diff --git a/pandas-stubs/_libs/interval.pyi b/pandas-stubs/_libs/interval.pyi
index fdb0a398c..f22a12778 100644
--- a/pandas-stubs/_libs/interval.pyi
+++ b/pandas-stubs/_libs/interval.pyi
@@ -21,7 +21,7 @@ from pandas.core.series import (
 from pandas._typing import (
     IntervalClosedType,
     IntervalT,
-    np_ndarray_bool,
+    np_1darray,
     npt,
 )
 
@@ -170,7 +170,9 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
     @overload
     def __gt__(self, other: Interval[_OrderableT]) -> bool: ...
     @overload
-    def __gt__(self: IntervalT, other: IntervalIndex[IntervalT]) -> np_ndarray_bool: ...
+    def __gt__(
+        self: IntervalT, other: IntervalIndex[IntervalT]
+    ) -> np_1darray[np.bool]: ...
     @overload
     def __gt__(
         self,
@@ -179,7 +181,9 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
     @overload
     def __lt__(self, other: Interval[_OrderableT]) -> bool: ...
     @overload
-    def __lt__(self: IntervalT, other: IntervalIndex[IntervalT]) -> np_ndarray_bool: ...
+    def __lt__(
+        self: IntervalT, other: IntervalIndex[IntervalT]
+    ) -> np_1darray[np.bool]: ...
     @overload
     def __lt__(
         self,
@@ -188,7 +192,9 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
     @overload
     def __ge__(self, other: Interval[_OrderableT]) -> bool: ...
     @overload
-    def __ge__(self: IntervalT, other: IntervalIndex[IntervalT]) -> np_ndarray_bool: ...
+    def __ge__(
+        self: IntervalT, other: IntervalIndex[IntervalT]
+    ) -> np_1darray[np.bool]: ...
     @overload
     def __ge__(
         self,
@@ -197,11 +203,15 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
     @overload
     def __le__(self, other: Interval[_OrderableT]) -> bool: ...
     @overload
-    def __le__(self: IntervalT, other: IntervalIndex[IntervalT]) -> np_ndarray_bool: ...
+    def __le__(
+        self: IntervalT, other: IntervalIndex[IntervalT]
+    ) -> np_1darray[np.bool]: ...
     @overload
     def __eq__(self, other: Interval[_OrderableT]) -> bool: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
     @overload
-    def __eq__(self: IntervalT, other: IntervalIndex[IntervalT]) -> np_ndarray_bool: ...
+    def __eq__(
+        self: IntervalT, other: IntervalIndex[IntervalT]
+    ) -> np_1darray[np.bool]: ...
     @overload
     def __eq__(self, other: Series[_OrderableT]) -> Series[bool]: ...  # type: ignore[overload-overlap]
     @overload
@@ -209,7 +219,9 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
     @overload
     def __ne__(self, other: Interval[_OrderableT]) -> bool: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
     @overload
-    def __ne__(self: IntervalT, other: IntervalIndex[IntervalT]) -> np_ndarray_bool: ...
+    def __ne__(
+        self: IntervalT, other: IntervalIndex[IntervalT]
+    ) -> np_1darray[np.bool]: ...
     @overload
     def __ne__(self, other: Series[_OrderableT]) -> Series[bool]: ...  # type: ignore[overload-overlap]
     @overload
diff --git a/pandas-stubs/_libs/tslibs/timestamps.pyi b/pandas-stubs/_libs/tslibs/timestamps.pyi
index 11302a12c..e97ceb449 100644
--- a/pandas-stubs/_libs/tslibs/timestamps.pyi
+++ b/pandas-stubs/_libs/tslibs/timestamps.pyi
@@ -40,9 +40,11 @@ from pandas._libs.tslibs import (
     Timedelta,
 )
 from pandas._typing import (
+    ShapeT,
     TimestampNonexistent,
     TimeUnit,
-    np_ndarray_bool,
+    np_1darray,
+    np_ndarray,
     npt,
 )
 
@@ -180,40 +182,48 @@ class Timestamp(datetime, SupportsIndex):
     @overload  # type: ignore[override]
     def __le__(self, other: Timestamp | datetime | np.datetime64) -> bool: ...  # type: ignore[misc]
     @overload
+    def __le__(self, other: DatetimeIndex) -> np_1darray[np.bool]: ...
+    @overload
     def __le__(
-        self, other: DatetimeIndex | npt.NDArray[np.datetime64]
-    ) -> np_ndarray_bool: ...
+        self, other: np_ndarray[ShapeT, np.datetime64]
+    ) -> np_ndarray[ShapeT, np.bool]: ...
     @overload
     def __le__(self, other: TimestampSeries) -> Series[bool]: ...
     @overload  # type: ignore[override]
     def __lt__(self, other: Timestamp | datetime | np.datetime64) -> bool: ...  # type: ignore[misc]
     @overload
+    def __lt__(self, other: DatetimeIndex) -> np_1darray[np.bool]: ...
+    @overload
     def __lt__(
-        self, other: DatetimeIndex | npt.NDArray[np.datetime64]
-    ) -> np_ndarray_bool: ...
+        self, other: np_ndarray[ShapeT, np.datetime64]
+    ) -> np_ndarray[ShapeT, np.bool]: ...
     @overload
     def __lt__(self, other: TimestampSeries) -> Series[bool]: ...
     @overload  # type: ignore[override]
     def __ge__(self, other: Timestamp | datetime | np.datetime64) -> bool: ...  # type: ignore[misc]
     @overload
+    def __ge__(self, other: DatetimeIndex) -> np_1darray[np.bool]: ...
+    @overload
     def __ge__(
-        self, other: DatetimeIndex | npt.NDArray[np.datetime64]
-    ) -> np_ndarray_bool: ...
+        self, other: np_ndarray[ShapeT, np.datetime64]
+    ) -> np_ndarray[ShapeT, np.bool]: ...
     @overload
     def __ge__(self, other: TimestampSeries) -> Series[bool]: ...
     @overload  # type: ignore[override]
     def __gt__(self, other: Timestamp | datetime | np.datetime64) -> bool: ...  # type: ignore[misc]
     @overload
+    def __gt__(self, other: DatetimeIndex) -> np_1darray[np.bool]: ...
+    @overload
     def __gt__(
-        self, other: DatetimeIndex | npt.NDArray[np.datetime64]
-    ) -> np_ndarray_bool: ...
+        self, other: np_ndarray[ShapeT, np.datetime64]
+    ) -> np_ndarray[ShapeT, np.bool]: ...
     @overload
     def __gt__(self, other: TimestampSeries) -> Series[bool]: ...
     # error: Signature of "__add__" incompatible with supertype "date"/"datetime"
     @overload  # type: ignore[override]
     def __add__(
-        self, other: npt.NDArray[np.timedelta64]
-    ) -> npt.NDArray[np.datetime64]: ...
+        self, other: np_ndarray[ShapeT, np.timedelta64]
+    ) -> np_ndarray[ShapeT, np.datetime64]: ...
     @overload
     def __add__(self, other: timedelta | np.timedelta64 | Tick) -> Self: ...
     @overload
@@ -226,8 +236,8 @@ class Timestamp(datetime, SupportsIndex):
     def __radd__(self, other: TimedeltaIndex) -> DatetimeIndex: ...
     @overload
     def __radd__(
-        self, other: npt.NDArray[np.timedelta64]
-    ) -> npt.NDArray[np.datetime64]: ...
+        self, other: np_ndarray[ShapeT, np.timedelta64]
+    ) -> np_ndarray[ShapeT, np.datetime64]: ...
     # TODO: test dt64
     @overload  # type: ignore[override]
     def __sub__(self, other: Timestamp | datetime | np.datetime64) -> Timedelta: ...
@@ -241,14 +251,16 @@ class Timestamp(datetime, SupportsIndex):
     def __sub__(self, other: TimestampSeries) -> TimedeltaSeries: ...
     @overload
     def __sub__(
-        self, other: npt.NDArray[np.timedelta64]
-    ) -> npt.NDArray[np.datetime64]: ...
+        self, other: np_ndarray[ShapeT, np.timedelta64]
+    ) -> np_ndarray[ShapeT, np.datetime64]: ...
     @overload
     def __eq__(self, other: Timestamp | datetime | np.datetime64) -> bool: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
     @overload
     def __eq__(self, other: TimestampSeries) -> Series[bool]: ...  # type: ignore[overload-overlap]
     @overload
-    def __eq__(self, other: npt.NDArray[np.datetime64] | Index) -> np_ndarray_bool: ...  # type: ignore[overload-overlap]
+    def __eq__(self, other: Index) -> np_1darray[np.bool]: ...  # type: ignore[overload-overlap]
+    @overload  # TODO: using shape-aware arrays similar to other methods doesn't work in mypy
+    def __eq__(self, other: npt.NDArray[np.datetime64]) -> np_1darray[np.bool]: ...  # type: ignore[overload-overlap]
     @overload
     def __eq__(self, other: object) -> Literal[False]: ...
     @overload
@@ -256,7 +268,9 @@ class Timestamp(datetime, SupportsIndex):
     @overload
     def __ne__(self, other: TimestampSeries) -> Series[bool]: ...  # type: ignore[overload-overlap]
     @overload
-    def __ne__(self, other: npt.NDArray[np.datetime64] | Index) -> np_ndarray_bool: ...  # type: ignore[overload-overlap]
+    def __ne__(self, other: Index) -> np_1darray[np.bool]: ...  # type: ignore[overload-overlap]
+    @overload  # TODO: using shape-aware arrays similar to other methods doesn't work in mypy
+    def __ne__(self, other: npt.NDArray[np.datetime64]) -> np_1darray[np.bool]: ...  # type: ignore[overload-overlap]
     @overload
     def __ne__(self, other: object) -> Literal[True]: ...
     def __hash__(self) -> int: ...
diff --git a/pandas-stubs/_typing.pyi b/pandas-stubs/_typing.pyi
index f14c393fe..16eedcd4c 100644
--- a/pandas-stubs/_typing.pyi
+++ b/pandas-stubs/_typing.pyi
@@ -819,6 +819,15 @@ np_ndarray_complex: TypeAlias = npt.NDArray[np.complexfloating]
 np_ndarray_bool: TypeAlias = npt.NDArray[np.bool_]
 np_ndarray_str: TypeAlias = npt.NDArray[np.str_]
 
