diff --git a/pandas-stubs/_libs/interval.pyi b/pandas-stubs/_libs/interval.pyi
index 5152f32b9..9aaede454 100644
--- a/pandas-stubs/_libs/interval.pyi
+++ b/pandas-stubs/_libs/interval.pyi
@@ -4,6 +4,7 @@ from typing import (
     Literal,
     TypeVar,
     overload,
+    type_check_only,
 )
 
 import numpy as np
@@ -18,7 +19,6 @@ from pandas._typing import (
     IntervalClosedType,
     IntervalT,
     np_1darray,
-    npt,
 )
 
 VALID_CLOSED: frozenset[str]
@@ -27,6 +27,7 @@ _OrderableScalarT = TypeVar("_OrderableScalarT", bound=int | float)
 _OrderableTimesT = TypeVar("_OrderableTimesT", bound=Timestamp | Timedelta)
 _OrderableT = TypeVar("_OrderableT", bound=int | float | Timestamp | Timedelta)
 
+@type_check_only
 class _LengthDescriptor:
     @overload
     def __get__(
@@ -36,9 +37,8 @@ class _LengthDescriptor:
     def __get__(
         self, instance: Interval[_OrderableTimesT], owner: Any
     ) -> Timedelta: ...
-    @overload
-    def __get__(self, instance: IntervalTree, owner: Any) -> np.ndarray: ...
 
+@type_check_only
 class _MidDescriptor:
     @overload
     def __get__(self, instance: Interval[_OrderableScalarT], owner: Any) -> float: ...
@@ -46,8 +46,6 @@ class _MidDescriptor:
     def __get__(
         self, instance: Interval[_OrderableTimesT], owner: Any
     ) -> _OrderableTimesT: ...
-    @overload
-    def __get__(self, instance: IntervalTree, owner: Any) -> np.ndarray: ...
 
 class IntervalMixin:
     @property
@@ -68,8 +66,8 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
     def right(self: Interval[_OrderableT]) -> _OrderableT: ...
     @property
     def closed(self) -> IntervalClosedType: ...
-    mid: _MidDescriptor
-    length: _LengthDescriptor
+    mid = _MidDescriptor()
+    length = _LengthDescriptor()
     def __init__(
         self,
         left: _OrderableT,
@@ -223,21 +221,4 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
     @overload
     def __ne__(self, other: object) -> Literal[True]: ...
 
-class IntervalTree(IntervalMixin):
-    def __init__(
-        self,
-        left: np.ndarray,
-        right: np.ndarray,
-        closed: IntervalClosedType = ...,
-        leaf_size: int = ...,
-    ) -> None: ...
-    def get_indexer(self, target) -> npt.NDArray[np.intp]: ...
-    def get_indexer_non_unique(
-        self, target
-    ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
-    _na_count: int
-    @property
-    def is_overlapping(self) -> bool: ...
-    @property
-    def is_monotonic_increasing(self) -> bool: ...
-    def clear_mapping(self) -> None: ...
+class IntervalTree(IntervalMixin): ...
diff --git a/pandas-stubs/_libs/tslibs/offsets.pyi b/pandas-stubs/_libs/tslibs/offsets.pyi
index a6cae3ce3..299feade0 100644
--- a/pandas-stubs/_libs/tslibs/offsets.pyi
+++ b/pandas-stubs/_libs/tslibs/offsets.pyi
@@ -14,10 +14,14 @@ from typing import (
 
 from dateutil.relativedelta import weekday as WeekdayClass
 import numpy as np
+from numpy import typing as npt
 from pandas import Timestamp
 from typing_extensions import Self
 
-from pandas._typing import npt
+from pandas._typing import (
+    ShapeT,
+    np_ndarray,
+)
 
 from pandas.tseries.holiday import AbstractHolidayCalendar
 
@@ -37,7 +41,9 @@ class BaseOffset:
     @property
     def base(self) -> BaseOffset: ...
     @overload
-    def __add__(self, other: npt.NDArray[np.object_]) -> npt.NDArray[np.object_]: ...
+    def __add__(
+        self, other: np_ndarray[ShapeT, np.object_]
+    ) -> np_ndarray[ShapeT, np.object_]: ...
     @overload
     def __add__(self, other: _DatetimeT) -> _DatetimeT: ...  # type: ignore[overload-overlap]  # pyright: ignore[reportOverlappingOverload]
     @overload
@@ -47,7 +53,9 @@ class BaseOffset:
     @overload
     def __add__(self, other: _TimedeltaT) -> _TimedeltaT: ...
     @overload
-    def __radd__(self, other: npt.NDArray[np.object_]) -> npt.NDArray[np.object_]: ...
+    def __radd__(
+        self, other: np_ndarray[ShapeT, np.object_]
+    ) -> np_ndarray[ShapeT, np.object_]: ...
     @overload
     def __radd__(self, other: _DatetimeT) -> _DatetimeT: ...  # type: ignore[overload-overlap]  # pyright: ignore[reportOverlappingOverload]
     @overload
@@ -68,11 +76,15 @@ class BaseOffset:
     @overload
     def __rsub__(self, other: _TimedeltaT) -> _TimedeltaT: ...
     @overload
-    def __mul__(self, other: np.ndarray) -> np.ndarray: ...
+    def __mul__(
+        self, other: np_ndarray[ShapeT, np.object_]
+    ) -> np_ndarray[ShapeT, np.object_]: ...
     @overload
     def __mul__(self, other: int) -> Self: ...
     @overload
-    def __rmul__(self, other: np.ndarray) -> np.ndarray: ...
+    def __rmul__(
+        self, other: np_ndarray[ShapeT, np.object_]
+    ) -> np_ndarray[ShapeT, np.object_]: ...
     @overload
     def __rmul__(self, other: int) -> Self: ...
     def __neg__(self) -> Self: ...
diff --git a/pandas-stubs/_testing/__init__.pyi b/pandas-stubs/_testing/__init__.pyi
index 3db4eccbb..06d605cdf 100644
--- a/pandas-stubs/_testing/__init__.pyi
+++ b/pandas-stubs/_testing/__init__.pyi
@@ -12,7 +12,7 @@ from typing import (
 import warnings
 
 from matplotlib.artist import Artist
-import numpy as np
+from numpy import typing as npt
 from pandas import (
     Categorical,
     DataFrame,
@@ -61,7 +61,7 @@ def assert_attr_equal(
     attr: str, left: object, right: object, obj: str = "Attributes"
 ) -> None: ...
 def assert_is_valid_plot_return_object(
-    objs: Series | np.ndarray | Artist | tuple | dict,
+    objs: Series | npt.NDArray[Any] | Artist | tuple | dict,
 ) -> None: ...
 def assert_is_sorted(seq: AnyArrayLike) -> None: ...
 def assert_categorical_equal(
@@ -96,7 +96,7 @@ def assert_extension_array_equal(
     left: ExtensionArray,
     right: ExtensionArray,
     check_dtype: bool | Literal["equiv"] = True,
-    index_values: Index | np.ndarray | None = None,
+    index_values: Index | npt.NDArray[Any] | None = None,
     check_exact: bool = False,
     rtol: float = 1e-5,
     atol: float = 1e-8,
diff --git a/pandas-stubs/_typing.pyi b/pandas-stubs/_typing.pyi
index f1e2bf606..03fa4b426 100644
--- a/pandas-stubs/_typing.pyi
+++ b/pandas-stubs/_typing.pyi
@@ -85,7 +85,7 @@ HashableT5 = TypeVar("HashableT5", bound=Hashable)
 
 # array-like
 
-ArrayLike: TypeAlias = ExtensionArray | np.ndarray
+ArrayLike: TypeAlias = ExtensionArray | npt.NDArray[Any]
 AnyArrayLike: TypeAlias = ArrayLike | Index | Series
 AnyArrayLikeInt: TypeAlias = (
     IntegerArray | Index[int] | Series[int] | npt.NDArray[np.integer]
@@ -166,6 +166,7 @@ ToTimestampHow: TypeAlias = Literal["s", "e", "start", "end"]
 NDFrameT = TypeVar("NDFrameT", bound=NDFrame)
 
 IndexT = TypeVar("IndexT", bound=Index)
+T_EXTENSION_ARRAY = TypeVar("T_EXTENSION_ARRAY", bound=ExtensionArray)
 
 # From _typing.py, not used here:
 # FreqIndexT = TypeVar("FreqIndexT", "DatetimeIndex", "PeriodIndex", "TimedeltaIndex")
@@ -697,11 +698,11 @@ InterpolateOptions: TypeAlias = Literal[
 # Using List[int] here rather than Sequence[int] to disallow tuples.
 
 ScalarIndexer: TypeAlias = int | np.integer
-SequenceIndexer: TypeAlias = slice | list[int] | np.ndarray
+SequenceIndexer: TypeAlias = slice | list[int] | npt.NDArray[np.integer | np.bool]
 PositionalIndexer: TypeAlias = ScalarIndexer | SequenceIndexer
 PositionalIndexerTuple: TypeAlias = tuple[PositionalIndexer, PositionalIndexer]
 # PositionalIndexer2D = Union[PositionalIndexer, PositionalIndexerTuple] Not used in stubs
-TakeIndexer: TypeAlias = Sequence[int] | Sequence[np.integer] | npt.NDArray[np.integer]
+TakeIndexer: TypeAlias = Sequence[int | np.integer] | npt.NDArray[np.integer | np.bool]
 
 # Shared by functions such as drop and astype
 IgnoreRaise: TypeAlias = Literal["ignore", "raise"]
@@ -832,18 +833,6 @@ SliceType: TypeAlias = Hashable | None
 ## All types below this point are only used in pandas-stubs
 ######
 
-num: TypeAlias = complex
-
-DtypeNp = TypeVar("DtypeNp", bound=np.dtype[np.generic])
-KeysArgType: TypeAlias = Any
-ListLikeT = TypeVar("ListLikeT", bound=ListLike)
-ListLikeExceptSeriesAndStr: TypeAlias = (
-    MutableSequence[Any] | np.ndarray | tuple[Any, ...] | Index
-)
-ListLikeU: TypeAlias = Sequence | np.ndarray | Series | Index
-ListLikeHashable: TypeAlias = (
-    MutableSequence[HashableT] | np.ndarray | tuple[HashableT, ...] | range
-)
 StrLike: TypeAlias = str | np.str_
 
 ScalarT = TypeVar("ScalarT", bound=Scalar)
@@ -871,6 +860,17 @@ np_ndarray: TypeAlias = np.ndarray[ShapeT, np.dtype[GenericT]]
 np_1darray: TypeAlias = np.ndarray[tuple[int], np.dtype[GenericT]]
 np_2darray: TypeAlias = np.ndarray[tuple[int, int], np.dtype[GenericT]]
 
+DtypeNp = TypeVar("DtypeNp", bound=np.dtype[np.generic])
+KeysArgType: TypeAlias = Any
+ListLikeT = TypeVar("ListLikeT", bound=ListLike)
+ListLikeExceptSeriesAndStr: TypeAlias = (
+    MutableSequence[Any] | np_1darray[Any] | tuple[Any, ...] | Index
+)
+ListLikeU: TypeAlias = Sequence | np_1darray[Any] | Series | Index
+ListLikeHashable: TypeAlias = (
+    MutableSequence[HashableT] | np_1darray[Any] | tuple[HashableT, ...] | range
+)
+
 class SupportsDType(Protocol[GenericT_co]):
     @property
     def dtype(self) -> np.dtype[GenericT_co]: ...
diff --git a/pandas-stubs/core/algorithms.pyi b/pandas-stubs/core/algorithms.pyi
index 5174218c6..2b3b5c867 100644
--- a/pandas-stubs/core/algorithms.pyi
+++ b/pandas-stubs/core/algorithms.pyi
@@ -5,65 +5,75 @@ from typing import (
 )
 
 import numpy as np
-from pandas import (
-    Categorical,
-    CategoricalIndex,
-    Index,
-    IntervalIndex,
-    PeriodIndex,
-    Series,
-)
+from numpy import typing as npt
 from pandas.api.extensions import ExtensionArray
+from pandas.core.arrays.categorical import Categorical
+from pandas.core.indexes.base import Index
+from pandas.core.indexes.category import CategoricalIndex
+from pandas.core.indexes.datetimes import DatetimeIndex
+from pandas.core.indexes.interval import IntervalIndex
+from pandas.core.indexes.period import PeriodIndex
+from pandas.core.series import Series
 
 from pandas._typing import (
+    T_EXTENSION_ARRAY,
     AnyArrayLike,
+    GenericT,
     IntervalT,
     TakeIndexer,
     np_1darray,
+    np_ndarray,
 )
 
