j(
 
     def k(x: int, t: "DatetimeIndexResampler[DataFrame]") -> DataFrame:
         assert isinstance(x, int)
-        return t.obj
+        return DataFrame({"a": [1, 2, 3]})
 
     check(assert_type(DF.resample("ME").pipe((k, "t"), 1), DataFrame), DataFrame)
 
@@ -281,10 +277,6 @@ def f(val: Series) -> Series:
     check(assert_type(DF.resample("ME").transform(f), DataFrame), DataFrame)
 
 
-def test_props_series() -> None:
-    check(assert_type(S.resample("ME").obj, Series), Series)
-
-
 def test_iter_series() -> None:
     for v in S.resample("ME"):
         check(assert_type(v, tuple[Hashable, Series]), tuple)