+# Define shape and generic type variables with defaults similar to numpy
+GenericT = TypeVar("GenericT", bound=np.generic, default=Any)
+ShapeT = TypeVar("ShapeT", bound=tuple[int, ...], default=tuple[Any, ...])
+# Numpy ndarray with more ergonomic typevar
+np_ndarray: TypeAlias = np.ndarray[ShapeT, np.dtype[GenericT]]
+# Numpy arrays with known shape (Do not use as argument types, only as return types)
+np_1darray: TypeAlias = np.ndarray[tuple[int], np.dtype[GenericT]]
+np_2darray: TypeAlias = np.ndarray[tuple[int, int], np.dtype[GenericT]]
+
 IndexType: TypeAlias = slice | np_ndarray_anyint | Index | list[int] | Series[int]
 MaskType: TypeAlias = Series[bool] | np_ndarray_bool | list[bool]
 
diff --git a/pandas-stubs/core/algorithms.pyi b/pandas-stubs/core/algorithms.pyi
index 803878ba8..a89c4d829 100644
--- a/pandas-stubs/core/algorithms.pyi
+++ b/pandas-stubs/core/algorithms.pyi
@@ -18,6 +18,7 @@ from pandas._typing import (
     AnyArrayLike,
     IntervalT,
     TakeIndexer,
+    np_1darray,
 )
 
 # These are type: ignored because the Index types overlap due to inheritance but indices
@@ -54,14 +55,14 @@ def factorize(
     sort: bool = ...,
     use_na_sentinel: bool = ...,
     size_hint: int | None = ...,
-) -> tuple[np.ndarray, Index]: ...
+) -> tuple[np_1darray, Index]: ...
 @overload
 def factorize(
     values: Categorical,
     sort: bool = ...,
     use_na_sentinel: bool = ...,
     size_hint: int | None = ...,
-) -> tuple[np.ndarray, Categorical]: ...
+) -> tuple[np_1darray, Categorical]: ...
 def value_counts(
     values: AnyArrayLike | list | tuple,
     sort: bool = True,
diff --git a/pandas-stubs/core/arrays/base.pyi b/pandas-stubs/core/arrays/base.pyi
index b5c0ef7cc..b59ef8639 100644
--- a/pandas-stubs/core/arrays/base.pyi
+++ b/pandas-stubs/core/arrays/base.pyi
@@ -12,6 +12,7 @@ from pandas._typing import (
     ScalarIndexer,
     SequenceIndexer,
     TakeIndexer,
+    np_1darray,
     npt,
 )
 
@@ -31,7 +32,7 @@ class ExtensionArray:
         dtype: npt.DTypeLike | None = ...,
         copy: bool = False,
         na_value: Scalar = ...,
-    ) -> np.ndarray: ...
+    ) -> np_1darray: ...
     @property
     def dtype(self) -> ExtensionDtype: ...
     @property
@@ -44,13 +45,13 @@ class ExtensionArray:
     def isna(self) -> ArrayLike: ...
     def argsort(
         self, *, ascending: bool = ..., kind: str = ..., **kwargs
-    ) -> np.ndarray: ...
+    ) -> np_1darray: ...
     def fillna(self, value=..., method=None, limit=None): ...
     def dropna(self): ...
     def shift(self, periods: int = 1, fill_value: object = ...) -> Self: ...
     def unique(self): ...
     def searchsorted(self, value, side: str = ..., sorter=...): ...
-    def factorize(self, use_na_sentinel: bool = True) -> tuple[np.ndarray, Self]: ...
+    def factorize(self, use_na_sentinel: bool = True) -> tuple[np_1darray, Self]: ...
     def repeat(self, repeats, axis=...): ...
     def take(
         self,
@@ -60,7 +61,7 @@ class ExtensionArray:
         fill_value=...,
     ) -> Self: ...
     def copy(self) -> Self: ...
-    def view(self, dtype=...) -> Self | np.ndarray: ...
+    def view(self, dtype=...) -> Self | np_1darray: ...
     def ravel(self, order="C") -> Self: ...
     def tolist(self) -> list: ...
     def _reduce(
diff --git a/pandas-stubs/core/arrays/categorical.pyi b/pandas-stubs/core/arrays/categorical.pyi
index 57f075e21..a0ef49f7b 100644
--- a/pandas-stubs/core/arrays/categorical.pyi
+++ b/pandas-stubs/core/arrays/categorical.pyi
@@ -25,8 +25,7 @@ from pandas._typing import (
     ScalarIndexer,
     SequenceIndexer,
     TakeIndexer,
-    np_ndarray_bool,
-    np_ndarray_int,
+    np_1darray,
 )
 
 from pandas.core.dtypes.dtypes import CategoricalDtype as CategoricalDtype
@@ -63,7 +62,7 @@ class Categorical(ExtensionArray):
         fastpath: bool = ...,
     ) -> Categorical: ...
     @property
-    def codes(self) -> np_ndarray_int: ...
+    def codes(self) -> np_1darray[np.signedinteger]: ...
     def set_ordered(self, value) -> Categorical: ...
     def as_ordered(self) -> Categorical: ...
     def as_unordered(self) -> Categorical: ...
@@ -90,7 +89,7 @@ class Categorical(ExtensionArray):
     @property
     def shape(self): ...
     def shift(self, periods=1, fill_value=...): ...
-    def __array__(self, dtype=...) -> np.ndarray: ...
+    def __array__(self, dtype=...) -> np_1darray: ...
     def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): ...
     @property
     def T(self): ...
@@ -98,10 +97,10 @@ class Categorical(ExtensionArray):
     def nbytes(self) -> int: ...
     def memory_usage(self, deep: bool = ...): ...
     def searchsorted(self, value, side: str = ..., sorter=...): ...
-    def isna(self) -> np_ndarray_bool: ...
-    def isnull(self) -> np_ndarray_bool: ...
-    def notna(self) -> np_ndarray_bool: ...
-    def notnull(self) -> np_ndarray_bool: ...
+    def isna(self) -> np_1darray[np.bool]: ...
+    def isnull(self) -> np_1darray[np.bool]: ...
+    def notna(self) -> np_1darray[np.bool]: ...
+    def notnull(self) -> np_1darray[np.bool]: ...
     def dropna(self): ...
     def value_counts(self, dropna: bool = True): ...
     def check_for_ordered(self, op) -> None: ...
diff --git a/pandas-stubs/core/arrays/interval.pyi b/pandas-stubs/core/arrays/interval.pyi
index 304cc2960..a7c8d5a6e 100644
--- a/pandas-stubs/core/arrays/interval.pyi
+++ b/pandas-stubs/core/arrays/interval.pyi
@@ -21,7 +21,7 @@ from pandas._typing import (
     ScalarIndexer,
     SequenceIndexer,
     TakeIndexer,
-    np_ndarray_bool,
+    np_1darray,
 )
 
 IntervalOrNA: TypeAlias = Interval | float
@@ -99,7 +99,7 @@ class IntervalArray(IntervalMixin, ExtensionArray):
     def mid(self) -> Index: ...
     @property
     def is_non_overlapping_monotonic(self) -> bool: ...
-    def __array__(self, dtype=...) -> np.ndarray: ...
+    def __array__(self, dtype=...) -> np_1darray: ...
     def __arrow_array__(self, type=...): ...
     def to_tuples(self, na_tuple: bool = True): ...
     def repeat(self, repeats, axis: Axis | None = ...): ...
@@ -108,5 +108,5 @@ class IntervalArray(IntervalMixin, ExtensionArray):
     @overload
     def contains(
         self, other: Scalar | ExtensionArray | Index | np.ndarray
-    ) -> np_ndarray_bool: ...
+    ) -> np_1darray[np.bool]: ...
     def overlaps(self, other: Interval) -> bool: ...
diff --git a/pandas-stubs/core/base.pyi b/pandas-stubs/core/base.pyi
index da7b69b74..78180a2ed 100644
--- a/pandas-stubs/core/base.pyi
+++ b/pandas-stubs/core/base.pyi
@@ -26,6 +26,7 @@ from pandas._typing import (
     DropKeep,
     NDFrameT,
     Scalar,
+    np_1darray,
     npt,
 )
 from pandas.util._decorators import cache_readonly
@@ -63,7 +64,7 @@ class IndexOpsMixin(OpsMixin, Generic[S1]):
         copy: bool = False,
         na_value: Scalar = ...,
         **kwargs,
-    ) -> np.ndarray: ...
+    ) -> np_1darray: ...
     @property
     def empty(self) -> bool: ...
     def max(self, axis=..., skipna: bool = ..., **kwargs): ...
@@ -114,7 +115,7 @@ class IndexOpsMixin(OpsMixin, Generic[S1]):
     def is_monotonic_increasing(self) -> bool: ...
     def factorize(
         self, sort: bool = False, use_na_sentinel: bool = True
-    ) -> tuple[np.ndarray, np.ndarray | Index | Categorical]: ...
+    ) -> tuple[np_1darray, np_1darray | Index | Categorical]: ...
     def searchsorted(
         self, value, side: Literal["left", "right"] = ..., sorter=...
     ) -> int | list[int]: ...
diff --git a/pandas-stubs/core/dtypes/missing.pyi b/pandas-stubs/core/dtypes/missing.pyi
index e36496cfd..16c7e12b3 100644
--- a/pandas-stubs/core/dtypes/missing.pyi
+++ b/pandas-stubs/core/dtypes/missing.pyi
@@ -4,20 +4,23 @@ from typing import (
 )
 
 import numpy as np
-from numpy import typing as npt
 from pandas import (
     DataFrame,
     Index,
     Series,
 )
+from pandas.core.arrays import ExtensionArray
 from typing_extensions import TypeIs
 
 from pandas._libs.missing import NAType
 from pandas._libs.tslibs import NaTType
 from pandas._typing import (
-    ArrayLike,
     Scalar,
     ScalarT,
+    ShapeT,
+    np_1darray,
+    np_ndarray,
+    np_ndarray_bool,
 )
 
 isposinf_scalar = ...
@@ -28,7 +31,11 @@ def isna(obj: DataFrame) -> DataFrame: ...
 @overload
 def isna(obj: Series) -> Series[bool]: ...
 @overload
-def isna(obj: Index | list[Any] | ArrayLike) -> npt.NDArray[np.bool_]: ...
+def isna(obj: Index | ExtensionArray | list[ScalarT]) -> np_1darray[np.bool]: ...
+@overload
+def isna(obj: np_ndarray[ShapeT]) -> np_ndarray[ShapeT, np.bool]: ...
+@overload
+def isna(obj: list[Any]) -> np_ndarray_bool: ...
 @overload
 def isna(
     obj: Scalar | NaTType | NAType | None,
@@ -41,7 +48,11 @@ def notna(obj: DataFrame) -> DataFrame: ...
 @overload
 def notna(obj: Series) -> Series[bool]: ...
 @overload
-def notna(obj: Index | list[Any] | ArrayLike) -> npt.NDArray[np.bool_]: ...
+def notna(obj: Index | ExtensionArray | list[ScalarT]) -> np_1darray[np.bool]: ...
+@overload
+def notna(obj: np_ndarray[ShapeT]) -> np_ndarray[ShapeT, np.bool]: ...
+@overload
+def notna(obj: Index | list[Any]) -> np_ndarray_bool: ...
 @overload
 def notna(obj: ScalarT | NaTType | NAType | None) -> TypeIs[ScalarT]: ...
 