 # These are type: ignored because the Index types overlap due to inheritance but indices
 # with extension types return the same type while standard type return ndarray
-
-@overload
-def unique(  # pyright: ignore[reportOverlappingOverload]
-    values: PeriodIndex,
-) -> PeriodIndex: ...
 @overload
-def unique(values: CategoricalIndex) -> CategoricalIndex: ...  # type: ignore[overload-overlap]
+def unique(values: CategoricalIndex) -> CategoricalIndex: ...
 @overload
 def unique(values: IntervalIndex[IntervalT]) -> IntervalIndex[IntervalT]: ...
 @overload
-def unique(values: Index) -> np.ndarray: ...
+def unique(values: PeriodIndex) -> PeriodIndex: ...
+@overload
+def unique(values: DatetimeIndex) -> np_1darray[np.datetime64] | DatetimeIndex: ...
+@overload
+def unique(values: Index) -> np_1darray[Any] | Index: ...
 @overload
 def unique(values: Categorical) -> Categorical: ...
+
+# @overload
+# def unique(values: Series[Never]) -> np_1darray[Any] | ExtensionArray: ...
+# TODO: DatetimeArray python/mypy#19952
+# @overload
+# def unique(values: Series[Timestamp]) -> np_1darray[np.datetime64] | ExtensionArray: ...
+# @overload
+# def unique(values: Series[int]) -> np_1darray[np.integer] | ExtensionArray: ...
 @overload
-def unique(values: Series) -> np.ndarray | ExtensionArray: ...
+def unique(values: Series) -> np_1darray[Any] | ExtensionArray: ...
 @overload
-def unique(values: np.ndarray) -> np.ndarray: ...
+def unique(values: npt.NDArray[GenericT]) -> np_1darray[GenericT]: ...
 @overload
-def unique(values: ExtensionArray) -> ExtensionArray: ...
+def unique(values: T_EXTENSION_ARRAY) -> T_EXTENSION_ARRAY: ...
 @overload
 def factorize(
-    values: np.ndarray,
+    values: npt.NDArray[GenericT],
     sort: bool = ...,
     use_na_sentinel: bool = ...,
     size_hint: int | None = ...,
-) -> tuple[np.ndarray, np.ndarray]: ...
+) -> tuple[np_1darray[np.int64], np_1darray[GenericT]]: ...
 @overload
 def factorize(
     values: Index | Series,
     sort: bool = ...,
     use_na_sentinel: bool = ...,
     size_hint: int | None = ...,
-) -> tuple[np_1darray, Index]: ...
+) -> tuple[np_1darray[np.int64], Index]: ...
 @overload
 def factorize(
     values: Categorical,
     sort: bool = ...,
     use_na_sentinel: bool = ...,
     size_hint: int | None = ...,
-) -> tuple[np_1darray, Categorical]: ...
+) -> tuple[np_1darray[np.int64], Categorical]: ...
 def value_counts(
     values: AnyArrayLike | list | tuple,
     sort: bool = True,
@@ -73,9 +83,9 @@ def value_counts(
     dropna: bool = True,
 ) -> Series: ...
 def take(
-    arr: np.ndarray | ExtensionArray | Index | Series,
+    arr: np_ndarray[Any] | ExtensionArray | Index | Series,
     indices: TakeIndexer,
     axis: Literal[0, 1] = 0,
     allow_fill: bool = False,
     fill_value: Any = None,
-) -> np_1darray | ExtensionArray: ...
+) -> np_1darray[Any] | ExtensionArray: ...
diff --git a/pandas-stubs/core/arrays/base.pyi b/pandas-stubs/core/arrays/base.pyi
index 09bf2b0cb..e29153bed 100644
--- a/pandas-stubs/core/arrays/base.pyi
+++ b/pandas-stubs/core/arrays/base.pyi
@@ -35,7 +35,7 @@ class ExtensionArray:
     def __getitem__(self, item: ScalarIndexer) -> Any: ...
     @overload
     def __getitem__(self, item: SequenceIndexer) -> Self: ...
-    def __setitem__(self, key: int | slice | np.ndarray, value: Any) -> None: ...
+    def __setitem__(self, key: int | slice | npt.NDArray[Any], value: Any) -> None: ...
     def __len__(self) -> int: ...
     def __iter__(self) -> Iterator[Any]: ...
     def __contains__(self, item: object) -> bool | np.bool_: ...
@@ -83,7 +83,9 @@ class ExtensionArray:
         side: Literal["left", "right"] = ...,
         sorter: ListLike | None = ...,
     ) -> np.intp: ...
-    def factorize(self, use_na_sentinel: bool = True) -> tuple[np_1darray, Self]: ...
+    def factorize(
+        self, use_na_sentinel: bool = True
+    ) -> tuple[np_1darray[Any], Self]: ...
     def repeat(
         self, repeats: int | AnyArrayLikeInt | Sequence[int], axis: None = None
     ) -> Self: ...
diff --git a/pandas-stubs/core/arrays/boolean.pyi b/pandas-stubs/core/arrays/boolean.pyi
index 224bae066..ed0b61477 100644
--- a/pandas-stubs/core/arrays/boolean.pyi
+++ b/pandas-stubs/core/arrays/boolean.pyi
@@ -1,10 +1,12 @@
 from typing import Any
 
-import numpy as np
 from pandas.core.arrays.masked import BaseMaskedArray as BaseMaskedArray
 
 from pandas._libs.missing import NAType
-from pandas._typing import type_t
+from pandas._typing import (
+    np_ndarray_bool,
+    type_t,
+)
 
 from pandas.core.dtypes.base import ExtensionDtype as ExtensionDtype
 
@@ -16,7 +18,7 @@ class BooleanDtype(ExtensionDtype):
 
 class BooleanArray(BaseMaskedArray):
     def __init__(
-        self, values: np.ndarray, mask: np.ndarray, copy: bool = ...
+        self, values: np_ndarray_bool, mask: np_ndarray_bool, copy: bool = ...
     ) -> None: ...
     @property
     def dtype(self): ...
diff --git a/pandas-stubs/core/arrays/datetimelike.pyi b/pandas-stubs/core/arrays/datetimelike.pyi
index 1f4870898..d764e1ea4 100644
--- a/pandas-stubs/core/arrays/datetimelike.pyi
+++ b/pandas-stubs/core/arrays/datetimelike.pyi
@@ -5,7 +5,6 @@ from typing import (
     overload,
 )
 
-import numpy as np
 from pandas.core.arrays.base import (
     ExtensionArray,
     ExtensionOpsMixin,
@@ -65,7 +64,7 @@ class DatetimeLikeArrayMixin(ExtensionOpsMixin, ExtensionArray):
     def ravel(self, *args: Any, **kwargs: Any): ...
     def __iter__(self): ...
     @property
-    def asi8(self) -> np.ndarray: ...
+    def asi8(self) -> np_1darray[Any]: ...
     @property
     def nbytes(self): ...
     def __array__(
diff --git a/pandas-stubs/core/arrays/interval.pyi b/pandas-stubs/core/arrays/interval.pyi
index 52d23ac51..cfa2a570c 100644
--- a/pandas-stubs/core/arrays/interval.pyi
+++ b/pandas-stubs/core/arrays/interval.pyi
@@ -5,6 +5,7 @@ from typing import (
 )
 
 import numpy as np
+from numpy import typing as npt
 from pandas.core.arrays.base import ExtensionArray as ExtensionArray
 from pandas.core.indexes.base import Index
 from pandas.core.series import Series
@@ -105,6 +106,6 @@ class IntervalArray(IntervalMixin, ExtensionArray):
     def contains(self, other: Series) -> Series[bool]: ...
     @overload
     def contains(
-        self, other: Scalar | ExtensionArray | Index | np.ndarray
+        self, other: Scalar | ExtensionArray | Index | npt.NDArray[Any]
     ) -> np_1darray[np.bool]: ...
     def overlaps(self, other: Interval) -> bool: ...
diff --git a/pandas-stubs/core/arrays/masked.pyi b/pandas-stubs/core/arrays/masked.pyi
index c382e8e67..b9a2d5139 100644
--- a/pandas-stubs/core/arrays/masked.pyi
+++ b/pandas-stubs/core/arrays/masked.pyi
@@ -3,7 +3,6 @@ from typing import (
     overload,
 )
 
-import numpy as np
 from pandas.core.arrays import (
     ExtensionArray as ExtensionArray,
     ExtensionOpsMixin,
@@ -31,7 +30,7 @@ class BaseMaskedArray(ExtensionArray, ExtensionOpsMixin):
         dtype: npt.DTypeLike | None = ...,
         copy: bool = False,
         na_value: Scalar = ...,
-    ) -> np.ndarray: ...
+    ) -> np_1darray[Any]: ...
     __array_priority__: int = ...
     def __array__(
         self, dtype: NpDtype | None = None, copy: bool | None = None
diff --git a/pandas-stubs/core/base.pyi b/pandas-stubs/core/base.pyi
index ea3865add..5a3f4d709 100644
--- a/pandas-stubs/core/base.pyi
+++ b/pandas-stubs/core/base.pyi
@@ -151,7 +151,7 @@ class IndexOpsMixin(OpsMixin, Generic[S1, GenericT_co]):
     def is_monotonic_increasing(self) -> bool: ...
     def factorize(
         self, sort: bool = False, use_na_sentinel: bool = True
-    ) -> tuple[np_1darray, np_1darray | Index | Categorical]: ...
+    ) -> tuple[np_1darray[Any], np_1darray | Index | Categorical]: ...
     @overload
     def searchsorted(
         self,
@@ -174,7 +174,7 @@ NumListLike: TypeAlias = (
     | np_ndarray_anyint
     | np_ndarray_float
     | np_ndarray_complex
-    | dict[str, np.ndarray]
+    | dict[str, np_1darray[Any]]
     | Sequence[complex]
 )
 
diff --git a/pandas-stubs/core/computation/eval.pyi b/pandas-stubs/core/computation/eval.pyi
index 19df29909..a6927e1ef 100644
--- a/pandas-stubs/core/computation/eval.pyi
+++ b/pandas-stubs/core/computation/eval.pyi
@@ -25,4 +25,4 @@ def eval(
     level: int = 0,
     target: object | None = None,
     inplace: bool = False,
-) -> npt.NDArray | Scalar | DataFrame | Series | None: ...
+) -> npt.NDArray[Any] | Scalar | DataFrame | Series | None: ...
diff --git a/pandas-stubs/core/frame.pyi b/pandas-stubs/core/frame.pyi
index 93af6f79d..ec777e851 100644
--- a/pandas-stubs/core/frame.pyi
+++ b/pandas-stubs/core/frame.pyi
@@ -31,6 +31,7 @@ from typing import (
 
