https://github.com/pandas-dev/pandas-stubs/pull/1462#discussion_r2490934466

Author: cmp0xff

pandas-stubs/core/groupby/grouper.pyi

@@ -1,36 +1,21 @@
-from collections.abc import (
-    Hashable,
-    Iterator,
-)
 from typing import (
     Any,
     final,
     overload,
 )
 
-import numpy as np
-from pandas import (
-    DataFrame,
-    Index,
-    Series,
-)
 from pandas.core.resample import TimeGrouper
 from typing_extensions import Self
 
 from pandas._libs.lib import _NoDefaultDoNotUse
 from pandas._typing import (
-    ArrayLike,
     Axis,
     Frequency,
     Incomplete,
     KeysArgType,
     Level,
     ListLikeHashable,
-    npt,
 )
-from pandas.util._decorators import cache_readonly
-
-from pandas.io.formats.printing import PrettyDict
 
 class Grouper:
     key: KeysArgType | None
@@ -53,27 +38,3 @@ class Grouper:
     def __new__(cls, *args: Any, freq: Frequency, **kwargs: Any) -> TimeGrouper: ...
     @final
     def __repr__(self) -> str: ...  # noqa: PYI029 __repr__ here is final
-
-@final
-class Grouping:
-    level: Level | None
-    obj: DataFrame | Series | None
-    in_axis: bool
-    grouping_vector: Incomplete
-    def __iter__(self) -> Iterator[Hashable]: ...
-    @cache_readonly
-    def name(self) -> Hashable: ...
-    @cache_readonly
-    def ngroups(self) -> int: ...
-    @cache_readonly
-    def indices(self) -> dict[Hashable, npt.NDArray[np.intp]]: ...
-    @property
-    def codes(self) -> npt.NDArray[np.signedinteger]: ...
-    @cache_readonly
-    def group_arraylike(self) -> ArrayLike: ...
-    @cache_readonly
-    def result_index(self) -> Index: ...
-    @cache_readonly
-    def group_index(self) -> Index: ...
-    @cache_readonly
-    def groups(self) -> PrettyDict[Hashable, Index]: ...

pandas-stubs/core/groupby/ops.pyi

@@ -1,96 +1,17 @@
 from collections.abc import (
-    Callable,
-    Hashable,
     Iterator,
 )
 from typing import (
     Generic,
-    final,
 )
 
 import numpy as np
-from pandas import (
-    Index,
-    Series,
-)
-from pandas.core.groupby import grouper
 
 from pandas._typing import (
-    ArrayLike,
     AxisInt,
-    Incomplete,
     NDFrameT,
-    Shape,
-    T,
     npt,
 )
-from pandas.util._decorators import cache_readonly
-
-class BaseGrouper:
-    axis: Index
-    dropna: bool
-    @property
-    def groupings(self) -> list[grouper.Grouping]: ...
-    @property
-    def shape(self) -> Shape: ...
-    def __iter__(self) -> Iterator: ...
-    @property
-    def nkeys(self) -> int: ...
-    def get_iterator(
-        self, data: NDFrameT, axis: AxisInt = ...
-    ) -> Iterator[tuple[Hashable, NDFrameT]]: ...
-    @cache_readonly
-    def indices(self) -> dict[Hashable, npt.NDArray[np.intp]]: ...
-    @final
-    def result_ilocs(self) -> npt.NDArray[np.intp]: ...
-    @final
-    @property
-    def codes(self) -> list[npt.NDArray[np.signedinteger]]: ...
-    @property
-    def levels(self) -> list[Index]: ...
-    @property
-    def names(self) -> list: ...
-    @final
-    def size(self) -> Series: ...
-    @cache_readonly
-    def groups(self) -> dict[Hashable, Index]: ...
-    @final
-    @cache_readonly
-    def is_monotonic(self) -> bool: ...
-    @final
-    @cache_readonly
-    def has_dropped_na(self) -> bool: ...
-    @cache_readonly
-    def group_info(self) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp], int]: ...
-    @cache_readonly
-    def codes_info(self) -> npt.NDArray[np.intp]: ...
-    @final
-    @cache_readonly
-    def ngroups(self) -> int: ...
-    @property
-    def reconstructed_codes(self) -> list[npt.NDArray[np.intp]]: ...
-    @cache_readonly
-    def result_index(self) -> Index: ...
-    @final
-    def get_group_levels(self) -> list[ArrayLike]: ...
-    @final
-    def agg_series(
-        self,
-        obj: Series,
-        func: Callable[[Series], object],
-        preserve_dtype: bool = ...,
-    ) -> ArrayLike: ...
-    @final
-    def apply_groupwise(
-        self, f: Callable[[NDFrameT], T], data: NDFrameT, axis: AxisInt = ...
-    ) -> tuple[list[T], bool]: ...
-
-class BinGrouper(BaseGrouper):
-    bins: npt.NDArray[np.int64]
-    binlabels: Index
-    indexer: npt.NDArray[np.intp]
-    @cache_readonly
-    def indices(self) -> dict[Incomplete, list[int]]: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
 
 class DataSplitter(Generic[NDFrameT]):
     data: NDFrameT

pandas-stubs/core/series.pyi

@@ -154,7 +154,6 @@ from pandas._typing import (
     FloatFormatType,
     Frequency,
     GenericT,
-    GenericT_co,
     GroupByObjectNonScalar,
     HashableT1,
     IgnoreRaise,
@@ -4618,30 +4617,3 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
     ) -> Self: ...
     @final
     def __bool__(self) -> NoReturn: ...
-
-@type_check_only
-class _SeriesSubclassBase(Series[S1], Generic[S1, GenericT_co]):
-    @overload  # type: ignore[override]
-    def to_numpy(  # pyrefly: ignore
-        self,
-        dtype: None = None,
-        copy: bool = False,
-        na_value: Scalar = ...,
-        **kwargs: Any,
-    ) -> np_1darray[GenericT_co]: ...
-    @overload
-    def to_numpy(
-        self,
-        dtype: np.dtype[GenericT] | SupportsDType[GenericT] | type[GenericT],
-        copy: bool = False,
-        na_value: Scalar = ...,
-        **kwargs: Any,
-    ) -> np_1darray[GenericT]: ...
-    @overload
-    def to_numpy(  # pyright: ignore[reportIncompatibleMethodOverride]
-        self,
-        dtype: DTypeLike,
-        copy: bool = False,
-        na_value: Scalar = ...,
-        **kwargs: Any,
-    ) -> np_1darray: ...