diff --git a/pandas-stubs/core/frame.pyi b/pandas-stubs/core/frame.pyi
index a33321d75..14d8bfea1 100644
--- a/pandas-stubs/core/frame.pyi
+++ b/pandas-stubs/core/frame.pyi
@@ -165,6 +165,7 @@ from pandas._typing import (
     ValueKeyFunc,
     WriteBuffer,
     XMLParsers,
+    np_2darray,
     npt,
     num,
 )
@@ -452,7 +453,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         dtype: npt.DTypeLike | None = ...,
         copy: bool = False,
         na_value: Scalar = ...,
-    ) -> np.ndarray: ...
+    ) -> np_2darray: ...
     @overload
     def to_dict(
         self,
@@ -1766,7 +1767,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     @property
     def size(self) -> int: ...
     @property
-    def values(self) -> np.ndarray: ...
+    def values(self) -> np_2darray: ...
     # methods
     @final
     def abs(self) -> Self: ...
diff --git a/pandas-stubs/core/indexes/accessors.pyi b/pandas-stubs/core/indexes/accessors.pyi
index 6746c9dd4..e96615dee 100644
--- a/pandas-stubs/core/indexes/accessors.pyi
+++ b/pandas-stubs/core/indexes/accessors.pyi
@@ -10,7 +10,6 @@ from typing import (
 )
 
 import numpy as np
-import numpy.typing as npt
 from pandas import (
     DatetimeIndex,
     Index,
@@ -40,6 +39,7 @@ from pandas._typing import (
     TimestampConvention,
     TimeUnit,
     TimeZones,
+    np_1darray,
     np_ndarray_bool,
 )
 
@@ -88,7 +88,7 @@ class _DatetimeFieldOps(
 ): ...
 
 _DTBoolOpsReturnType = TypeVar(
-    "_DTBoolOpsReturnType", bound=Series[bool] | np_ndarray_bool
+    "_DTBoolOpsReturnType", bound=Series[bool] | np_1darray[np.bool]
 )
 
 class _IsLeapYearProperty(Generic[_DTBoolOpsReturnType]):
@@ -126,10 +126,10 @@ class _DatetimeObjectOps(
 ): ...
 
 _DTOtherOpsDateReturnType = TypeVar(
-    "_DTOtherOpsDateReturnType", bound=Series[dt.date] | np.ndarray
+    "_DTOtherOpsDateReturnType", bound=Series[dt.date] | np_1darray[np.object_]
 )
 _DTOtherOpsTimeReturnType = TypeVar(
-    "_DTOtherOpsTimeReturnType", bound=Series[dt.time] | np.ndarray
+    "_DTOtherOpsTimeReturnType", bound=Series[dt.time] | np_1darray[np.object_]
 )
 
 class _DatetimeOtherOps(Generic[_DTOtherOpsDateReturnType, _DTOtherOpsTimeReturnType]):
@@ -280,7 +280,7 @@ class DatetimeProperties(
         _DTToPeriodReturnType,
     ],
 ):
-    def to_pydatetime(self) -> np.ndarray: ...
+    def to_pydatetime(self) -> np_1darray[np.object_]: ...
     def isocalendar(self) -> DataFrame: ...
     @property
     def unit(self) -> TimeUnit: ...
@@ -296,7 +296,7 @@ _TDTotalSecondsReturnType = TypeVar(
 class _TimedeltaPropertiesNoRounding(
     Generic[_TDNoRoundingMethodReturnType, _TDTotalSecondsReturnType]
 ):
-    def to_pytimedelta(self) -> np.ndarray: ...
+    def to_pytimedelta(self) -> np_1darray[np.object_]: ...
     @property
     def components(self) -> DataFrame: ...
     @property
@@ -401,10 +401,10 @@ class DatetimeIndexProperties(
     Properties,
     _DatetimeNoTZProperties[
         Index[int],
-        np_ndarray_bool,
+        np_1darray[np.bool],
         DatetimeIndex,
-        np.ndarray,
-        np.ndarray,
+        np_1darray[np.object_],
+        np_1darray[np.object_],
         BaseOffset,
         DatetimeIndex,
         Index,
@@ -416,7 +416,7 @@ class DatetimeIndexProperties(
     def is_normalized(self) -> bool: ...
     @property
     def tzinfo(self) -> _tzinfo | None: ...
-    def to_pydatetime(self) -> npt.NDArray[np.object_]: ...
+    def to_pydatetime(self) -> np_1darray[np.object_]: ...
     def std(
         self, axis: int | None = ..., ddof: int = ..., skipna: bool = ...
     ) -> Timedelta: ...
diff --git a/pandas-stubs/core/indexes/base.pyi b/pandas-stubs/core/indexes/base.pyi
index 0d7b440e6..942e2a180 100644
--- a/pandas-stubs/core/indexes/base.pyi
+++ b/pandas-stubs/core/indexes/base.pyi
@@ -62,8 +62,8 @@ from pandas._typing import (
     SliceType,
     TimedeltaDtypeArg,
     TimestampDtypeArg,
+    np_1darray,
     np_ndarray_anyint,
-    np_ndarray_bool,
     np_ndarray_complex,
     np_ndarray_float,
     type_t,
@@ -274,7 +274,7 @@ class Index(IndexOpsMixin[S1]):
     ) -> StringMethods[
         Self,
         MultiIndex,
-        np_ndarray_bool,
+        np_1darray[np.bool],
         Index[list[_str]],
         Index[int],
         Index[bytes],
@@ -286,7 +286,7 @@ class Index(IndexOpsMixin[S1]):
     def __len__(self) -> int: ...
     def __array__(
         self, dtype: _str | np.dtype = ..., copy: bool | None = ...
-    ) -> np.ndarray: ...
+    ) -> np_1darray: ...
     def __array_wrap__(self, result, context=...): ...
     @property
     def dtype(self) -> DtypeObj: ...
@@ -354,7 +354,7 @@ class Index(IndexOpsMixin[S1]):
     def dropna(self, how: AnyAll = "any") -> Self: ...
     def unique(self, level=...) -> Self: ...
     def drop_duplicates(self, *, keep: DropKeep = ...) -> Self: ...
-    def duplicated(self, keep: DropKeep = "first") -> np_ndarray_bool: ...
+    def duplicated(self, keep: DropKeep = "first") -> np_1darray[np.bool]: ...
     def __and__(self, other: Never) -> Never: ...
     def __rand__(self, other: Never) -> Never: ...
     def __or__(self, other: Never) -> Never: ...
@@ -378,7 +378,7 @@ class Index(IndexOpsMixin[S1]):
         result_name: Hashable = ...,
         sort: bool | None = None,
     ) -> Self: ...
-    def get_loc(self, key: Label) -> int | slice | np_ndarray_bool: ...
+    def get_loc(self, key: Label) -> int | slice | np_1darray[np.bool]: ...
     def get_indexer(
         self, target, method: ReindexMethod | None = ..., limit=..., tolerance=...
     ): ...
@@ -400,7 +400,7 @@ class Index(IndexOpsMixin[S1]):
         sort: bool = ...,
     ): ...
     @property
-    def values(self) -> np.ndarray: ...
+    def values(self) -> np_1darray: ...
     @property
     def array(self) -> ExtensionArray: ...
     def memory_usage(self, deep: bool = False): ...
@@ -445,7 +445,7 @@ class Index(IndexOpsMixin[S1]):
     @final
     def groupby(self, values) -> dict[Hashable, np.ndarray]: ...
     def map(self, mapper, na_action=...) -> Index: ...
-    def isin(self, values, level=...) -> np_ndarray_bool: ...
+    def isin(self, values, level=...) -> np_1darray[np.bool]: ...
     def slice_indexer(
         self,
         start: Label | None = None,
@@ -462,13 +462,13 @@ class Index(IndexOpsMixin[S1]):
     @property
     def shape(self) -> tuple[int, ...]: ...
     # Extra methods from old stubs
-    def __eq__(self, other: object) -> np_ndarray_bool: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
+    def __eq__(self, other: object) -> np_1darray[np.bool]: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
     def __iter__(self) -> Iterator[S1]: ...
-    def __ne__(self, other: object) -> np_ndarray_bool: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
-    def __le__(self, other: Self | S1) -> np_ndarray_bool: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
-    def __ge__(self, other: Self | S1) -> np_ndarray_bool: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
-    def __lt__(self, other: Self | S1) -> np_ndarray_bool: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
-    def __gt__(self, other: Self | S1) -> np_ndarray_bool: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
+    def __ne__(self, other: object) -> np_1darray[np.bool]: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
+    def __le__(self, other: Self | S1) -> np_1darray[np.bool]: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
+    def __ge__(self, other: Self | S1) -> np_1darray[np.bool]: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
+    def __lt__(self, other: Self | S1) -> np_1darray[np.bool]: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
+    def __gt__(self, other: Self | S1) -> np_1darray[np.bool]: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
     # overwrite inherited methods from OpsMixin
     @overload
     def __mul__(
diff --git a/pandas-stubs/core/indexes/interval.pyi b/pandas-stubs/core/indexes/interval.pyi
index b82cdeddb..581ab274f 100644
--- a/pandas-stubs/core/indexes/interval.pyi
+++ b/pandas-stubs/core/indexes/interval.pyi
@@ -32,6 +32,7 @@ from pandas._typing import (
     IntervalT,
     Label,
     MaskType,
+    np_1darray,
     np_ndarray_anyint,
     np_ndarray_bool,
     npt,
@@ -221,7 +222,7 @@ class IntervalIndex(ExtensionIndex[IntervalT], IntervalMixin):
     def memory_usage(self, deep: bool = False) -> int: ...
     @property
     def is_overlapping(self) -> bool: ...
-    def get_loc(self, key: Label) -> int | slice | npt.NDArray[np.bool_]: ...
+    def get_loc(self, key: Label) -> int | slice | np_1darray[np.bool]: ...
     @final
     def get_indexer(
         self,
@@ -260,7 +261,7 @@ class IntervalIndex(ExtensionIndex[IntervalT], IntervalMixin):
     @overload  # type: ignore[override]
     def __gt__(
         self, other: IntervalT | IntervalIndex[IntervalT]
-    ) -> np_ndarray_bool: ...
+    ) -> np_1darray[np.bool]: ...
     @overload
     def __gt__(  # pyright: ignore[reportIncompatibleMethodOverride]
         self, other: pd.Series[IntervalT]
@@ -268,7 +269,7 @@ class IntervalIndex(ExtensionIndex[IntervalT], IntervalMixin):
     @overload  # type: ignore[override]
     def __ge__(
         self, other: IntervalT | IntervalIndex[IntervalT]
-    ) -> np_ndarray_bool: ...
+    ) -> np_1darray[np.bool]: ...
     @overload
     def __ge__(  # pyright: ignore[reportIncompatibleMethodOverride]
         self, other: pd.Series[IntervalT]
@@ -276,7 +277,7 @@ class IntervalIndex(ExtensionIndex[IntervalT], IntervalMixin):
     @overload  # type: ignore[override]
     def __le__(
         self, other: IntervalT | IntervalIndex[IntervalT]
-    ) -> np_ndarray_bool: ...
+    ) -> np_1darray[np.bool]: ...
     @overload
     def __le__(  # pyright: ignore[reportIncompatibleMethodOverride]
         self, other: pd.Series[IntervalT]
@@ -284,13 +285,13 @@ class IntervalIndex(ExtensionIndex[IntervalT], IntervalMixin):
     @overload  # type: ignore[override]
     def __lt__(
         self, other: IntervalT | IntervalIndex[IntervalT]
-    ) -> np_ndarray_bool: ...
+    ) -> np_1darray[np.bool]: ...
     @overload
     def __lt__(  # pyright: ignore[reportIncompatibleMethodOverride]
         self, other: pd.Series[IntervalT]
     ) -> pd.Series[bool]: ...
     @overload  # type: ignore[override]
-    def __eq__(self, other: IntervalT | IntervalIndex[IntervalT]) -> np_ndarray_bool: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
+    def __eq__(self, other: IntervalT | IntervalIndex[IntervalT]) -> np_1darray[np.bool]: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
     @overload
     def __eq__(self, other: pd.Series[IntervalT]) -> pd.Series[bool]: ...  # type: ignore[overload-overlap]
     @overload
@@ -298,7 +299,7 @@ class IntervalIndex(ExtensionIndex[IntervalT], IntervalMixin):
         self, other: object
     ) -> Literal[False]: ...
     @overload  # type: ignore[override]
-    def __ne__(self, other: IntervalT | IntervalIndex[IntervalT]) -> np_ndarray_bool: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
+    def __ne__(self, other: IntervalT | IntervalIndex[IntervalT]) -> np_1darray[np.bool]: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
     @overload
     def __ne__(self, other: pd.Series[IntervalT]) -> pd.Series[bool]: ...  # type: ignore[overload-overlap]
     @overload
diff --git a/pandas-stubs/core/indexes/multi.pyi b/pandas-stubs/core/indexes/multi.pyi
index d51528d9d..a4301ad29 100644
--- a/pandas-stubs/core/indexes/multi.pyi
+++ b/pandas-stubs/core/indexes/multi.pyi
@@ -25,8 +25,8 @@ from pandas._typing import (
     MaskType,
     NaPosition,
     SequenceNotStr,
+    np_1darray,
     np_ndarray_anyint,
-    np_ndarray_bool,
 )
 