 from matplotlib.axes import Axes as PlotAxes
 import numpy as np
+from numpy import typing as npt
 from pandas import (
     Period,
     Timedelta,
@@ -162,8 +163,7 @@ from pandas._typing import (
     WriteBuffer,
     XMLParsers,
     np_2darray,
-    npt,
-    num,
+    np_ndarray_float,
 )
 
 from pandas.io.formats.style import Styler
@@ -206,7 +206,7 @@ class _iLocIndexerFrame(_iLocIndexer, Generic[_T]):
             Scalar
             | Series
             | DataFrame
-            | np.ndarray
+            | npt.NDArray[Any]
             | NAType
             | NaTType
             | Mapping[Hashable, Scalar | NAType | NaTType]
@@ -427,7 +427,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     @overload
     def __matmul__(self, other: Series) -> Series: ...
     @overload
-    def __matmul__(self, other: np.ndarray) -> Self: ...
+    def __matmul__(self, other: npt.NDArray[Any]) -> Self: ...
     def __rmatmul__(self, other): ...
     @overload
     @classmethod
@@ -832,7 +832,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     @overload
     def eval(
         self, expr: _str, *, inplace: Literal[False] = False, **kwargs: Any
-    ) -> Scalar | np.ndarray | Self | Series: ...
+    ) -> Scalar | npt.NDArray[Any] | Self | Series: ...
     @overload
     def select_dtypes(
         self, include: StrDtypeArg, exclude: _AstypeArgExtList | None = ...
@@ -970,7 +970,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
             Label
             | Series
             | Index
-            | np.ndarray
+            | npt.NDArray[Any]
             | Iterator[Hashable]
             | Sequence[Hashable]
         ),
@@ -987,7 +987,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
             Label
             | Series
             | Index
-            | np.ndarray
+            | npt.NDArray[Any]
             | Iterator[Hashable]
             | Sequence[Hashable]
         ),
@@ -1402,8 +1402,8 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     ) -> Self | Series: ...
     def melt(
         self,
-        id_vars: tuple | Sequence | np.ndarray | None = ...,
-        value_vars: tuple | Sequence | np.ndarray | None = ...,
+        id_vars: tuple | Sequence | npt.NDArray[Any] | None = ...,
+        value_vars: tuple | Sequence | npt.NDArray[Any] | None = ...,
         var_name: Scalar | None = None,
         value_name: Scalar = "value",
         col_level: int | _str | None = ...,
@@ -1676,7 +1676,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     @overload
     def quantile(
         self,
-        q: list[float] | np.ndarray,
+        q: Sequence[float] | np_ndarray_float,
         axis: Axis = ...,
         numeric_only: _bool = ...,
         interpolation: QuantileInterpolation = ...,
@@ -1778,7 +1778,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     def __add__(self, other: Any) -> Self: ...
     def add(
         self,
-        other: num | ListLike | DataFrame,
+        other: complex | ListLike | DataFrame,
         axis: Axis | None = "columns",
         level: Level | None = None,
         fill_value: float | None = None,
@@ -1786,7 +1786,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     def __radd__(self, other: Any) -> Self: ...
     def radd(
         self,
-        other,
+        other: complex | ListLike | DataFrame,
         axis: Axis = "columns",
         level: Level | None = None,
         fill_value: float | None = None,
@@ -1794,7 +1794,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     def __sub__(self, other: Any) -> Self: ...
     def sub(
         self,
-        other: num | ListLike | DataFrame,
+        other: complex | ListLike | DataFrame,
         axis: Axis | None = ...,
         level: Level | None = ...,
         fill_value: float | None = None,
@@ -1802,7 +1802,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     def __rsub__(self, other: Any) -> Self: ...
     def rsub(
         self,
-        other,
+        other: complex | ListLike | DataFrame,
         axis: Axis = ...,
         level: Level | None = ...,
         fill_value: float | None = None,
@@ -2005,20 +2005,14 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         include: Literal["all"] | list[Dtype] | None = ...,
         exclude: list[Dtype] | None = ...,
     ) -> Self: ...
-    def div(
-        self,
-        other: num | ListLike | DataFrame,
-        axis: Axis | None = ...,
-        level: Level | None = ...,
-        fill_value: float | None = None,
-    ) -> Self: ...
-    def divide(
+    def truediv(
         self,
-        other: num | ListLike | DataFrame,
+        other: complex | ListLike | DataFrame,
         axis: Axis | None = ...,
         level: Level | None = ...,
         fill_value: float | None = None,
     ) -> Self: ...
+    div = truediv
     @final
     def droplevel(self, level: Level | list[Level], axis: Axis = 0) -> Self: ...
     def eq(self, other, axis: Axis = "columns", level: Level | None = ...) -> Self: ...
@@ -2074,7 +2068,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     def first_valid_index(self) -> Scalar: ...
     def floordiv(
         self,
-        other: num | ListLike | DataFrame,
+        other: float | ListLike | DataFrame,
         axis: Axis | None = ...,
         level: Level | None = ...,
         fill_value: float | None = None,
@@ -2144,7 +2138,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         cond: (
             Series
             | DataFrame
-            | np.ndarray
+            | npt.NDArray[Any]
             | Callable[[DataFrame], DataFrame]
             | Callable[[Any], _bool]
         ),
@@ -2160,7 +2154,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         cond: (
             Series
             | DataFrame
-            | np.ndarray
+            | npt.NDArray[Any]
             | Callable[[DataFrame], DataFrame]
             | Callable[[Any], _bool]
         ),
@@ -2200,21 +2194,14 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     ) -> Series: ...
     def mod(
         self,
-        other: num | ListLike | DataFrame,
+        other: float | ListLike | DataFrame,
         axis: Axis | None = ...,
         level: Level | None = ...,
         fill_value: float | None = None,
     ) -> Self: ...
     def mul(
         self,
-        other: num | ListLike | DataFrame,
-        axis: Axis | None = ...,
-        level: Level | None = ...,
-        fill_value: float | None = None,
-    ) -> Self: ...
-    def multiply(
-        self,
-        other: num | ListLike | DataFrame,
+        other: complex | ListLike | DataFrame,
         axis: Axis | None = ...,
         level: Level | None = ...,
         fill_value: float | None = None,
@@ -2232,7 +2219,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     def pop(self, item: _str) -> Series: ...
     def pow(
         self,
-        other: num | ListLike | DataFrame,
+        other: complex | ListLike | DataFrame,
         axis: Axis | None = ...,
         level: Level | None = ...,
         fill_value: float | None = None,
@@ -2554,13 +2541,6 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     ) -> _str: ...
     @final
     def to_xarray(self) -> xr.Dataset: ...
-    def truediv(
-        self,
-        other: num | ListLike | DataFrame,
-        axis: Axis | None = "columns",
-        level: Level | None = None,
-        fill_value: float | None = None,
-    ) -> Self: ...
     @final
     def truncate(
         self,
@@ -2601,7 +2581,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         cond: (
             Series
             | DataFrame
-            | np.ndarray
+            | npt.NDArray[Any]
             | Callable[[DataFrame], DataFrame]
             | Callable[[Any], _bool]
         ),
@@ -2617,7 +2597,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         cond: (
             Series
             | DataFrame
-            | np.ndarray
+            | npt.NDArray[Any]
             | Callable[[DataFrame], DataFrame]
             | Callable[[Any], _bool]
         ),
diff --git a/pandas-stubs/core/generic.pyi b/pandas-stubs/core/generic.pyi
index 1b292b843..48402be7c 100644
--- a/pandas-stubs/core/generic.pyi
+++ b/pandas-stubs/core/generic.pyi
@@ -21,7 +21,7 @@ from typing import (
     overload,
 )
 
-import numpy as np
+from numpy import typing as npt
 from pandas import Index
 import pandas.core.indexing as indexing
 from pandas.core.resample import DatetimeIndexResampler
@@ -100,7 +100,7 @@ class NDFrame(indexing.IndexingMixin):
     @property
     def empty(self) -> _bool: ...
     __array_priority__: int = ...
-    def __array__(self, dtype=...) -> np.ndarray: ...
+    def __array__(self, dtype=...) -> npt.NDArray[Any]: ...
     @final
     def to_excel(
         self,
diff --git a/pandas-stubs/core/groupby/generic.pyi b/pandas-stubs/core/groupby/generic.pyi
index 7c058cd79..3279e31b0 100644
--- a/pandas-stubs/core/groupby/generic.pyi
+++ b/pandas-stubs/core/groupby/generic.pyi
@@ -19,7 +19,7 @@ from typing import (
 )
 
 from matplotlib.axes import Axes as PlotAxes
-import numpy as np
+from numpy import typing as npt
 from pandas.core.frame import DataFrame
 from pandas.core.groupby.base import TransformReductionListType
 from pandas.core.groupby.groupby import (
@@ -418,7 +418,7 @@ class DataFrameGroupBy(GroupBy[DataFrame], Generic[ByT, _TT]):
     def plot(self) -> GroupByPlot[Self]: ...
     def corr(
         self,
-        method: str | Callable[[np.ndarray, np.ndarray], float] = ...,
+        method: str | Callable[[npt.NDArray[Any], npt.NDArray[Any]], float] = ...,
         min_periods: int = ...,
         numeric_only: bool = False,
     ) -> DataFrame: ...
diff --git a/pandas-stubs/core/groupby/groupby.pyi b/pandas-stubs/core/groupby/groupby.pyi
index c5bc50110..abb89e22b 100644
--- a/pandas-stubs/core/groupby/groupby.pyi
+++ b/pandas-stubs/core/groupby/groupby.pyi
@@ -240,7 +240,7 @@ class GroupBy(BaseGroupBy[NDFrameT]):
         adjust: bool = ...,
         ignore_na: bool = ...,
         axis: Axis = ...,
-        times: str | np.ndarray | Series | np.timedelta64 | None = ...,
+        times: str | npt.NDArray[Any] | Series | np.timedelta64 | None = ...,
         method: CalculationMethod = ...,
         *,
         selection: IndexLabel | None = ...,
diff --git a/pandas-stubs/core/groupby/grouper.pyi b/pandas-stubs/core/groupby/grouper.pyi
index 8ac7f901a..30900f48a 100644
--- a/pandas-stubs/core/groupby/grouper.pyi
+++ b/pandas-stubs/core/groupby/grouper.pyi
@@ -30,6 +30,8 @@ from pandas._typing import (
 )
 from pandas.util._decorators import cache_readonly
 
+from pandas.io.formats.printing import PrettyDict
+
 class Grouper:
     key: KeysArgType | None
     level: Level | ListLikeHashable[Level] | None
@@ -73,3 +75,5 @@ class Grouping:
     def result_index(self) -> Index: ...
     @cache_readonly
     def group_index(self) -> Index: ...
+    @cache_readonly
+    def groups(self) -> PrettyDict[Hashable, Index]: ...
diff --git a/pandas-stubs/core/groupby/ops.pyi b/pandas-stubs/core/groupby/ops.pyi
index 740eeb760..9a77edc6d 100644
--- a/pandas-stubs/core/groupby/ops.pyi
+++ b/pandas-stubs/core/groupby/ops.pyi
@@ -53,7 +53,7 @@ class BaseGrouper:
     @final
     def size(self) -> Series: ...
     @cache_readonly
-    def groups(self) -> dict[Hashable, np.ndarray]: ...
+    def groups(self) -> dict[Hashable, Index]: ...
     @final
     @cache_readonly
     def is_monotonic(self) -> bool: ...
diff --git a/pandas-stubs/core/indexers.pyi b/pandas-stubs/core/indexers.pyi
index c6bcc6d84..6d5db972d 100644
--- a/pandas-stubs/core/indexers.pyi
+++ b/pandas-stubs/core/indexers.pyi
@@ -1,13 +1,21 @@
 from typing import Any
 
 import numpy as np
+from numpy import typing as npt
 
-def check_array_indexer(arrayArrayLike, indexer): ...
+from pandas._typing import (
+    AnyArrayLike,
+    np_1darray,
+)
+
+def check_array_indexer(
+    arrayArrayLike: AnyArrayLike, indexer: AnyArrayLike
+) -> np_1darray[np.bool_]: ...
 