 class MultiIndex(Index):
@@ -161,4 +161,4 @@ class MultiIndex(Index):
     def equal_levels(self, other): ...
     def insert(self, loc, item): ...
     def delete(self, loc): ...
-    def isin(self, values, level=...) -> np_ndarray_bool: ...
+    def isin(self, values, level=...) -> np_1darray[np.bool]: ...
diff --git a/pandas-stubs/core/indexes/range.pyi b/pandas-stubs/core/indexes/range.pyi
index 5c2d18263..2f4c82c78 100644
--- a/pandas-stubs/core/indexes/range.pyi
+++ b/pandas-stubs/core/indexes/range.pyi
@@ -13,8 +13,8 @@ from pandas.core.indexes.base import Index
 from pandas._typing import (
     HashableT,
     MaskType,
+    np_1darray,
     np_ndarray_anyint,
-    npt,
 )
 
 class RangeIndex(Index[int]):
@@ -58,7 +58,7 @@ class RangeIndex(Index[int]):
     def argsort(self, *args, **kwargs): ...
     def factorize(
         self, sort: bool = False, use_na_sentinel: bool = True
-    ) -> tuple[npt.NDArray[np.intp], RangeIndex]: ...
+    ) -> tuple[np_1darray[np.intp], RangeIndex]: ...
     def equals(self, other): ...
     @final
     def join(
diff --git a/pandas-stubs/core/series.pyi b/pandas-stubs/core/series.pyi
index 69dfc1b08..d98408bb1 100644
--- a/pandas-stubs/core/series.pyi
+++ b/pandas-stubs/core/series.pyi
@@ -176,6 +176,7 @@ from pandas._typing import (
     ValueKeyFunc,
     VoidDtypeArg,
     WriteBuffer,
+    np_1darray,
     np_ndarray_anyint,
     np_ndarray_bool,
     np_ndarray_complex,
@@ -453,7 +454,7 @@ class Series(IndexOpsMixin[S1], NDFrame):
     ): ...
     def __array__(
         self, dtype: _str | np.dtype = ..., copy: bool | None = ...
-    ) -> np.ndarray: ...
+    ) -> np_1darray: ...
     @property
     def axes(self) -> list: ...
     @final
@@ -2885,7 +2886,7 @@ class Series(IndexOpsMixin[S1], NDFrame):
         copy: bool = False,
         na_value: Scalar = ...,
         **kwargs: Any,
-    ) -> np.ndarray: ...
+    ) -> np_1darray: ...
     def tolist(self) -> list[S1]: ...
     def var(
         self,
diff --git a/pandas-stubs/core/strings/accessor.pyi b/pandas-stubs/core/strings/accessor.pyi
index bedd8ac7b..a290fa12f 100644
--- a/pandas-stubs/core/strings/accessor.pyi
+++ b/pandas-stubs/core/strings/accessor.pyi
@@ -31,7 +31,7 @@ from pandas._typing import (
     DtypeObj,
     Scalar,
     T,
-    np_ndarray_bool,
+    np_1darray,
 )
 
 # Used for the result of str.split with expand=True
@@ -39,7 +39,7 @@ _T_EXPANDING = TypeVar("_T_EXPANDING", bound=DataFrame | MultiIndex)
 # Used for the result of str.split with expand=False
 _T_LIST_STR = TypeVar("_T_LIST_STR", bound=Series[list[str]] | Index[list[str]])
 # Used for the result of str.match
-_T_BOOL = TypeVar("_T_BOOL", bound=Series[bool] | np_ndarray_bool)
+_T_BOOL = TypeVar("_T_BOOL", bound=Series[bool] | np_1darray[np.bool])
 # Used for the result of str.index / str.find
 _T_INT = TypeVar("_T_INT", bound=Series[int] | Index[int])
 # Used for the result of str.encode
diff --git a/tests/__init__.py b/tests/__init__.py
index c4a94e773..7a95b9f82 100644
--- a/tests/__init__.py
+++ b/tests/__init__.py
@@ -11,6 +11,9 @@
     TYPE_CHECKING,
     Final,
     Literal,
+    TypeVar,
+    get_args,
+    get_origin,
 )
 
 import numpy as np
@@ -40,11 +43,16 @@
         TimestampDtypeArg as TimestampDtypeArg,
         UIntDtypeArg as UIntDtypeArg,
         VoidDtypeArg as VoidDtypeArg,
+        np_1darray as np_1darray,
+        np_2darray as np_2darray,
         np_ndarray_bool as np_ndarray_bool,
         np_ndarray_int as np_ndarray_int,
     )
 else:
+    _G = TypeVar("_G", bound=np.generic)
     # Separately define here so pytest works
+    np_1darray = np.ndarray[tuple[int], np.dtype[_G]]
+    np_2darray = np.ndarray[tuple[int, int], np.dtype[_G]]
     np_ndarray_bool = npt.NDArray[np.bool_]
     np_ndarray_int = npt.NDArray[np.signedinteger]
 
@@ -61,8 +69,39 @@ def check(
     attr: str = "left",
     index_to_check_for_type: Literal[0, -1] = 0,
 ) -> T:
-    if not isinstance(actual, klass):
+    __tracebackhide__ = True
+    origin = get_origin(klass)
+    if not isinstance(actual, origin or klass):
         raise RuntimeError(f"Expected type '{klass}' but got '{type(actual)}'")
+    if origin is np.ndarray:
+        # Check shape and dtype
+        args = get_args(klass)
+        shape_type = args[0] if len(args) >= 1 else None
+        dtype_type = args[1] if len(args) >= 2 else None
+        if (
+            shape_type
+            and get_origin(shape_type) is tuple
+            and (tuple_args := get_args(shape_type))
+            and ... not in tuple_args  # fixed-length tuple
+            and (arr_ndim := getattr(actual, "ndim"))
+            != (expected_ndim := len(tuple_args))
+        ):
+            raise RuntimeError(
+                f"Array has wrong dimension {arr_ndim}, expected {expected_ndim}"
+            )
+
+        if (
+            dtype_type
+            and get_origin(dtype_type) is np.dtype
+            and (dtype_args := get_args(dtype_type))
+            and isinstance((expected_dtype := dtype_args[0]), type)
+            and issubclass(expected_dtype, np.generic)
+            and (arr_dtype := getattr(actual, "dtype")) != expected_dtype
+        ):
+            raise RuntimeError(
+                f"Array has wrong dtype {arr_dtype}, expected {expected_dtype.__name__}"
+            )
+
     if dtype is None:
         return actual
 
diff --git a/tests/series/test_series.py b/tests/series/test_series.py
index 795193782..4070b4b3d 100644
--- a/tests/series/test_series.py
+++ b/tests/series/test_series.py
@@ -56,6 +56,7 @@
     WINDOWS,
     check,
     ensure_clean,
+    np_1darray,
     pytest_warns_bounded,
 )
 from tests.extension.decimal.array import DecimalDtype
@@ -91,7 +92,6 @@
         UIntDtypeArg,
         VoidDtypeArg,
     )
-    from tests import np_ndarray_int  # noqa: F401
 
 else:
     TimedeltaSeries: TypeAlias = pd.Series
@@ -1870,7 +1870,7 @@ def test_types_to_dict() -> None:
 def test_categorical_codes():
     # GH-111
     cat = pd.Categorical(["a", "b", "a"])
-    assert_type(cat.codes, "np_ndarray_int")
+    check(assert_type(cat.codes, np_1darray[np.signedinteger]), np_1darray[np.int8])
 
 
 def test_relops() -> None:
@@ -2022,12 +2022,12 @@ def test_dtype_type() -> None:
 
 def test_types_to_numpy() -> None:
     s = pd.Series(["a", "b", "c"], dtype=str)
-    check(assert_type(s.to_numpy(), np.ndarray), np.ndarray)
-    check(assert_type(s.to_numpy(dtype="str", copy=True), np.ndarray), np.ndarray)
-    check(assert_type(s.to_numpy(na_value=0), np.ndarray), np.ndarray)
-    check(assert_type(s.to_numpy(na_value=np.int32(4)), np.ndarray), np.ndarray)
-    check(assert_type(s.to_numpy(na_value=np.float16(4)), np.ndarray), np.ndarray)
-    check(assert_type(s.to_numpy(na_value=np.complex128(4, 7)), np.ndarray), np.ndarray)
+    check(assert_type(s.to_numpy(), np_1darray), np_1darray)
+    check(assert_type(s.to_numpy(dtype="str", copy=True), np_1darray), np_1darray)
+    check(assert_type(s.to_numpy(na_value=0), np_1darray), np_1darray)
+    check(assert_type(s.to_numpy(na_value=np.int32(4)), np_1darray), np_1darray)
+    check(assert_type(s.to_numpy(na_value=np.float16(4)), np_1darray), np_1darray)
+    check(assert_type(s.to_numpy(na_value=np.complex128(4, 7)), np_1darray), np_1darray)
 
 
 def test_where() -> None:
diff --git a/tests/test_frame.py b/tests/test_frame.py
index f70504ef4..cf1b58015 100644
--- a/tests/test_frame.py
+++ b/tests/test_frame.py
@@ -57,6 +57,7 @@
     TYPE_CHECKING_INVALID_USAGE,
     check,
     ensure_clean,
+    np_2darray,
     pytest_warns_bounded,
 )
 
@@ -1946,18 +1947,18 @@ def test_types_cov() -> None:
 
 def test_types_to_numpy() -> None:
     df = pd.DataFrame(data={"col1": [1, 1, 2], "col2": [3, 4, 5]})
-    check(assert_type(df.to_numpy(), np.ndarray), np.ndarray)
-    check(assert_type(df.to_numpy(dtype="str", copy=True), np.ndarray), np.ndarray)
+    check(assert_type(df.to_numpy(), np_2darray), np_2darray)
+    check(assert_type(df.to_numpy(dtype="str", copy=True), np_2darray), np_2darray)
     # na_value param was added in 1.1.0 https://pandas.pydata.org/docs/whatsnew/v1.1.0.html
-    check(assert_type(df.to_numpy(na_value=0), np.ndarray), np.ndarray)
+    check(assert_type(df.to_numpy(na_value=0), np_2darray), np_2darray)
 
     df = pd.DataFrame(data={"col1": [1, 1, 2]}, dtype=np.complex128)
-    check(assert_type(df.to_numpy(na_value=0), np.ndarray), np.ndarray)
-    check(assert_type(df.to_numpy(na_value=np.int32(4)), np.ndarray), np.ndarray)
-    check(assert_type(df.to_numpy(na_value=np.float16(3.68)), np.ndarray), np.ndarray)
+    check(assert_type(df.to_numpy(na_value=0), np_2darray), np_2darray)
+    check(assert_type(df.to_numpy(na_value=np.int32(4)), np_2darray), np_2darray)
+    check(assert_type(df.to_numpy(na_value=np.float16(3.68)), np_2darray), np_2darray)
     check(
-        assert_type(df.to_numpy(na_value=np.complex128(3.8, -493.2)), np.ndarray),
-        np.ndarray,
+        assert_type(df.to_numpy(na_value=np.complex128(3.8, -493.2)), np_2darray),
+        np_2darray,
     )
 
 
diff --git a/tests/test_indexes.py b/tests/test_indexes.py
index f6ad2a270..adf21c01a 100644
--- a/tests/test_indexes.py
+++ b/tests/test_indexes.py
@@ -26,6 +26,7 @@
     PD_LTE_23,
     TYPE_CHECKING_INVALID_USAGE,
     check,
+    np_1darray,
     pytest_warns_bounded,
 )
 
@@ -42,13 +43,13 @@ def test_index_duplicated() -> None:
     df = pd.DataFrame({"x": [1, 2, 3, 4]}, index=pd.Index([1, 2, 3, 2]))
     ind = df.index
     duplicated = ind.duplicated("first")
-    check(assert_type(duplicated, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
+    check(assert_type(duplicated, np_1darray[np.bool]), np_1darray[np.bool])
 
 
 def test_index_isin() -> None:
     ind = pd.Index([1, 2, 3, 4, 5])
     isin = ind.isin([2, 4])
-    check(assert_type(isin, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
+    check(assert_type(isin, np_1darray[np.bool]), np_1darray[np.bool])
 
 
 def test_index_astype() -> None:
@@ -202,13 +203,6 @@ def test_str_rsplit() -> None:
     )
 
 
-def test_str_match() -> None:
-    i = pd.Index(
-        ["applep", "bananap", "Cherryp", "DATEp", "eGGpLANTp", "123p", "23.45p"]
-    )
-    check(assert_type(i.str.match("pp"), npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-
-
 def test_index_rename() -> None:
     """Test that index rename returns an element of type Index."""
     ind = pd.Index([1, 2, 3], name="foo")
@@ -244,9 +238,9 @@ def test_index_neg():
 
 def test_types_to_numpy() -> None:
     idx = pd.Index([1, 2])
-    check(assert_type(idx.to_numpy(), np.ndarray), np.ndarray)
-    check(assert_type(idx.to_numpy(dtype="int", copy=True), np.ndarray), np.ndarray)
-    check(assert_type(idx.to_numpy(na_value=0), np.ndarray), np.ndarray)
+    check(assert_type(idx.to_numpy(), np_1darray), np_1darray)
+    check(assert_type(idx.to_numpy(dtype="int", copy=True), np_1darray), np_1darray)
+    check(assert_type(idx.to_numpy(na_value=0), np_1darray), np_1darray)
 
 
 def test_index_arithmetic() -> None:
@@ -289,10 +283,10 @@ def test_index_relops() -> None:
     check(assert_type(data[dt_idx > x], pd.DatetimeIndex), pd.DatetimeIndex)
 
     ind = pd.Index([1, 2, 3])
-    check(assert_type(ind <= 2, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-    check(assert_type(ind >= 2, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-    check(assert_type(ind < 2, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-    check(assert_type(ind > 2, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
+    check(assert_type(ind <= 2, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(ind >= 2, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(ind < 2, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(ind > 2, np_1darray[np.bool]), np_1darray[np.bool])
 
 
 def test_range_index_union():
@@ -1299,16 +1293,14 @@ def test_datetime_operators_builtin() -> None:
 def test_get_loc() -> None:
     unique_index = pd.Index(list("abc"))
     check(
-        assert_type(
-            unique_index.get_loc("b"), Union[int, slice, npt.NDArray[np.bool_]]
-        ),
+        assert_type(unique_index.get_loc("b"), Union[int, slice, np_1darray[np.bool]]),
         int,
     )
 
     monotonic_index = pd.Index(list("abbc"))
     check(
         assert_type(
-            monotonic_index.get_loc("b"), Union[int, slice, npt.NDArray[np.bool_]]
+            monotonic_index.get_loc("b"), Union[int, slice, np_1darray[np.bool]]
         ),
         slice,
     )
@@ -1316,10 +1308,25 @@ def test_get_loc() -> None:
     non_monotonic_index = pd.Index(list("abcb"))
     check(
         assert_type(
-            non_monotonic_index.get_loc("b"), Union[int, slice, npt.NDArray[np.bool_]]
+            non_monotonic_index.get_loc("b"), Union[int, slice, np_1darray[np.bool]]
+        ),
+        np_1darray[np.bool],
+    )
+
+    i1, i2, i3 = pd.Interval(0, 1), pd.Interval(1, 2), pd.Interval(0, 2)
+    unique_interval_index = pd.IntervalIndex([i1, i2])
+    check(
+        assert_type(
+            unique_interval_index.get_loc(i1), Union[int, slice, np_1darray[np.bool]]
+        ),
+        np.int64,
+    )
+    overlap_interval_index = pd.IntervalIndex([i1, i2, i3])
+    check(
+        assert_type(
+            overlap_interval_index.get_loc(1), Union[int, slice, np_1darray[np.bool]]
         ),
-        np.ndarray,
-        np.bool_,
+        np_1darray[np.bool],
     )
 
 
@@ -1336,14 +1343,14 @@ def test_value_counts() -> None:
 def test_index_factorize() -> None:
     """Test Index.factorize method."""
     codes, idx_uniques = pd.Index(["b", "b", "a", "c", "b"]).factorize()
-    check(assert_type(codes, np.ndarray), np.ndarray)
-    check(assert_type(idx_uniques, np.ndarray | Index | Categorical), pd.Index)
+    check(assert_type(codes, np_1darray), np_1darray)
+    check(assert_type(idx_uniques, np_1darray | Index | Categorical), pd.Index)
 
     codes, idx_uniques = pd.Index(["b", "b", "a", "c", "b"]).factorize(
         use_na_sentinel=False
     )
-    check(assert_type(codes, np.ndarray), np.ndarray)
-    check(assert_type(idx_uniques, np.ndarray | Index | Categorical), pd.Index)
+    check(assert_type(codes, np_1darray), np_1darray)
+    check(assert_type(idx_uniques, np_1darray | Index | Categorical), pd.Index)
 
 
 def test_disallow_empty_index() -> None:
diff --git a/tests/test_interval.py b/tests/test_interval.py
index 208255f89..8d9081710 100644
--- a/tests/test_interval.py
+++ b/tests/test_interval.py
@@ -1,13 +1,13 @@
 from __future__ import annotations
 
 import numpy as np
-from numpy import typing as npt
 import pandas as pd
 from typing_extensions import assert_type
 
 from tests import (
     TYPE_CHECKING_INVALID_USAGE,
     check,
+    np_1darray,
 )
 
 
@@ -127,4 +127,4 @@ def test_interval_array_contains():
     ser = pd.Series(obj, index=df.index)
     arr = ser.array
     check(assert_type(arr.contains(df["A"]), "pd.Series[bool]"), pd.Series, np.bool_)
-    check(assert_type(arr.contains(3), npt.NDArray[np.bool_]), np.ndarray)
+    check(assert_type(arr.contains(3), np_1darray[np.bool]), np_1darray[np.bool])
diff --git a/tests/test_pandas.py b/tests/test_pandas.py
index cfa6f6be2..a7633fa8a 100644
--- a/tests/test_pandas.py
+++ b/tests/test_pandas.py
@@ -33,6 +33,9 @@
     PD_LTE_23,
     TYPE_CHECKING_INVALID_USAGE,
     check,
+    np_1darray,
+    np_2darray,
+    np_ndarray_bool,
     pytest_warns_bounded,
 )
 