 class BaseIndexer:
     def __init__(
         self,
-        index_array: np.ndarray | None = ...,
+        index_array: npt.NDArray[Any] | None = ...,
         window_size: int = ...,
         **kwargs: Any,
     ) -> None: ...
@@ -17,12 +25,12 @@ class BaseIndexer:
         min_periods: int | None = ...,
         center: bool | None = ...,
         closed: str | None = ...,
-    ) -> tuple[np.ndarray, np.ndarray]: ...
+    ) -> tuple[npt.NDArray[Any], npt.NDArray[Any]]: ...
 
 class VariableOffsetWindowIndexer(BaseIndexer):
     def __init__(
         self,
-        index_array: np.ndarray | None = ...,
+        index_array: npt.NDArray[Any] | None = ...,
         window_size: int = ...,
         index=...,
         offset=...,
@@ -34,7 +42,7 @@ class VariableOffsetWindowIndexer(BaseIndexer):
         min_periods: int | None = ...,
         center: bool | None = ...,
         closed: str | None = ...,
-    ) -> tuple[np.ndarray, np.ndarray]: ...
+    ) -> tuple[npt.NDArray[Any], npt.NDArray[Any]]: ...
 
 class FixedForwardWindowIndexer(BaseIndexer):
     def get_window_bounds(
@@ -43,4 +51,4 @@ class FixedForwardWindowIndexer(BaseIndexer):
         min_periods: int | None = ...,
         center: bool | None = ...,
         closed: str | None = ...,
-    ) -> tuple[np.ndarray, np.ndarray]: ...
+    ) -> tuple[npt.NDArray[Any], npt.NDArray[Any]]: ...
diff --git a/pandas-stubs/core/indexers/objects.pyi b/pandas-stubs/core/indexers/objects.pyi
index 2187cf885..74541b805 100644
--- a/pandas-stubs/core/indexers/objects.pyi
+++ b/pandas-stubs/core/indexers/objects.pyi
@@ -1,13 +1,16 @@
 from typing import Any
 
-import numpy as np
-from pandas import DatetimeIndex
+from numpy import typing as npt
+from pandas.core.indexes.datetimes import DatetimeIndex
 
 from pandas._libs.tslibs import BaseOffset
 
 class BaseIndexer:
     def __init__(
-        self, index_array: np.ndarray | None = None, window_size: int = 0, **kwargs: Any
+        self,
+        index_array: npt.NDArray[Any] | None = None,
+        window_size: int = 0,
+        **kwargs: Any,
     ) -> None: ...
     def get_window_bounds(
         self,
@@ -16,14 +19,14 @@ class BaseIndexer:
         center: bool | None,
         closed: str | None = None,
         step: int | None = None,
-    ) -> tuple[np.ndarray, np.ndarray]: ...
+    ) -> tuple[npt.NDArray[Any], npt.NDArray[Any]]: ...
 
 class FixedForwardWindowIndexer(BaseIndexer): ...
 
 class VariableOffsetWindowIndexer(BaseIndexer):
     def __init__(
         self,
-        index_array: np.ndarray | None = None,
+        index_array: npt.NDArray[Any] | None = None,
         window_size: int = 0,
         index: DatetimeIndex | None = None,
         offset: BaseOffset | None = None,
diff --git a/pandas-stubs/core/indexes/base.pyi b/pandas-stubs/core/indexes/base.pyi
index 8252a0228..318c4689c 100644
--- a/pandas-stubs/core/indexes/base.pyi
+++ b/pandas-stubs/core/indexes/base.pyi
@@ -106,6 +106,8 @@ from pandas._typing import (
     type_t,
 )
 
+from pandas.io.formats.printing import PrettyDict
+
 class InvalidIndexError(Exception): ...
 
 class Index(IndexOpsMixin[S1], ElementOpsMixin[S1]):
@@ -469,7 +471,7 @@ class Index(IndexOpsMixin[S1], ElementOpsMixin[S1]):
         sort: bool = False,
     ) -> Index: ...
     @property
-    def values(self) -> np_1darray: ...
+    def values(self) -> np_1darray[Any]: ...
     def memory_usage(self, deep: bool = False): ...
     @overload
     def where(
@@ -521,7 +523,7 @@ class Index(IndexOpsMixin[S1], ElementOpsMixin[S1]):
     @final
     def get_indexer_for(self, target, **kwargs: Any): ...
     @final
-    def groupby(self, values) -> dict[Hashable, np.ndarray]: ...
+    def groupby(self, values) -> PrettyDict[Hashable, Self]: ...
     def map(self, mapper, na_action=...) -> Index: ...
     def isin(self, values, level=...) -> np_1darray[np.bool]: ...
     def slice_indexer(
diff --git a/pandas-stubs/core/indexes/category.pyi b/pandas-stubs/core/indexes/category.pyi
index dd9f12471..d2112cb3e 100644
--- a/pandas-stubs/core/indexes/category.pyi
+++ b/pandas-stubs/core/indexes/category.pyi
@@ -2,9 +2,12 @@ from collections.abc import (
     Hashable,
     Iterable,
 )
-from typing import final
+from typing import (
+    Any,
+    final,
+)
 
-import numpy as np
+from numpy import typing as npt
 from pandas.core import accessor
 from pandas.core.arrays.categorical import Categorical
 from pandas.core.indexes.base import Index
@@ -14,7 +17,7 @@ from typing_extensions import Self
 from pandas._typing import S1
 
 class CategoricalIndex(ExtensionIndex[S1], accessor.PandasDelegate):
-    codes: np.ndarray = ...
+    codes: npt.NDArray[Any] = ...
     categories: Index = ...
     @property
     def array(self) -> Categorical: ...  # type: ignore[override] # pyrefly: ignore[bad-override]
diff --git a/pandas-stubs/core/indexes/period.pyi b/pandas-stubs/core/indexes/period.pyi
index 84abc62ea..4ae2a9457 100644
--- a/pandas-stubs/core/indexes/period.pyi
+++ b/pandas-stubs/core/indexes/period.pyi
@@ -6,6 +6,7 @@ from typing import (
 )
 
 import numpy as np
+from numpy import typing as npt
 import pandas as pd
 from pandas import Index
 from pandas.core.indexes.accessors import PeriodIndexFieldOps
@@ -67,7 +68,7 @@ class PeriodIndex(DatetimeIndexOpsMixin[pd.Period, np.object_], PeriodIndexField
     def asof_locs(
         self,
         where: pd.DatetimeIndex | PeriodIndex,
-        mask: np_1darray[np.bool_],
+        mask: npt.NDArray[np.bool_],
     ) -> np_1darray[np.intp]: ...
     @property
     def is_full(self) -> bool: ...
diff --git a/pandas-stubs/core/indexes/timedeltas.pyi b/pandas-stubs/core/indexes/timedeltas.pyi
index dd1a8b189..30df91413 100644
--- a/pandas-stubs/core/indexes/timedeltas.pyi
+++ b/pandas-stubs/core/indexes/timedeltas.pyi
@@ -36,7 +36,6 @@ from pandas._typing import (
     np_ndarray_dt,
     np_ndarray_float,
     np_ndarray_td,
-    num,
 )
 
 _NUM_FACTOR: TypeAlias = Just[int] | Just[float] | np.integer | np.floating
@@ -125,7 +124,7 @@ class TimedeltaIndex(
     ) -> Index[float]: ...
     @overload  # type: ignore[override]
     # pyrefly: ignore  # bad-override
-    def __floordiv__(self, other: num | Sequence[float]) -> Self: ...
+    def __floordiv__(self, other: float | Sequence[float]) -> Self: ...
     @overload
     def __floordiv__(  # pyright: ignore[reportIncompatibleMethodOverride]
         self, other: dt.timedelta | Sequence[dt.timedelta]
diff --git a/pandas-stubs/core/resample.pyi b/pandas-stubs/core/resample.pyi
index 91299803e..6efd26b8a 100644
--- a/pandas-stubs/core/resample.pyi
+++ b/pandas-stubs/core/resample.pyi
@@ -12,16 +12,15 @@ from typing import (
 )
 
 import numpy as np
-from pandas import (
-    DataFrame,
-    Series,
-    Timedelta,
-)
+from numpy import typing as npt
+from pandas.core.frame import DataFrame
 from pandas.core.groupby.generic import SeriesGroupBy
 from pandas.core.groupby.groupby import BaseGroupBy
 from pandas.core.groupby.grouper import Grouper
+from pandas.core.series import Series
 from typing_extensions import Self
 
+from pandas._libs.tslibs.timedeltas import Timedelta
 from pandas._typing import (
     S1,
     Axis,
@@ -30,7 +29,6 @@ from pandas._typing import (
     Scalar,
     TimeGrouperOrigin,
     TimestampConvention,
-    npt,
 )
 
 _FrameGroupByFunc: TypeAlias = (
diff --git a/pandas-stubs/core/reshape/melt.pyi b/pandas-stubs/core/reshape/melt.pyi
index 68a9ee57d..2c9429edd 100644
--- a/pandas-stubs/core/reshape/melt.pyi
+++ b/pandas-stubs/core/reshape/melt.pyi
@@ -1,14 +1,18 @@
-from collections.abc import Hashable
+from collections.abc import (
+    Hashable,
+    Sequence,
+)
+from typing import Any
 
-import numpy as np
+from numpy import typing as npt
 from pandas.core.frame import DataFrame
 
 from pandas._typing import HashableT
 
 def melt(
     frame: DataFrame,
-    id_vars: tuple | list | np.ndarray | None = None,
-    value_vars: tuple | list | np.ndarray | None = None,
+    id_vars: Sequence[Hashable] | npt.NDArray[Any] | None = None,
+    value_vars: Sequence[Hashable] | npt.NDArray[Any] | None = None,
     var_name: str | None = None,
     value_name: Hashable = "value",
     col_level: int | str | None = None,
diff --git a/pandas-stubs/core/reshape/pivot.pyi b/pandas-stubs/core/reshape/pivot.pyi
index 8e8382798..9f76c0955 100644
--- a/pandas-stubs/core/reshape/pivot.pyi
+++ b/pandas-stubs/core/reshape/pivot.pyi
@@ -6,6 +6,7 @@ from collections.abc import (
 )
 import datetime
 from typing import (
+    Any,
     Literal,
     TypeAlias,
     overload,
@@ -85,7 +86,7 @@ def pivot_table(
     values: _PivotTableValuesTypes = ...,
     *,
     index: Grouper,
-    columns: _PivotTableColumnsTypes | Index | npt.NDArray = ...,
+    columns: _PivotTableColumnsTypes | Index | npt.NDArray[Any] = ...,
     aggfunc: (
         _PivotAggFunc | Sequence[_PivotAggFunc] | Mapping[Hashable, _PivotAggFunc]
     ) = ...,
@@ -100,7 +101,7 @@ def pivot_table(
 def pivot_table(
     data: DataFrame,
     values: _PivotTableValuesTypes = ...,
-    index: _PivotTableIndexTypes | Index | npt.NDArray = ...,
+    index: _PivotTableIndexTypes | Index | npt.NDArray[Any] = ...,
     *,
     columns: Grouper,
     aggfunc: (
diff --git a/pandas-stubs/core/reshape/tile.pyi b/pandas-stubs/core/reshape/tile.pyi
index 0eed14683..c9a4e3efd 100644
--- a/pandas-stubs/core/reshape/tile.pyi
+++ b/pandas-stubs/core/reshape/tile.pyi
@@ -1,5 +1,6 @@
 from collections.abc import Sequence
 from typing import (
+    Any,
     Literal,
     overload,
 )
@@ -19,12 +20,15 @@ from pandas.core.series import Series
 from pandas._typing import (
     IntervalT,
     Label,
+    np_1darray,
+    np_ndarray_anyint,
+    np_ndarray_float,
     npt,
 )
 