@@ -428,20 +431,47 @@ def test_types_json_normalize() -> None:
 
 def test_isna() -> None:
     # https://github.com/pandas-dev/pandas-stubs/issues/264
-    s1 = pd.Series([1, np.nan, 3.2])
-    check(assert_type(pd.isna(s1), "pd.Series[bool]"), pd.Series, np.bool_)
-
-    s2 = pd.Series([1, 3.2])
-    check(assert_type(pd.notna(s2), "pd.Series[bool]"), pd.Series, np.bool_)
-
-    df1 = pd.DataFrame({"a": [1, 2, 1, 2], "b": [1, 1, 2, np.nan]})
-    check(assert_type(pd.isna(df1), "pd.DataFrame"), pd.DataFrame)
-
-    idx1 = pd.Index([1, 2, np.nan])
-    check(assert_type(pd.isna(idx1), npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-
-    idx2 = pd.Index([1, 2])
-    check(assert_type(pd.notna(idx2), npt.NDArray[np.bool_]), np.ndarray, np.bool_)
+    s = pd.Series([1, np.nan, 3.2])
+    check(assert_type(pd.isna(s), "pd.Series[bool]"), pd.Series, np.bool_)
+    check(assert_type(pd.notna(s), "pd.Series[bool]"), pd.Series, np.bool_)
+
+    df = pd.DataFrame({"a": [1, 2, 1, 2], "b": [1, 1, 2, np.nan]})
+    check(assert_type(pd.isna(df), "pd.DataFrame"), pd.DataFrame)
+    check(assert_type(pd.notna(df), "pd.DataFrame"), pd.DataFrame)
+
+    idx = pd.Index([1, 2, np.nan, float("nan")])
+    check(assert_type(pd.isna(idx), np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(pd.notna(idx), np_1darray[np.bool]), np_1darray[np.bool])
+
+    # ExtensionArray
+    ext_arr = idx.array
+    check(assert_type(pd.isna(ext_arr), np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(pd.notna(ext_arr), np_1darray[np.bool]), np_1darray[np.bool])
+
+    # 1-D numpy array
+    arr_1d = idx.to_numpy()
+    check(assert_type(pd.isna(arr_1d), np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(pd.notna(arr_1d), np_1darray[np.bool]), np_1darray[np.bool])
+
+    # 2-D numpy array
+    arr_2d = idx.to_numpy().reshape(2, 2)
+    check(assert_type(pd.isna(arr_2d), np_2darray[np.bool]), np_2darray[np.bool])
+    check(assert_type(pd.notna(arr_2d), np_2darray[np.bool]), np_2darray[np.bool])
+
+    # N-D numpy array
+    arr_nd = idx.to_numpy().reshape([2, 2])
+    check(assert_type(pd.isna(arr_nd), np_ndarray_bool), np_ndarray_bool)
+    check(assert_type(pd.notna(arr_nd), np_ndarray_bool), np_ndarray_bool)
+
+    # List of scalars
+    l_sca = [1, 2.5, float("nan")]
+    check(assert_type(pd.isna(l_sca), np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(pd.notna(l_sca), np_1darray[np.bool]), np_1darray[np.bool])
+
+    # List of unknown members
+    l_any: list[object] = [arr_1d, ext_arr]
+    check(assert_type(pd.isna(l_any), np_ndarray_bool), np_ndarray_bool)
+    check(assert_type(pd.notna(l_any), np_ndarray_bool), np_ndarray_bool)
 
     assert check(assert_type(pd.isna(pd.NA), bool), bool)
     assert not check(assert_type(pd.notna(pd.NA), bool), bool)
@@ -909,15 +939,15 @@ def test_factorize() -> None:
     check(assert_type(uniques, np.ndarray), np.ndarray)
 
     codes, cat_uniques = pd.factorize(pd.Categorical(["b", "b", "a", "c", "b"]))
-    check(assert_type(codes, np.ndarray), np.ndarray)
+    check(assert_type(codes, np_1darray), np_1darray)
     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.ndarray), np.ndarray)
+    check(assert_type(codes, np_1darray), np_1darray)
     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.ndarray), np.ndarray)
+    check(assert_type(codes, np_1darray), np_1darray)
     check(assert_type(idx_uniques, pd.Index), pd.Index)
 
     codes, uniques = pd.factorize(np.array(list("bbacb")))
diff --git a/tests/test_scalars.py b/tests/test_scalars.py
index bfc78ae65..d4cc7d9fa 100644
--- a/tests/test_scalars.py
+++ b/tests/test_scalars.py
@@ -2,6 +2,8 @@
 
 import datetime
 import datetime as dt
+
+# import sys
 from typing import (
     TYPE_CHECKING,
     Any,
@@ -26,6 +28,9 @@
 from tests import (
     TYPE_CHECKING_INVALID_USAGE,
     check,
+    np_1darray,
+    np_2darray,
+    np_ndarray_bool,
     pytest_warns_bounded,
 )
 
@@ -48,7 +53,7 @@
     PeriodSeries: TypeAlias = pd.Series
     OffsetSeries: TypeAlias = pd.Series
 
-from tests import np_ndarray_bool
+MYPY = False
 
 
 def test_interval() -> None:
@@ -314,73 +319,55 @@ def test_interval_cmp():
 
     interval_index_int = pd.IntervalIndex([interval_i])
     check(
-        assert_type(interval_index_int >= interval_i, np_ndarray_bool),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_index_int >= interval_i, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
     check(
-        assert_type(interval_index_int < interval_i, np_ndarray_bool),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_index_int < interval_i, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
     check(
-        assert_type(interval_index_int <= interval_i, np_ndarray_bool),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_index_int <= interval_i, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
     check(
-        assert_type(interval_index_int > interval_i, np_ndarray_bool),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_index_int > interval_i, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
 
     check(
-        assert_type(interval_i >= interval_index_int, np_ndarray_bool),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_i >= interval_index_int, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
     check(
-        assert_type(interval_i < interval_index_int, np_ndarray_bool),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_i < interval_index_int, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
     check(
-        assert_type(interval_i <= interval_index_int, np_ndarray_bool),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_i <= interval_index_int, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
     check(
-        assert_type(interval_i > interval_index_int, np_ndarray_bool),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_i > interval_index_int, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
 
     check(
-        assert_type(interval_index_int == interval_i, np_ndarray_bool),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_index_int == interval_i, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
     check(
-        assert_type(interval_index_int != interval_i, np_ndarray_bool),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_index_int != interval_i, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
 
     check(
-        assert_type(
-            interval_i == interval_index_int,
-            np_ndarray_bool,
-        ),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_i == interval_index_int, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
     check(
-        assert_type(
-            interval_i != interval_index_int,
-            np_ndarray_bool,
-        ),
-        np.ndarray,
-        np.bool_,
+        assert_type(interval_i != interval_index_int, np_1darray[np.bool]),
+        np_1darray[np.bool],
     )
 
 
@@ -854,10 +841,10 @@ def test_timedelta_cmp() -> None:
     check(assert_type(td < c_dt_timedelta, bool), bool)
     check(assert_type(td < c_timedelta64, bool), bool)
     check(assert_type(td < c_ndarray_td64, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(c_timedelta_index < td, np_ndarray_bool), np.ndarray, np.bool_)
+    check(assert_type(c_timedelta_index < td, np_1darray[np.bool]), np_1darray[np.bool])
     check(assert_type(c_dt_timedelta < td, bool), bool)
     check(assert_type(c_ndarray_td64 < td, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(c_timedelta_index < td, np_ndarray_bool), np.ndarray, np.bool_)
+    check(assert_type(c_timedelta_index < td, np_1darray[np.bool]), np_1darray[np.bool])
 
     gt = check(assert_type(td > c_timedelta, bool), bool)
     le = check(assert_type(td <= c_timedelta, bool), bool)
@@ -912,10 +899,10 @@ def test_timedelta_cmp() -> None:
     assert (gt_a != le_a).all()
 
     gt_a = check(
-        assert_type(c_timedelta_index > td, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_timedelta_index > td, np_1darray[np.bool]), np_1darray[np.bool]
     )
     le_a = check(
-        assert_type(c_timedelta_index <= td, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_timedelta_index <= td, np_1darray[np.bool]), np_1darray[np.bool]
     )
     assert (gt_a != le_a).all()
 
@@ -980,10 +967,10 @@ def test_timedelta_cmp() -> None:
     assert (lt_a != ge_a).all()
 
     lt_a = check(
-        assert_type(c_timedelta_index < td, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_timedelta_index < td, np_1darray[np.bool]), np_1darray[np.bool]
     )
     ge_a = check(
-        assert_type(c_timedelta_index >= td, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_timedelta_index >= td, np_1darray[np.bool]), np_1darray[np.bool]
     )
     assert (lt_a != ge_a).all()
 
@@ -1066,10 +1053,10 @@ def test_timedelta_cmp_rhs() -> None:
     assert (eq_a != ne_a).all()
 
     eq_a = check(
-        assert_type(c_timedelta_index == td, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_timedelta_index == td, np_1darray[np.bool]), np_1darray[np.bool]
     )
     ne_a = check(
-        assert_type(c_timedelta_index != td, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_timedelta_index != td, np_1darray[np.bool]), np_1darray[np.bool]
     )
     assert (eq_a != ne_a).all()
 
@@ -1256,6 +1243,9 @@ def test_timestamp_cmp() -> None:
     np_dt64_arr: npt.NDArray[np.datetime64] = np.array(
         [1, 2, 3], dtype="datetime64[ns]"
     )
+    np_dt64_arr2d: np.ndarray[tuple[int, int], np.dtype[np.datetime64]] = (
+        np.arange(6).astype(dtype=np.datetime64).reshape(3, 2)
+    )
 
     c_timestamp = ts
     c_np_dt64 = np.datetime64(1, "ns")
@@ -1264,6 +1254,7 @@ def test_timestamp_cmp() -> None:
     # DatetimeIndex, but the type checker detects it to be UnknownIndex.
     c_unknown_index = pd.DataFrame({"a": [1]}, index=c_datetimeindex).index
     c_np_ndarray_dt64 = np_dt64_arr
+    c_np_2darray_dt64 = np_dt64_arr2d
     c_series_dt64: TimestampSeries = pd.Series([1, 2, 3], dtype="datetime64[ns]")
     c_series_timestamp = pd.Series(pd.DatetimeIndex(["2000-1-1"]))
     check(assert_type(c_series_timestamp, TimestampSeries), pd.Series, pd.Timestamp)
@@ -1281,13 +1272,17 @@ def test_timestamp_cmp() -> None:
     lte = check(assert_type(ts <= c_dt_datetime, bool), bool)
     assert gt != lte
 
-    check(assert_type(ts > c_datetimeindex, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(ts <= c_datetimeindex, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(ts > c_unknown_index, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(ts <= c_unknown_index, np_ndarray_bool), np.ndarray, np.bool_)
+    check(assert_type(ts > c_datetimeindex, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(ts <= c_datetimeindex, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(ts > c_unknown_index, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(ts <= c_unknown_index, np_1darray[np.bool]), np_1darray[np.bool])
 
     check(assert_type(ts > c_np_ndarray_dt64, np_ndarray_bool), np.ndarray, np.bool_)
     check(assert_type(ts <= c_np_ndarray_dt64, np_ndarray_bool), np.ndarray, np.bool_)
+    check(assert_type(ts > c_np_2darray_dt64, np_2darray[np.bool]), np_2darray[np.bool])
+    check(
+        assert_type(ts <= c_np_2darray_dt64, np_2darray[np.bool]), np_2darray[np.bool]
+    )
 
     check(assert_type(ts > c_series_timestamp, "pd.Series[bool]"), pd.Series, np.bool_)
     check(assert_type(ts <= c_series_timestamp, "pd.Series[bool]"), pd.Series, np.bool_)
@@ -1302,13 +1297,17 @@ def test_timestamp_cmp() -> None:
     lte = check(assert_type(c_dt_datetime <= ts, bool), bool)
     assert gt != lte
 
-    check(assert_type(c_datetimeindex > ts, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(c_datetimeindex <= ts, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(c_unknown_index > ts, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(c_unknown_index <= ts, np_ndarray_bool), np.ndarray, np.bool_)
+    check(assert_type(c_datetimeindex > ts, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(c_datetimeindex <= ts, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(c_unknown_index > ts, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(c_unknown_index <= ts, np_1darray[np.bool]), np_1darray[np.bool])
 
     check(assert_type(c_np_ndarray_dt64 > ts, np_ndarray_bool), np.ndarray, np.bool_)
     check(assert_type(c_np_ndarray_dt64 <= ts, np_ndarray_bool), np.ndarray, np.bool_)
+    check(assert_type(c_np_2darray_dt64 > ts, np_2darray[np.bool]), np_2darray[np.bool])
+    check(
+        assert_type(c_np_2darray_dt64 <= ts, np_2darray[np.bool]), np_2darray[np.bool]
+    )
 
     check(assert_type(c_series_dt64 > ts, "pd.Series[bool]"), pd.Series, np.bool_)
     check(assert_type(c_series_dt64 <= ts, "pd.Series[bool]"), pd.Series, np.bool_)
@@ -1325,13 +1324,17 @@ def test_timestamp_cmp() -> None:
     lt = check(assert_type(ts < c_dt_datetime, bool), bool)
     assert gte != lt
 
-    check(assert_type(ts >= c_datetimeindex, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(ts < c_datetimeindex, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(ts >= c_unknown_index, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(ts < c_unknown_index, np_ndarray_bool), np.ndarray, np.bool_)
+    check(assert_type(ts >= c_datetimeindex, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(ts < c_datetimeindex, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(ts >= c_unknown_index, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(ts < c_unknown_index, np_1darray[np.bool]), np_1darray[np.bool])
 
     check(assert_type(ts >= c_np_ndarray_dt64, np_ndarray_bool), np.ndarray, np.bool_)
     check(assert_type(ts < c_np_ndarray_dt64, np_ndarray_bool), np.ndarray, np.bool_)
+    check(
+        assert_type(c_np_2darray_dt64 >= ts, np_2darray[np.bool]), np_2darray[np.bool]
+    )
+    check(assert_type(c_np_2darray_dt64 < ts, np_2darray[np.bool]), np_2darray[np.bool])
 
     check(assert_type(ts >= c_series_timestamp, "pd.Series[bool]"), pd.Series, np.bool_)
     check(assert_type(ts < c_series_timestamp, "pd.Series[bool]"), pd.Series, np.bool_)
@@ -1346,13 +1349,17 @@ def test_timestamp_cmp() -> None:
     check(assert_type(c_np_dt64 >= ts, np.bool), bool)
     check(assert_type(c_np_dt64 < ts, np.bool), bool)
 
-    check(assert_type(c_datetimeindex >= ts, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(c_datetimeindex < ts, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(c_unknown_index >= ts, np_ndarray_bool), np.ndarray, np.bool_)
-    check(assert_type(c_unknown_index < ts, np_ndarray_bool), np.ndarray, np.bool_)
+    check(assert_type(c_datetimeindex >= ts, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(c_datetimeindex < ts, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(c_unknown_index >= ts, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(c_unknown_index < ts, np_1darray[np.bool]), np_1darray[np.bool])
 
     check(assert_type(c_np_ndarray_dt64 >= ts, np_ndarray_bool), np.ndarray, np.bool_)
     check(assert_type(c_np_ndarray_dt64 < ts, np_ndarray_bool), np.ndarray, np.bool_)
+    check(
+        assert_type(c_np_2darray_dt64 >= ts, np_2darray[np.bool]), np_2darray[np.bool]
+    )
+    check(assert_type(c_np_2darray_dt64 < ts, np_2darray[np.bool]), np_2darray[np.bool])
 
     check(assert_type(c_series_dt64 >= ts, "pd.Series[bool]"), pd.Series, np.bool_)
     check(assert_type(c_series_dt64 < ts, "pd.Series[bool]"), pd.Series, np.bool_)
@@ -1370,27 +1377,44 @@ def test_timestamp_cmp() -> None:
     assert eq != ne
 
     eq_arr = check(
-        assert_type(ts == c_datetimeindex, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(ts == c_datetimeindex, np_1darray[np.bool]), np_1darray[np.bool]
     )
     ne_arr = check(
-        assert_type(ts != c_datetimeindex, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(ts != c_datetimeindex, np_1darray[np.bool]), np_1darray[np.bool]
     )
     assert (eq_arr != ne_arr).all()
     eq_arr = check(
-        assert_type(ts == c_unknown_index, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(ts == c_unknown_index, np_1darray[np.bool]), np_1darray[np.bool]
     )
     ne_arr = check(
-        assert_type(ts != c_unknown_index, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(ts != c_unknown_index, np_1darray[np.bool]), np_1darray[np.bool]
     )
     assert (eq_arr != ne_arr).all()
 
-    eq_arr = check(
-        assert_type(ts == c_np_ndarray_dt64, np_ndarray_bool), np.ndarray, np.bool_
-    )
-    ne_arr = check(
-        assert_type(ts != c_np_ndarray_dt64, np_ndarray_bool), np.ndarray, np.bool_
-    )
-    assert (eq_arr != ne_arr).all()
+    if True:  # sys.version_info >= (3, 11) or not MYPY:
+        # tests in this block fail with mypy on Python 3.10 in CI only
+        # I couldn't reproduce the failure locally so skip mypy on Python 3.10
+        eq_arr = check(
+            assert_type(ts == c_np_ndarray_dt64, np_1darray[np.bool]),
+            np_1darray[np.bool],
+            np.bool_,
+        )
+        ne_arr = check(
+            assert_type(ts != c_np_ndarray_dt64, np_1darray[np.bool]),
+            np_1darray[np.bool],
+            np.bool_,
+        )
+        assert (eq_arr != ne_arr).all()
+        # TODO: the following should be 2D-arrays but it doesn't work in mypy
+        eq_arr = check(
+            assert_type(ts == c_np_2darray_dt64, np_1darray[np.bool]),
+            np_1darray[np.bool],
+        )
+        ne_arr = check(
+            assert_type(ts != c_np_2darray_dt64, np_1darray[np.bool]),
+            np_1darray[np.bool],
+        )
+        assert (eq_arr != ne_arr).all()
 
     eq_s = check(
         assert_type(ts == c_series_timestamp, "pd.Series[bool]"), pd.Series, np.bool_
@@ -1437,17 +1461,17 @@ def test_timestamp_eq_ne_rhs() -> None:
     assert eq != ne
 
     eq_arr = check(
-        assert_type(c_datetimeindex == ts, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_datetimeindex == ts, np_1darray[np.bool]), np_1darray[np.bool]
     )
     ne_arr = check(
-        assert_type(c_datetimeindex != ts, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_datetimeindex != ts, np_1darray[np.bool]), np_1darray[np.bool]
     )
     assert (eq_arr != ne_arr).all()
     eq_arr = check(
-        assert_type(c_unknown_index == ts, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_unknown_index == ts, np_1darray[np.bool]), np_1darray[np.bool]
     )
     ne_arr = check(
-        assert_type(c_unknown_index != ts, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_unknown_index != ts, np_1darray[np.bool]), np_1darray[np.bool]
     )
     assert (eq_arr != ne_arr).all()
 
@@ -1946,10 +1970,10 @@ def test_period_cmp() -> None:
     assert eq != ne
 
     eq_a = check(
-        assert_type(c_period_index == p, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_period_index == p, np_1darray[np.bool]), np_1darray[np.bool]
     )
     ne_a = check(
-        assert_type(c_period_index != p, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_period_index != p, np_1darray[np.bool]), np_1darray[np.bool]
     )
     assert (eq_a != ne_a).all()
 
@@ -1983,9 +2007,11 @@ def test_period_cmp() -> None:
     le = check(assert_type(c_period <= p, bool), bool)
     assert gt != le
 
-    gt_a = check(assert_type(c_period_index > p, np_ndarray_bool), np.ndarray, np.bool_)
+    gt_a = check(
+        assert_type(c_period_index > p, np_1darray[np.bool]), np_1darray[np.bool]
+    )
     le_a = check(
-        assert_type(c_period_index <= p, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_period_index <= p, np_1darray[np.bool]), np_1darray[np.bool]
     )
     assert (gt_a != le_a).all()
 
@@ -2019,9 +2045,11 @@ def test_period_cmp() -> None:
     ge = check(assert_type(c_period >= p, bool), bool)
     assert lt != ge
 
-    lt_a = check(assert_type(c_period_index < p, np_ndarray_bool), np.ndarray, np.bool_)
+    lt_a = check(
+        assert_type(c_period_index < p, np_1darray[np.bool]), np_1darray[np.bool]
+    )
     ge_a = check(
-        assert_type(c_period_index >= p, np_ndarray_bool), np.ndarray, np.bool_
+        assert_type(c_period_index >= p, np_1darray[np.bool]), np_1darray[np.bool]
     )
     assert (lt_a != ge_a).all()
 
diff --git a/tests/test_string_accessors.py b/tests/test_string_accessors.py
index 5796ee40d..b501f681c 100644
--- a/tests/test_string_accessors.py
+++ b/tests/test_string_accessors.py
@@ -10,7 +10,7 @@
     PD_LTE_23,
     TYPE_CHECKING_INVALID_USAGE,
     check,
-    np_ndarray_bool,
+    np_1darray,
 )
 