 @overload
 def cut(
-    x: Index | npt.NDArray | Sequence[int] | Sequence[float],
+    x: Index | npt.NDArray[Any] | Sequence[int] | Sequence[float],
     bins: int | Series | Index[int] | Index[float] | Sequence[int] | Sequence[float],
     right: bool = ...,
     *,
@@ -34,10 +38,10 @@ def cut(
     include_lowest: bool = ...,
     duplicates: Literal["raise", "drop"] = ...,
     ordered: bool = ...,
-) -> tuple[npt.NDArray[np.intp], npt.NDArray]: ...
+) -> tuple[np_1darray[np.intp], np_1darray[np.double]]: ...
 @overload
 def cut(
-    x: Index | npt.NDArray | Sequence[int] | Sequence[float],
+    x: Index | npt.NDArray[Any] | Sequence[int] | Sequence[float],
     bins: IntervalIndex[IntervalT],
     right: bool = ...,
     *,
@@ -47,7 +51,7 @@ def cut(
     include_lowest: bool = ...,
     duplicates: Literal["raise", "drop"] = ...,
     ordered: bool = ...,
-) -> tuple[npt.NDArray[np.intp], IntervalIndex[IntervalT]]: ...
+) -> tuple[np_1darray[np.intp], IntervalIndex[IntervalT]]: ...
 @overload
 def cut(  # pyright: ignore[reportOverlappingOverload]
     x: Series[Timestamp],
@@ -92,7 +96,7 @@ def cut(
     include_lowest: bool = ...,
     duplicates: Literal["raise", "drop"] = ...,
     ordered: bool = ...,
-) -> tuple[Series, npt.NDArray]: ...
+) -> tuple[Series, np_1darray[np.double]]: ...
 @overload
 def cut(
     x: Series,
@@ -108,7 +112,7 @@ def cut(
 ) -> tuple[Series, IntervalIndex]: ...
 @overload
 def cut(
-    x: Index | npt.NDArray | Sequence[int] | Sequence[float],
+    x: Index | npt.NDArray[Any] | Sequence[int] | Sequence[float],
     bins: int | Series | Index[int] | Index[float] | Sequence[int] | Sequence[float],
     right: bool = ...,
     labels: Sequence[Label] | None = ...,
@@ -118,10 +122,10 @@ def cut(
     include_lowest: bool = ...,
     duplicates: Literal["raise", "drop"] = ...,
     ordered: bool = ...,
-) -> tuple[Categorical, npt.NDArray]: ...
+) -> tuple[Categorical, np_1darray[np.double]]: ...
 @overload
 def cut(
-    x: Index | npt.NDArray | Sequence[int] | Sequence[float],
+    x: Index | npt.NDArray[Any] | Sequence[int] | Sequence[float],
     bins: IntervalIndex[IntervalT],
     right: bool = ...,
     labels: Sequence[Label] | None = ...,
@@ -134,7 +138,7 @@ def cut(
 ) -> tuple[Categorical, IntervalIndex[IntervalT]]: ...
 @overload
 def cut(
-    x: Index | npt.NDArray | Sequence[int] | Sequence[float],
+    x: Index | npt.NDArray[Any] | Sequence[int] | Sequence[float],
     bins: (
         int
         | Series
@@ -152,7 +156,7 @@ def cut(
     include_lowest: bool = ...,
     duplicates: Literal["raise", "drop"] = ...,
     ordered: bool = ...,
-) -> npt.NDArray[np.intp]: ...
+) -> np_1darray[np.intp]: ...
 @overload
 def cut(
     x: Series[Timestamp],
@@ -194,7 +198,7 @@ def cut(
 ) -> Series: ...
 @overload
 def cut(
-    x: Index | npt.NDArray | Sequence[int] | Sequence[float],
+    x: Index | npt.NDArray[Any] | Sequence[int] | Sequence[float],
     bins: (
         int
         | Series
@@ -214,59 +218,70 @@ def cut(
 ) -> Categorical: ...
 @overload
 def qcut(
-    x: Index | npt.NDArray | Sequence[int] | Sequence[float],
-    q: int | Sequence[float] | Series[float] | Index[float] | npt.NDArray,
-    *,
+    x: Index | npt.NDArray[Any] | Sequence[int] | Sequence[float],
+    q: int | Sequence[float] | np_ndarray_float | Index[float] | Series[float],
     labels: Literal[False],
     retbins: Literal[False] = False,
-    precision: int = ...,
-    duplicates: Literal["raise", "drop"] = ...,
-) -> npt.NDArray[np.intp]: ...
+    precision: int = 3,
+    duplicates: Literal["raise", "drop"] = "raise",
+) -> np_1darray[np.intp]: ...
 @overload
 def qcut(
-    x: Index | npt.NDArray | Sequence[int] | Sequence[float],
-    q: int | Sequence[float] | Series[float] | Index[float] | npt.NDArray,
-    labels: Sequence[Label] | None = ...,
+    x: Index | npt.NDArray[Any] | Sequence[int] | Sequence[float],
+    q: int | Sequence[float] | np_ndarray_float | Index[float] | Series[float],
+    labels: Sequence[Label] | None = None,
     retbins: Literal[False] = False,
-    precision: int = ...,
-    duplicates: Literal["raise", "drop"] = ...,
+    precision: int = 3,
+    duplicates: Literal["raise", "drop"] = "raise",
 ) -> Categorical: ...
 @overload
 def qcut(
     x: Series,
-    q: int | Sequence[float] | Series[float] | Index[float] | npt.NDArray,
+    q: int | Sequence[float] | np_ndarray_float | Index[float] | Series[float],
     labels: Literal[False] | Sequence[Label] | None = ...,
     retbins: Literal[False] = False,
-    precision: int = ...,
-    duplicates: Literal["raise", "drop"] = ...,
+    precision: int = 3,
+    duplicates: Literal["raise", "drop"] = "raise",
 ) -> Series: ...
 @overload
 def qcut(
-    x: Index | npt.NDArray | Sequence[int] | Sequence[float],
-    q: int | Sequence[float] | Series[float] | Index[float] | npt.NDArray,
-    *,
+    x: (
+        Sequence[float]
+        | np_ndarray_anyint
+        | np_ndarray_float
+        | Index[int]
+        | Index[float]
+    ),
+    q: int | Sequence[float] | np_ndarray_float | Index[float] | Series[float],
     labels: Literal[False],
     retbins: Literal[True],
-    precision: int = ...,
-    duplicates: Literal["raise", "drop"] = ...,
-) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.double]]: ...
+    precision: int = 3,
+    duplicates: Literal["raise", "drop"] = "raise",
+    # double when there are nan's
+) -> tuple[np_1darray[np.intp | np.double], np_1darray[np.double]]: ...
 @overload
 def qcut(
-    x: Series,
-    q: int | Sequence[float] | Series[float] | Index[float] | npt.NDArray,
+    x: Series[int] | Series[float],
+    q: int | Sequence[float] | np_ndarray_float | Index[float] | Series[float],
     labels: Literal[False] | Sequence[Label] | None = ...,
     *,
     retbins: Literal[True],
-    precision: int = ...,
-    duplicates: Literal["raise", "drop"] = ...,
-) -> tuple[Series, npt.NDArray[np.double]]: ...
+    precision: int = 3,
+    duplicates: Literal["raise", "drop"] = "raise",
+) -> tuple[Series, np_1darray[np.double]]: ...
 @overload
 def qcut(
-    x: Index | npt.NDArray | Sequence[int] | Sequence[float],
-    q: int | Sequence[float] | Series[float] | Index[float] | npt.NDArray,
+    x: (
+        Sequence[float]
+        | np_ndarray_anyint
+        | np_ndarray_float
+        | Index[int]
+        | Index[float]
+    ),
+    q: int | Sequence[float] | np_ndarray_float | Index[float] | Series[float],
     labels: Sequence[Label] | None = ...,
     *,
     retbins: Literal[True],
-    precision: int = ...,
-    duplicates: Literal["raise", "drop"] = ...,
-) -> tuple[Categorical, npt.NDArray[np.double]]: ...
+    precision: int = 3,
+    duplicates: Literal["raise", "drop"] = "raise",
+) -> tuple[Categorical, np_1darray[np.double]]: ...
diff --git a/pandas-stubs/core/series.pyi b/pandas-stubs/core/series.pyi
index c05af4813..e2a779b2a 100644
--- a/pandas-stubs/core/series.pyi
+++ b/pandas-stubs/core/series.pyi
@@ -47,6 +47,7 @@ from matplotlib.axes import (
     SubplotBase,
 )
 import numpy as np
+from numpy import typing as npt
 from pandas import (
     Index,
     Period,
@@ -60,8 +61,12 @@ from pandas.core.api import (
     Int32Dtype as Int32Dtype,
     Int64Dtype as Int64Dtype,
 )
+from pandas.core.arrays.base import ExtensionArray
 from pandas.core.arrays.boolean import BooleanDtype
-from pandas.core.arrays.categorical import CategoricalAccessor
+from pandas.core.arrays.categorical import (
+    Categorical,
+    CategoricalAccessor,
+)
 from pandas.core.arrays.datetimes import DatetimeArray
 from pandas.core.arrays.timedeltas import TimedeltaArray
 from pandas.core.base import (
@@ -210,8 +215,6 @@ from pandas._typing import (
     np_ndarray_float,
     np_ndarray_str,
     np_ndarray_td,
-    npt,
-    num,
 )
 
 from pandas.core.dtypes.base import ExtensionDtype
@@ -296,9 +299,9 @@ class _LocIndexerSeries(_LocIndexer, Generic[S1]):
         value: S1 | ArrayLike | Series[S1] | None,
     ) -> None: ...
 
-_DataLike: TypeAlias = ArrayLike | dict[str, np.ndarray] | SequenceNotStr[S1]
+_DataLike: TypeAlias = ArrayLike | dict[str, npt.NDArray[Any]] | SequenceNotStr[S1]
 _DataLikeS1: TypeAlias = (
-    ArrayLike | dict[_str, np.ndarray] | Sequence[S1] | IndexOpsMixin[S1]
+    ArrayLike | dict[_str, npt.NDArray[Any]] | Sequence[S1] | IndexOpsMixin[S1]
 )
 
 class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
@@ -510,8 +513,8 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
     @name.setter
     def name(self, value: Hashable | None) -> None: ...
     @property
-    def values(self) -> ArrayLike: ...
-    def ravel(self, order: _str = ...) -> np.ndarray: ...
+    def values(self) -> np_1darray[Any] | ExtensionArray | Categorical: ...
+    def ravel(self, order: _str = ...) -> np_1darray[Any]: ...
     def __len__(self) -> int: ...
     def view(self, dtype=...) -> Series[S1]: ...
     @final
@@ -806,13 +809,13 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
     def count(self) -> int: ...
     def mode(self, dropna=True) -> Series[S1]: ...
     @overload
-    def unique(self: Series[Never]) -> np.ndarray: ...  # type: ignore[overload-overlap]
+    def unique(self: Series[Never]) -> np_1darray[Any]: ...  # type: ignore[overload-overlap]
     @overload
     def unique(self: Series[Timestamp]) -> DatetimeArray: ...  # type: ignore[overload-overlap]
     @overload
     def unique(self: Series[Timedelta]) -> TimedeltaArray: ...  # type: ignore[overload-overlap]
     @overload
-    def unique(self) -> np.ndarray: ...
+    def unique(self) -> np_1darray[Any]: ...
     @overload
     def drop_duplicates(
         self,
@@ -889,20 +892,21 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
     def dot(self, other: DataFrame) -> Series[S1]: ...
     @overload
     def dot(
-        self, other: ArrayLike | dict[_str, np.ndarray] | Sequence[S1] | Index[S1]
-    ) -> np.ndarray: ...
+        self,
+        other: ArrayLike | dict[_str, npt.NDArray[Any]] | Sequence[S1] | Index[S1],
+    ) -> npt.NDArray[Any]: ...
     @overload
     def __matmul__(self, other: Series) -> Scalar: ...
     @overload
     def __matmul__(self, other: DataFrame) -> Series: ...
     @overload
-    def __matmul__(self, other: np.ndarray) -> np.ndarray: ...
+    def __matmul__(self, other: npt.NDArray[Any]) -> npt.NDArray[Any]: ...
     @overload
     def __rmatmul__(self, other: Series) -> Scalar: ...
     @overload
     def __rmatmul__(self, other: DataFrame) -> Series: ...
     @overload
-    def __rmatmul__(self, other: np.ndarray) -> np.ndarray: ...
+    def __rmatmul__(self, other: npt.NDArray[Any]) -> npt.NDArray[Any]: ...
     @overload
     def searchsorted(
         self,
@@ -1327,7 +1331,7 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
         n: int | None = None,
         frac: float | None = None,
         replace: _bool = False,
-        weights: _str | ListLike | np.ndarray | None = None,
+        weights: _str | ListLike | npt.NDArray[Any] | None = None,
         random_state: RandomState | None = None,
         axis: AxisIndex | None = None,
         ignore_index: _bool = False,
@@ -1546,7 +1550,7 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
         cond: (
             Series[S1]
             | Series[_bool]
-            | np.ndarray
+            | npt.NDArray[Any]
             | Callable[[Series[S1]], Series[bool]]
             | Callable[[S1], bool]
         ),
@@ -1562,7 +1566,7 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
         cond: (
             Series[S1]
             | Series[_bool]
-            | np.ndarray
+            | npt.NDArray[Any]
             | Callable[[Series[S1]], Series[bool]]
             | Callable[[S1], bool]
         ),
@@ -1578,7 +1582,7 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
         cond: (
             Series[S1]
             | Series[_bool]
-            | np.ndarray
+            | npt.NDArray[Any]
             | Callable[[Series[S1]], Series[bool]]
             | Callable[[S1], bool]
         ),
@@ -1594,7 +1598,7 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
         cond: (
             Series[S1]
             | Series[_bool]
-            | np.ndarray
+            | npt.NDArray[Any]
             | Callable[[Series[S1]], Series[bool]]
             | Callable[[S1], bool]
         ),
@@ -1610,8 +1614,8 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
             tuple[
                 Sequence[bool]
                 | Series[bool]
-                | Callable[[Series], Series | np.ndarray | Sequence[bool]],
-                ListLikeU | Scalar | Callable[[Series], Series | np.ndarray],
+                | Callable[[Series], Series | npt.NDArray[Any] | Sequence[bool]],
+                ListLikeU | Scalar | Callable[[Series], Series | npt.NDArray[Any]],
             ],
         ],
     ) -> Series: ...
@@ -2903,9 +2907,9 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
         fill_value: float | None = None,
         axis: int = 0,
     ) -> Series[complex]: ...
-    def __mod__(self, other: num | ListLike | Series[S1]) -> Series[S1]: ...
+    def __mod__(self, other: float | ListLike | Series[S1]) -> Series[S1]: ...
     def __ne__(self, other: object) -> Series[_bool]: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
-    def __pow__(self, other: num | ListLike | Series[S1]) -> Series[S1]: ...
+    def __pow__(self, other: complex | ListLike | Series[S1]) -> Series[S1]: ...
     # ignore needed for mypy as we want different results based on the arguments
     @overload  # type: ignore[override]
     # pyrefly: ignore  # bad-override
@@ -2922,9 +2926,9 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
     ) -> Series[bool]: ...
     @overload
     def __rand__(self, other: int | np_ndarray_anyint | Series[int]) -> Series[int]: ...
-    def __rdivmod__(self, other: num | ListLike | Series[S1]) -> Series[S1]: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
-    def __rmod__(self, other: num | ListLike | Series[S1]) -> Series[S1]: ...
-    def __rpow__(self, other: num | ListLike | Series[S1]) -> Series[S1]: ...
+    def __rdivmod__(self, other: float | ListLike | Series[S1]) -> Series[S1]: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
+    def __rmod__(self, other: float | ListLike | Series[S1]) -> Series[S1]: ...
+    def __rpow__(self, other: complex | ListLike | Series[S1]) -> Series[S1]: ...
     # ignore needed for mypy as we want different results based on the arguments
     @overload  # type: ignore[override]
     # pyrefly: ignore  # bad-override
@@ -4156,7 +4160,7 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
     ) -> Series[S1]: ...
     def divmod(
         self,
-        other: num | ListLike | Series[S1],
+        other: float | ListLike | Series[S1],
         level: Level | None = ...,
         fill_value: float | None = None,
         axis: AxisIndex = ...,
@@ -4179,7 +4183,7 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
         adjust: _bool = True,
         ignore_na: _bool = False,
         axis: Axis = 0,
-        times: np.ndarray | Series | None = None,
+        times: npt.NDArray[Any] | Series | None = None,
         method: CalculationMethod = "single",
     ) -> ExponentialMovingWindow[Series]: ...
     @final
@@ -4314,7 +4318,7 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
     ) -> S1: ...
     def mod(
         self,
-        other: num | ListLike | Series[S1],
+        other: float | ListLike | Series[S1],
         level: Level | None = ...,
         fill_value: float | None = None,
         axis: AxisIndex | None = 0,
@@ -4330,7 +4334,7 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
     def nunique(self, dropna: _bool = True) -> int: ...
     def pow(
         self,
-        other: num | ListLike | Series[S1],
+        other: complex | ListLike | Series[S1],
         level: Level | None = ...,
         fill_value: float | None = None,
         axis: AxisIndex | None = 0,
diff --git a/pandas-stubs/core/tools/numeric.pyi b/pandas-stubs/core/tools/numeric.pyi
index 3e3d100ed..e130f880b 100644
--- a/pandas-stubs/core/tools/numeric.pyi
+++ b/pandas-stubs/core/tools/numeric.pyi
@@ -1,10 +1,13 @@
+from collections.abc import Sequence
 from typing import (
+    Any,
     Literal,
     TypeAlias,
     overload,
 )
 
 import numpy as np
+from numpy import typing as npt
 import pandas as pd
 
 from pandas._libs.lib import _NoDefaultDoNotUse
@@ -12,29 +15,37 @@ from pandas._typing import (
     DtypeBackend,
     RaiseCoerce,
     Scalar,
-    npt,
+    SequenceNotStr,
+    np_1darray,
 )
 
 _Downcast: TypeAlias = Literal["integer", "signed", "unsigned", "float"] | None
 
 @overload
-def to_numeric(
+def to_numeric(  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
     arg: Scalar,
-    errors: Literal["raise", "coerce"] = ...,
-    downcast: _Downcast = ...,
-    dtype_backend: DtypeBackend | _NoDefaultDoNotUse = ...,
+    errors: RaiseCoerce = "raise",
+    downcast: _Downcast = None,
+    dtype_backend: DtypeBackend | _NoDefaultDoNotUse = "numpy_nullable",
 ) -> float: ...
 @overload
 def to_numeric(
-    arg: list | tuple | np.ndarray,
-    errors: RaiseCoerce = ...,
-    downcast: _Downcast = ...,
-    dtype_backend: DtypeBackend | _NoDefaultDoNotUse = ...,
-) -> npt.NDArray: ...
+    arg: Sequence[int],
+    errors: RaiseCoerce = "raise",
+    downcast: _Downcast = None,
+    dtype_backend: DtypeBackend | _NoDefaultDoNotUse = "numpy_nullable",
+) -> np_1darray[np.integer]: ...
+@overload
+def to_numeric(
+    arg: SequenceNotStr[Any] | npt.NDArray[Any],
+    errors: RaiseCoerce = "raise",
+    downcast: _Downcast = None,
+    dtype_backend: DtypeBackend | _NoDefaultDoNotUse = "numpy_nullable",
+) -> np_1darray[np.floating]: ...
 @overload
 def to_numeric(
     arg: pd.Series,
-    errors: RaiseCoerce = ...,
-    downcast: _Downcast = ...,
-    dtype_backend: DtypeBackend | _NoDefaultDoNotUse = ...,
+    errors: RaiseCoerce = "raise",
+    downcast: _Downcast = None,
+    dtype_backend: DtypeBackend | _NoDefaultDoNotUse = "numpy_nullable",
 ) -> pd.Series: ...
diff --git a/pandas-stubs/core/util/hashing.pyi b/pandas-stubs/core/util/hashing.pyi
index fa59fc2ce..6bd077828 100644
--- a/pandas-stubs/core/util/hashing.pyi
+++ b/pandas-stubs/core/util/hashing.pyi
@@ -7,7 +7,7 @@ from pandas import (
 
 from pandas._typing import (
     ArrayLike,
-    npt,
+    np_1darray,
 )
 
 def hash_pandas_object(
@@ -22,4 +22,4 @@ def hash_array(
     encoding: str = "utf8",
     hash_key: str = "0123456789123456",
     categorize: bool = True,
-) -> npt.NDArray[np.uint64]: ...
+) -> np_1darray[np.uint64]: ...
diff --git a/pandas-stubs/io/formats/printing.pyi b/pandas-stubs/io/formats/printing.pyi
new file mode 100644
index 000000000..ccd0b3dfb
--- /dev/null
+++ b/pandas-stubs/io/formats/printing.pyi
@@ -0,0 +1,6 @@
+from typing import TypeVar
+
+_KT = TypeVar("_KT")
+_VT = TypeVar("_VT")
+
+class PrettyDict(dict[_KT, _VT]): ...
diff --git a/pandas-stubs/io/formats/style.pyi b/pandas-stubs/io/formats/style.pyi
index 8516c9075..aecf5c8cf 100644
--- a/pandas-stubs/io/formats/style.pyi
+++ b/pandas-stubs/io/formats/style.pyi
@@ -52,7 +52,7 @@ class _SeriesFunc(Protocol):
 class _DataFrameFunc(Protocol):
     def __call__(
         self, series: DataFrame, /, *args: Any, **kwargs: Any
-    ) -> npt.NDArray | DataFrame: ...
+    ) -> npt.NDArray[Any] | DataFrame: ...
 
 class _MapCallable(Protocol):
     def __call__(
@@ -238,7 +238,7 @@ class Styler(StylerRenderer):
     @overload
     def apply(
         self,
-        func: _DataFrameFunc | Callable[[DataFrame], npt.NDArray | DataFrame],
+        func: _DataFrameFunc | Callable[[DataFrame], npt.NDArray[Any] | DataFrame],
         axis: None,
         subset: Subset | None = ...,
         **kwargs: Any,
@@ -295,7 +295,7 @@ class Styler(StylerRenderer):
         gmap: (
             Sequence[float]
             | Sequence[Sequence[float]]
-            | npt.NDArray
+            | npt.NDArray[Any]
             | DataFrame
             | Series
             | None
@@ -313,7 +313,7 @@ class Styler(StylerRenderer):
         gmap: (
             Sequence[float]
             | Sequence[Sequence[float]]
-            | npt.NDArray
+            | npt.NDArray[Any]
             | DataFrame
             | Series
             | None
@@ -334,7 +334,7 @@ class Styler(StylerRenderer):
         align: (
             Literal["left", "right", "zero", "mid", "mean"]
             | float
-            | Callable[[Series | npt.NDArray | DataFrame], float]
+            | Callable[[Series | npt.NDArray[Any] | DataFrame], float]
         ) = "mid",
         vmin: float | None = None,
         vmax: float | None = None,
diff --git a/tests/series/test_series.py b/tests/series/test_series.py
index 73bc51bb5..a753fdca5 100644
--- a/tests/series/test_series.py
+++ b/tests/series/test_series.py
@@ -26,6 +26,7 @@
 )
 
 import numpy as np
+from numpy import typing as npt
 import pandas as pd
 from pandas.api.extensions import (
     ExtensionArray,
@@ -33,6 +34,7 @@
 )
 from pandas.api.typing import NAType
 from pandas.core.arrays.datetimes import DatetimeArray
+from pandas.core.arrays.string_ import StringArray
 from pandas.core.arrays.timedeltas import TimedeltaArray
 from pandas.core.window import ExponentialMovingWindow
 from pandas.core.window.expanding import Expanding
@@ -771,7 +773,7 @@ def test_types_value_counts() -> None:
 
 def test_types_unique() -> None:
     s = pd.Series([-10, 2, 2, 3, 10, 10])
-    check(assert_type(s.unique(), np.ndarray), np.ndarray)
+    check(assert_type(s.unique(), np_1darray[Any]), np_1darray[Any])
 
 
 def test_types_apply() -> None:
@@ -1412,31 +1414,41 @@ def test_types_rename_axis() -> None:
 
 def test_types_values() -> None:
     check(
-        assert_type(pd.Series([1, 2, 3]).values, ExtensionArray | np.ndarray),
-        np.ndarray,
+        assert_type(
+            pd.Series([1, 2, 3]).values,
+            np_1darray[Any] | ExtensionArray | pd.Categorical,
+        ),
+        np_1darray,
+        np.integer,
     )
-    valresult_type: type[np.ndarray | ExtensionArray]
+    valresult_type: type[np_1darray[Any] | ExtensionArray | pd.Categorical]
     if PD_LTE_23:
-        valresult_type = np.ndarray
+        valresult_type = np_1darray[Any]
     else:
-        valresult_type = ExtensionArray
+        valresult_type = StringArray
     check(
-        assert_type(pd.Series(list("aabc")).values, np.ndarray | ExtensionArray),
+        assert_type(
+            pd.Series(list("aabc")).values,
+            np_1darray[Any] | ExtensionArray | pd.Categorical,
+        ),
         valresult_type,
+        str,
     )
     check(
         assert_type(
             pd.Series(list("aabc")).astype("category").values,
-            np.ndarray | ExtensionArray,
+            np_1darray[Any] | ExtensionArray | pd.Categorical,
         ),
         pd.Categorical,
+        str,
     )
     check(
         assert_type(
             pd.Series(pd.date_range("20130101", periods=3, tz="US/Eastern")).values,
-            np.ndarray | ExtensionArray,
+            np_1darray[Any] | ExtensionArray | pd.Categorical,
         ),
-        np.ndarray,
+        np_1darray,
+        np.datetime64,
     )
 
 
@@ -1572,8 +1584,8 @@ def test_types_dot() -> None:
     check(assert_type(s1 @ s2, Scalar), np.int64)
     check(assert_type(s1.dot(df1), "pd.Series[int]"), pd.Series, np.int64)
     check(assert_type(s1 @ df1, pd.Series), pd.Series)
-    check(assert_type(s1.dot(n1), np.ndarray), np.ndarray)
-    check(assert_type(s1 @ n1, np.ndarray), np.ndarray)
+    check(assert_type(s1.dot(n1), npt.NDArray[Any]), npt.NDArray[Any])
+    check(assert_type(s1 @ n1, npt.NDArray[Any]), npt.NDArray[Any])
 
 
 def test_series_loc_setitem() -> None:
diff --git a/tests/test_frame.py b/tests/test_frame.py
index 560beff1f..39d73671a 100644
--- a/tests/test_frame.py
+++ b/tests/test_frame.py
@@ -54,6 +54,7 @@
     TYPE_CHECKING_INVALID_USAGE,
     check,
     ensure_clean,
+    np_1darray,
     np_2darray,
     pytest_warns_bounded,
 )
@@ -626,7 +627,8 @@ def test_types_eval() -> None:
     check(assert_type(df.eval("C = col1 % col2 == 0", inplace=True), None), type(None))
     check(
         assert_type(
-            df.eval("E = col1 > col2"), Scalar | np.ndarray | pd.DataFrame | pd.Series
+            df.eval("E = col1 > col2"),
+            Scalar | npt.NDArray[Any] | pd.DataFrame | pd.Series,
         ),
         pd.DataFrame,
     )
@@ -1082,7 +1084,7 @@ def test_types_value_counts() -> None:
 def test_types_unique() -> None:
     # This is really more for of a Series test
     df = pd.DataFrame(data={"col1": [1, 2], "col2": [1, 4]})
-    check(assert_type(df["col1"].unique(), np.ndarray), np.ndarray)
+    check(assert_type(df["col1"].unique(), np_1darray[Any]), np_1darray[Any])
 
 
 def test_types_apply() -> None:
diff --git a/tests/test_pandas.py b/tests/test_pandas.py
index af442375b..c3e04ccd6 100644
--- a/tests/test_pandas.py
+++ b/tests/test_pandas.py
@@ -9,14 +9,14 @@
 )
 
 import numpy as np
-import numpy.typing as npt
+from numpy import typing as npt
 import pandas as pd
-from pandas import Grouper
 from pandas.api.extensions import ExtensionArray
 from pandas.api.typing import (
     NaTType,
     NAType,
 )
+from pandas.core.groupby.grouper import Grouper
 import pandas.util as pdutil
 
 # TODO: pandas-dev/pandas#55023
@@ -558,21 +558,26 @@ def test_read_xml() -> None:
 def test_unique() -> None:
     # Taken from the docs
     check(
-        assert_type(pd.unique(pd.Series([2, 1, 3, 3])), np.ndarray | ExtensionArray),
-        np.ndarray,
+        assert_type(
+            pd.unique(pd.Series([2, 1, 3, 3])), np_1darray[Any] | ExtensionArray
+        ),
+        np_1darray[np.int64],
     )
 
     check(
-        assert_type(pd.unique(pd.Series([2] + [1] * 5)), np.ndarray | ExtensionArray),
-        np.ndarray,
+        assert_type(
+            pd.unique(pd.Series([2] + [1] * 5)), np_1darray[Any] | ExtensionArray
+        ),
+        np_1darray[np.int64],
     )
 
     check(
         assert_type(
             pd.unique(pd.Series([pd.Timestamp("20160101"), pd.Timestamp("20160101")])),
-            np.ndarray | ExtensionArray,
+            np_1darray[Any] | ExtensionArray,
         ),
-        np.ndarray,
+        np_1darray,
+        np.datetime64,
     )
 
     check(
@@ -585,7 +590,7 @@ def test_unique() -> None:
                     ]
                 )
             ),
-            np.ndarray | ExtensionArray,
+            np_1darray[Any] | ExtensionArray,
         ),
         pd.arrays.DatetimeArray,
     )
@@ -599,24 +604,27 @@ def test_unique() -> None:
                     ]
                 )
             ),
-            np.ndarray,
+            np_1darray[np.datetime64] | pd.DatetimeIndex,
         ),
         pd.DatetimeIndex,
     )
 
-    check(assert_type(pd.unique(np.array(list("baabc"))), np.ndarray), np.ndarray)
+    check(
+        assert_type(pd.unique(np.array(list("baabc"))), np_1darray[Any]),
+        np_1darray[Any],
+    )
 
     check(
         assert_type(
             pd.unique(pd.Series(pd.Categorical(list("baabc")))),
-            np.ndarray | ExtensionArray,
+            np_1darray[Any] | ExtensionArray,
         ),
         pd.Categorical,
     )
     check(
         assert_type(
             pd.unique(pd.Series(pd.Categorical(list("baabc"), categories=list("abc")))),
-            np.ndarray | ExtensionArray,
+            np_1darray[Any] | ExtensionArray,
         ),
         pd.Categorical,
     )
@@ -627,16 +635,18 @@ def test_unique() -> None:
                     pd.Categorical(list("baabc"), categories=list("abc"), ordered=True)
                 )
             ),
-            np.ndarray | ExtensionArray,
+            np_1darray[Any] | ExtensionArray,
         ),
         pd.Categorical,
     )
     check(
-        assert_type(pd.unique(pd.Index(["a", "b", "c", "a"])), np.ndarray),
+        assert_type(
+            pd.unique(pd.Index(["a", "b", "c", "a"])), np_1darray[Any] | pd.Index
+        ),
         np.ndarray if PD_LTE_23 else pd.Index,
     )
     check(
-        assert_type(pd.unique(pd.RangeIndex(0, 10)), np.ndarray),
+        assert_type(pd.unique(pd.RangeIndex(0, 10)), np_1darray[Any] | pd.Index),
         np.ndarray if PD_LTE_23 else pd.Index,
     )
     check(
@@ -653,7 +663,7 @@ def test_unique() -> None:
     check(
         assert_type(
             pd.unique(pd.timedelta_range(start="1 day", periods=4)),
-            np.ndarray,
+            np_1darray[Any] | pd.Index,
         ),
         np.ndarray if PD_LTE_23 else pd.Index,
     )
@@ -692,13 +702,15 @@ def test_arrow_dtype() -> None:
 
 def test_hashing() -> None:
     a = np.array([1, 2, 3])
-    check(assert_type(pdutil.hash_array(a), npt.NDArray[np.uint64]), np.ndarray)
+    check(
+        assert_type(pdutil.hash_array(a), np_1darray[np.uint64]), np_1darray[np.uint64]
+    )
     check(
         assert_type(
             pdutil.hash_array(a, encoding="latin1", hash_key="1", categorize=True),
-            npt.NDArray[np.uint64],
+            np_1darray[np.uint64],
         ),
-        np.ndarray,
+        np_1darray[np.uint64],
     )
 
     b = pd.Series(a)
@@ -723,7 +735,7 @@ def test_eval() -> None:
     check(
         assert_type(
             pd.eval("double_age = df.age * 2", target=df),
-            npt.NDArray | Scalar | pd.DataFrame | pd.Series | None,
+            npt.NDArray[Any] | Scalar | pd.DataFrame | pd.Series | None,
         ),
         pd.DataFrame,
     )
@@ -741,50 +753,46 @@ def test_to_numeric_scalar() -> None:
 
 def test_to_numeric_array_like() -> None:
     check(
-        assert_type(
-            pd.to_numeric([1, 2, 3]),
-            npt.NDArray,
-        ),
-        np.ndarray,
+        assert_type(pd.to_numeric([1, 2, 3]), np_1darray[np.integer]),
+        np_1darray,
+        np.integer,
     )
     check(
-        assert_type(
-            pd.to_numeric([1.0, 2.0, 3.0]),
-            npt.NDArray,
-        ),
-        np.ndarray,
+        assert_type(pd.to_numeric([1.0, 2.0, 3.0]), np_1darray[np.floating]),
+        np_1darray,
+        np.floating,
     )
     check(
-        assert_type(
-            pd.to_numeric([1.0, 2.0, "3.0"]),
-            npt.NDArray,
-        ),
-        np.ndarray,
+        assert_type(pd.to_numeric([1.0, 2.0, "3.0"]), np_1darray[np.floating]),
+        np_1darray,
+        np.floating,
     )
     check(
         assert_type(
             pd.to_numeric(np.array([1.0, 2.0, "3.0"], dtype=object)),
-            npt.NDArray,
+            np_1darray[np.floating],
         ),
-        np.ndarray,
+        np_1darray,
+        np.floating,
     )
     check(
         assert_type(
-            pd.to_numeric([1.0, 2.0, "blerg"], errors="coerce"),
-            npt.NDArray,
+            pd.to_numeric([1.0, 2.0, "blerg"], errors="coerce"), np_1darray[np.floating]
         ),
-        np.ndarray,
+        np_1darray,
+        np.floating,
     )
     check(
-        assert_type(
-            pd.to_numeric((1.0, 2.0, 3.0)),
-            npt.NDArray,
-        ),
-        np.ndarray,
+        assert_type(pd.to_numeric((1.0, 2.0, 3.0)), np_1darray[np.floating]),
+        np_1darray,
+        np.floating,
     )
     check(
-        assert_type(pd.to_numeric([1, 2, 3], downcast="unsigned"), npt.NDArray),
-        np.ndarray,
+        assert_type(
+            pd.to_numeric([1, 2, 3], downcast="unsigned"), np_1darray[np.integer]
+        ),
+        np_1darray,
+        np.integer,
     )
 
 
@@ -931,34 +939,34 @@ def test_lreshape() -> None:
 
 def test_factorize() -> None:
     codes, uniques = pd.factorize(np.array(["b", "b", "a", "c", "b"]))
-    check(assert_type(codes, np.ndarray), np.ndarray)
-    check(assert_type(uniques, np.ndarray), np.ndarray)
+    check(assert_type(codes, np_1darray[np.int64]), np_1darray[np.int64])
+    check(assert_type(uniques, np_1darray[Any]), np_1darray[Any])
 
     codes, uniques = pd.factorize(np.recarray((1,), dtype=[("x", int)]))
-    check(assert_type(codes, np.ndarray), np.ndarray)
-    check(assert_type(uniques, np.ndarray), np.ndarray)
+    check(assert_type(codes, np_1darray[np.int64]), np_1darray[np.int64])
+    check(assert_type(uniques, np_1darray[Any]), np_1darray[Any])
 
     codes, cat_uniques = pd.factorize(pd.Categorical(["b", "b", "a", "c", "b"]))
-    check(assert_type(codes, np_1darray), np_1darray)
+    check(assert_type(codes, np_1darray[np.int64]), np_1darray[np.int64])
     check(assert_type(cat_uniques, pd.Categorical), pd.Categorical)
 
     codes, idx_uniques = pd.factorize(pd.Index(["b", "b", "a", "c", "b"]))
-    check(assert_type(codes, np_1darray), np_1darray)
+    check(assert_type(codes, np_1darray[np.int64]), np_1darray[np.int64])
     check(assert_type(idx_uniques, pd.Index), pd.Index)
 
     codes, idx_uniques = pd.factorize(pd.Series(["b", "b", "a", "c", "b"]))
-    check(assert_type(codes, np_1darray), np_1darray)
+    check(assert_type(codes, np_1darray[np.int64]), np_1darray[np.int64])
     check(assert_type(idx_uniques, pd.Index), pd.Index)
 
     codes, uniques = pd.factorize(np.array(list("bbacb")))
-    check(assert_type(codes, np.ndarray), np.ndarray)
-    check(assert_type(uniques, np.ndarray), np.ndarray)
+    check(assert_type(codes, np_1darray[np.int64]), np_1darray[np.int64])
+    check(assert_type(uniques, np_1darray[Any]), np_1darray[Any])
 
     codes, uniques = pd.factorize(
         np.array(["b", "b", "a", "c", "b"]), use_na_sentinel=True, size_hint=10
     )
-    check(assert_type(codes, np.ndarray), np.ndarray)
-    check(assert_type(uniques, np.ndarray), np.ndarray)
+    check(assert_type(codes, np_1darray[np.int64]), np_1darray[np.int64])
+    check(assert_type(uniques, np_1darray[Any]), np_1darray[Any])
 
 
 def test_index_unqiue() -> None:
@@ -976,18 +984,31 @@ def test_index_unqiue() -> None:
 
     check(assert_type(pd.unique(ci), pd.CategoricalIndex), pd.CategoricalIndex)
     check(
-        assert_type(pd.unique(dti), np.ndarray), np.ndarray if PD_LTE_23 else pd.Index
+        assert_type(pd.unique(dti), np_1darray[np.datetime64] | pd.DatetimeIndex),
+        np_1darray if PD_LTE_23 else pd.DatetimeIndex,
+        np.datetime64,
+    )
+    check(
+        assert_type(pd.unique(i), np_1darray[Any] | pd.Index),
+        np_1darray[Any] if PD_LTE_23 else pd.Index,
     )
-    check(assert_type(pd.unique(i), np.ndarray), np.ndarray if PD_LTE_23 else pd.Index)
     check(assert_type(pd.unique(pi), pd.PeriodIndex), pd.PeriodIndex)
-    check(assert_type(pd.unique(ri), np.ndarray), np.ndarray if PD_LTE_23 else pd.Index)
     check(
-        assert_type(pd.unique(tdi), np.ndarray), np.ndarray if PD_LTE_23 else pd.Index
+        assert_type(pd.unique(ri), np_1darray[Any] | pd.Index),
+        np_1darray[Any] if PD_LTE_23 else pd.Index,
+    )
+    check(
+        assert_type(pd.unique(tdi), np_1darray[Any] | pd.Index),
+        np_1darray[Any] if PD_LTE_23 else pd.Index,
+    )
+    check(
+        assert_type(pd.unique(mi), np_1darray[Any] | pd.Index),
+        np_1darray[Any] if PD_LTE_23 else pd.Index,
     )
-    check(assert_type(pd.unique(mi), np.ndarray), np.ndarray if PD_LTE_23 else pd.Index)
     check(
         assert_type(pd.unique(interval_i), "pd.IntervalIndex[pd.Interval[int]]"),
         pd.IntervalIndex,
+        pd.Interval,
     )
 
 
@@ -997,7 +1018,10 @@ def test_cut() -> None:
     b = pd.cut([1, 2, 3, 4, 5, 6, 7, 8], 4, labels=False, duplicates="raise")
     c = pd.cut([1, 2, 3, 4, 5, 6, 7, 8], 4, labels=["1", "2", "3", "4"])
     check(assert_type(a, pd.Categorical), pd.Categorical)
-    check(assert_type(b, npt.NDArray[np.intp]), np.ndarray)
+    check(
+        assert_type(b, np_1darray[np.intp]),
+        np_1darray[np.intp],
+    )
     check(assert_type(c, pd.Categorical), pd.Categorical)
 
     d0, d1 = pd.cut([1, 2, 3, 4, 5, 6, 7, 8], 4, retbins=True)
@@ -1006,11 +1030,14 @@ def test_cut() -> None:
         [1, 2, 3, 4, 5, 6, 7, 8], 4, labels=["1", "2", "3", "4"], retbins=True
     )
     check(assert_type(d0, pd.Categorical), pd.Categorical)
-    check(assert_type(d1, npt.NDArray), np.ndarray)
-    check(assert_type(e0, npt.NDArray[np.intp]), np.ndarray)
-    check(assert_type(e1, npt.NDArray), np.ndarray)
+    check(assert_type(d1, np_1darray[np.double]), np_1darray[np.double])
+    check(
+        assert_type(e0, np_1darray[np.intp]),
+        np_1darray[np.intp],
+    )
+    check(assert_type(e1, np_1darray[np.double]), np_1darray[np.double])
     check(assert_type(f0, pd.Categorical), pd.Categorical)
-    check(assert_type(f1, npt.NDArray), np.ndarray)
+    check(assert_type(f1, np_1darray[np.double]), np_1darray[np.double])
 
     g = pd.cut(pd.Series([1, 2, 3, 4, 5, 6, 7, 8]), 4, precision=1, duplicates="drop")
     h = pd.cut(pd.Series([1, 2, 3, 4, 5, 6, 7, 8]), 4, labels=False, duplicates="raise")
@@ -1045,11 +1072,11 @@ def test_cut() -> None:
         retbins=True,
     )
     check(assert_type(j0, pd.Series), pd.Series)
-    check(assert_type(j1, npt.NDArray), np.ndarray)
+    check(assert_type(j1, np_1darray[np.double]), np_1darray[np.double])
     check(assert_type(k0, pd.Series), pd.Series)
-    check(assert_type(k1, npt.NDArray), np.ndarray)
+    check(assert_type(k1, np_1darray[np.double]), np_1darray[np.double])
     check(assert_type(l0, pd.Series), pd.Series)
-    check(assert_type(l1, npt.NDArray), np.ndarray)
+    check(assert_type(l1, np_1darray[np.double]), np_1darray[np.double])
     check(assert_type(m0, pd.Series), pd.Series)
     check(assert_type(m1, pd.IntervalIndex), pd.IntervalIndex)
 
@@ -1122,10 +1149,10 @@ def test_qcut() -> None:
     check(assert_type(c0, pd.Categorical), pd.Categorical)
     check(assert_type(d0, pd.Series), pd.Series)
 
-    check(assert_type(a1, npt.NDArray[np.double]), np.ndarray)
-    check(assert_type(b1, npt.NDArray[np.double]), np.ndarray)
-    check(assert_type(c1, npt.NDArray[np.double]), np.ndarray)
-    check(assert_type(d1, npt.NDArray[np.double]), np.ndarray)
+    check(assert_type(a1, np_1darray[np.double]), np_1darray[np.double])
+    check(assert_type(b1, np_1darray[np.double]), np_1darray[np.double])
+    check(assert_type(c1, np_1darray[np.double]), np_1darray[np.double])
+    check(assert_type(d1, np_1darray[np.double]), np_1darray[np.double])
 
     e0, e1 = pd.qcut(val_list, [0.25, 0.5, 0.75], retbins=True)
     f0, f1 = pd.qcut(val_arr, np.array([0.25, 0.5, 0.75]), retbins=True)
@@ -1136,17 +1163,23 @@ def test_qcut() -> None:
 
     check(assert_type(e0, pd.Categorical), pd.Categorical)
     check(assert_type(f0, pd.Categorical), pd.Categorical)
-    check(assert_type(g0, npt.NDArray[np.intp]), np.ndarray)
+    check(
+        assert_type(g0, np_1darray[np.intp | np.double]),
+        np_1darray[np.intp],
+    )
     check(assert_type(h0, pd.Series), pd.Series)
-    check(assert_type(i0, npt.NDArray[np.intp]), np.ndarray)
-    check(assert_type(j0, npt.NDArray[np.intp]), np.ndarray)
-
-    check(assert_type(e1, npt.NDArray[np.double]), np.ndarray)
-    check(assert_type(f1, npt.NDArray[np.double]), np.ndarray)
-    check(assert_type(g1, npt.NDArray[np.double]), np.ndarray)
-    check(assert_type(h1, npt.NDArray[np.double]), np.ndarray)
-    check(assert_type(i1, npt.NDArray[np.double]), np.ndarray)
-    check(assert_type(j1, npt.NDArray[np.double]), np.ndarray)
+    check(
+        assert_type(i0, np_1darray[np.intp | np.double]),
+        np_1darray[np.double],  # because of nans
+    )
+    check(assert_type(j0, np_1darray[np.intp | np.double]), np_1darray[np.double])
+
+    check(assert_type(e1, np_1darray[np.double]), np_1darray[np.double])
+    check(assert_type(f1, np_1darray[np.double]), np_1darray[np.double])
+    check(assert_type(g1, np_1darray[np.double]), np_1darray[np.double])
+    check(assert_type(h1, np_1darray[np.double]), np_1darray[np.double])
+    check(assert_type(i1, np_1darray[np.double]), np_1darray[np.double])
+    check(assert_type(j1, np_1darray[np.double]), np_1darray[np.double])
 
 
 @pytest.mark.xfail(