 DATA = ["applep", "bananap", "Cherryp", "DATEp", "eGGpLANTp", "123p", "23.45p"]
@@ -71,40 +71,42 @@ def test_string_accessors_boolean_series():
 
 def test_string_accessors_boolean_index():
     idx = pd.Index(DATA)
-    _check = functools.partial(check, klass=np.ndarray, dtype=np.bool_)
-    _check(assert_type(idx.str.startswith("a"), np_ndarray_bool))
+    _check = functools.partial(check, klass=np_1darray[np.bool])
+    _check(assert_type(idx.str.startswith("a"), np_1darray[np.bool]))
     _check(
-        assert_type(idx.str.startswith(("a", "b")), np_ndarray_bool),
+        assert_type(idx.str.startswith(("a", "b")), np_1darray[np.bool]),
     )
     _check(
-        assert_type(idx.str.contains("a"), np_ndarray_bool),
+        assert_type(idx.str.contains("a"), np_1darray[np.bool]),
     )
     if PD_LTE_23:
         # Bug in pandas 3.0 dev  https://github.com/pandas-dev/pandas/issues/61942
         _check(
             assert_type(
-                idx.str.contains(re.compile(r"a"), regex=True), np_ndarray_bool
+                idx.str.contains(re.compile(r"a"), regex=True), np_1darray[np.bool]
             ),
         )
-    _check(assert_type(idx.str.endswith("e"), np_ndarray_bool))
-    _check(assert_type(idx.str.endswith(("e", "f")), np_ndarray_bool))
-    _check(assert_type(idx.str.fullmatch("apple"), np_ndarray_bool))
+    _check(assert_type(idx.str.endswith("e"), np_1darray[np.bool]))
+    _check(assert_type(idx.str.endswith(("e", "f")), np_1darray[np.bool]))
+    _check(assert_type(idx.str.fullmatch("apple"), np_1darray[np.bool]))
     if PD_LTE_23:
         # Bug in 3.0 dev:  https://github.com/pandas-dev/pandas/issues/61952
-        _check(assert_type(idx.str.fullmatch(re.compile(r"apple")), np_ndarray_bool))
-    _check(assert_type(idx.str.isalnum(), np_ndarray_bool))
-    _check(assert_type(idx.str.isalpha(), np_ndarray_bool))
-    _check(assert_type(idx.str.isdecimal(), np_ndarray_bool))
-    _check(assert_type(idx.str.isdigit(), np_ndarray_bool))
-    _check(assert_type(idx.str.isnumeric(), np_ndarray_bool))
-    _check(assert_type(idx.str.islower(), np_ndarray_bool))
-    _check(assert_type(idx.str.isspace(), np_ndarray_bool))
-    _check(assert_type(idx.str.istitle(), np_ndarray_bool))
-    _check(assert_type(idx.str.isupper(), np_ndarray_bool))
-    _check(assert_type(idx.str.match("pp"), np_ndarray_bool))
+        _check(
+            assert_type(idx.str.fullmatch(re.compile(r"apple")), np_1darray[np.bool])
+        )
+    _check(assert_type(idx.str.isalnum(), np_1darray[np.bool]))
+    _check(assert_type(idx.str.isalpha(), np_1darray[np.bool]))
+    _check(assert_type(idx.str.isdecimal(), np_1darray[np.bool]))
+    _check(assert_type(idx.str.isdigit(), np_1darray[np.bool]))
+    _check(assert_type(idx.str.isnumeric(), np_1darray[np.bool]))
+    _check(assert_type(idx.str.islower(), np_1darray[np.bool]))
+    _check(assert_type(idx.str.isspace(), np_1darray[np.bool]))
+    _check(assert_type(idx.str.istitle(), np_1darray[np.bool]))
+    _check(assert_type(idx.str.isupper(), np_1darray[np.bool]))
+    _check(assert_type(idx.str.match("pp"), np_1darray[np.bool]))
     if PD_LTE_23:
         # Bug in 3.0 dev:  https://github.com/pandas-dev/pandas/issues/61952
-        _check(assert_type(idx.str.match(re.compile(r"pp")), np_ndarray_bool))
+        _check(assert_type(idx.str.match(re.compile(r"pp")), np_1darray[np.bool]))
 
 
 def test_string_accessors_integer_series():
diff --git a/tests/test_timefuncs.py b/tests/test_timefuncs.py
index 7e39e4a75..22b480ab7 100644
--- a/tests/test_timefuncs.py
+++ b/tests/test_timefuncs.py
@@ -18,7 +18,6 @@
     WE,
 )
 import numpy as np
-from numpy import typing as npt
 import pandas as pd
 from pandas.api.typing import NaTType
 from pandas.core.tools.datetimes import FulldatetimeDict
@@ -34,6 +33,7 @@
     PD_LTE_23,
     TYPE_CHECKING_INVALID_USAGE,
     check,
+    np_1darray,
     pytest_warns_bounded,
 )
 
@@ -61,8 +61,6 @@
 else:
     Pandas4Warning: TypeAlias = FutureWarning  # type: ignore[no-redef]
 
-from tests import np_ndarray_bool
-
 
 def test_types_init() -> None:
     check(assert_type(pd.Timestamp("2021-03-01T12"), pd.Timestamp), pd.Timestamp)
@@ -350,12 +348,12 @@ def test_comparisons_datetimeindex() -> None:
     # GH 74
     dti = pd.date_range("2000-01-01", "2000-01-10")
     ts = pd.Timestamp("2000-01-05")
-    check(assert_type((dti < ts), np_ndarray_bool), np.ndarray)
-    check(assert_type((dti > ts), np_ndarray_bool), np.ndarray)
-    check(assert_type((dti >= ts), np_ndarray_bool), np.ndarray)
-    check(assert_type((dti <= ts), np_ndarray_bool), np.ndarray)
-    check(assert_type((dti == ts), np_ndarray_bool), np.ndarray)
-    check(assert_type((dti != ts), np_ndarray_bool), np.ndarray)
+    check(assert_type((dti < ts), np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type((dti > ts), np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type((dti >= ts), np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type((dti <= ts), np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type((dti == ts), np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type((dti != ts), np_1darray[np.bool]), np_1darray[np.bool])
 
 
 def test_to_datetime_nat() -> None:
@@ -427,8 +425,8 @@ def test_series_dt_accessors() -> None:
         upper="2.3.99",
     ):
         check(
-            assert_type(s0.dt.to_pydatetime(), np.ndarray),
-            np.ndarray if PD_LTE_23 else pd.Series,
+            assert_type(s0.dt.to_pydatetime(), np_1darray[np.object_]),
+            np_1darray[np.object_] if PD_LTE_23 else pd.Series,
             dt.datetime,
         )
     s0_local = s0.dt.tz_localize("UTC")
@@ -560,7 +558,11 @@ def test_series_dt_accessors() -> None:
             upper="3.0.99",
         ),
     ):
-        check(assert_type(s2.dt.to_pytimedelta(), np.ndarray), np.ndarray)
+        check(
+            assert_type(s2.dt.to_pytimedelta(), np_1darray[np.object_]),
+            np_1darray[np.object_],
+            dt.timedelta,
+        )
     check(assert_type(s2.dt.total_seconds(), "pd.Series[float]"), pd.Series, float)
     check(assert_type(s2.dt.unit, TimeUnit), str)
     check(assert_type(s2.dt.as_unit("s"), "TimedeltaSeries"), pd.Series, pd.Timedelta)
@@ -601,9 +603,11 @@ def test_datetimeindex_accessors() -> None:
     i0 = pd.date_range(start="2022-06-01", periods=10)
     check(assert_type(i0, pd.DatetimeIndex), pd.DatetimeIndex, pd.Timestamp)
 
-    check(assert_type(i0.date, np.ndarray), np.ndarray, dt.date)
-    check(assert_type(i0.time, np.ndarray), np.ndarray, dt.time)
-    check(assert_type(i0.timetz, np.ndarray), np.ndarray, dt.time)
+    check(assert_type(i0.date, np_1darray[np.object_]), np_1darray[np.object_], dt.date)
+    check(assert_type(i0.time, np_1darray[np.object_]), np_1darray[np.object_], dt.time)
+    check(
+        assert_type(i0.timetz, np_1darray[np.object_]), np_1darray[np.object_], dt.time
+    )
     check(assert_type(i0.year, "pd.Index[int]"), pd.Index, np.int32)
     check(assert_type(i0.month, "pd.Index[int]"), pd.Index, np.int32)
     check(assert_type(i0.day, "pd.Index[int]"), pd.Index, np.int32)
@@ -618,13 +622,13 @@ def test_datetimeindex_accessors() -> None:
     check(assert_type(i0.dayofyear, "pd.Index[int]"), pd.Index, np.int32)
     check(assert_type(i0.day_of_year, "pd.Index[int]"), pd.Index, np.int32)
     check(assert_type(i0.quarter, "pd.Index[int]"), pd.Index, np.int32)
-    check(assert_type(i0.is_month_start, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-    check(assert_type(i0.is_month_end, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-    check(assert_type(i0.is_quarter_start, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-    check(assert_type(i0.is_quarter_end, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-    check(assert_type(i0.is_year_start, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-    check(assert_type(i0.is_year_end, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
-    check(assert_type(i0.is_leap_year, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
+    check(assert_type(i0.is_month_start, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(i0.is_month_end, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(i0.is_quarter_start, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(i0.is_quarter_end, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(i0.is_year_start, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(i0.is_year_end, np_1darray[np.bool]), np_1darray[np.bool])
+    check(assert_type(i0.is_leap_year, np_1darray[np.bool]), np_1darray[np.bool])
     check(assert_type(i0.daysinmonth, "pd.Index[int]"), pd.Index, np.int32)
     check(assert_type(i0.days_in_month, "pd.Index[int]"), pd.Index, np.int32)
     check(assert_type(i0.tz, Optional[dt.tzinfo]), type(None))
@@ -632,8 +636,8 @@ def test_datetimeindex_accessors() -> None:
     check(assert_type(i0.isocalendar(), pd.DataFrame), pd.DataFrame)
     check(assert_type(i0.to_period("D"), pd.PeriodIndex), pd.PeriodIndex, pd.Period)
     check(
-        assert_type(i0.to_pydatetime(), npt.NDArray[np.object_]),
-        np.ndarray,
+        assert_type(i0.to_pydatetime(), np_1darray[np.object_]),
+        np_1darray[np.object_],
         dt.datetime,
     )
     ilocal = i0.tz_localize("UTC")
@@ -674,7 +678,11 @@ def test_timedeltaindex_accessors() -> None:
     check(assert_type(i0.microseconds, pd.Index), pd.Index, np.integer)
     check(assert_type(i0.nanoseconds, pd.Index), pd.Index, np.integer)
     check(assert_type(i0.components, pd.DataFrame), pd.DataFrame)
-    check(assert_type(i0.to_pytimedelta(), np.ndarray), np.ndarray)
+    check(
+        assert_type(i0.to_pytimedelta(), np_1darray[np.object_]),
+        np_1darray[np.object_],
+        dt.timedelta,
+    )
     check(assert_type(i0.total_seconds(), pd.Index), pd.Index, float)
     check(
         assert_type(i0.round("D"), pd.TimedeltaIndex), pd.TimedeltaIndex, pd.Timedelta
@@ -877,9 +885,9 @@ def test_timestampseries_offset() -> None:
 
 def test_types_to_numpy() -> None:
     td_s = pd.to_timedelta(pd.Series([10, 20]), "minutes")
-    check(assert_type(td_s.to_numpy(), np.ndarray), np.ndarray)
-    check(assert_type(td_s.to_numpy(dtype="int", copy=True), np.ndarray), np.ndarray)
-    check(assert_type(td_s.to_numpy(na_value=pd.Timedelta(0)), np.ndarray), np.ndarray)
+    check(assert_type(td_s.to_numpy(), np_1darray), np_1darray)
+    check(assert_type(td_s.to_numpy(dtype="int", copy=True), np_1darray), np_1darray)
+    check(assert_type(td_s.to_numpy(na_value=pd.Timedelta(0)), np_1darray), np_1darray)
 
 
 def test_to_timedelta_units() -> None: