diff --git a/pandas/_typing.py b/pandas/_typing.py
index 5f8ea79046235..9c20eb12dc7fc 100644
--- a/pandas/_typing.py
+++ b/pandas/_typing.py
@@ -101,11 +101,11 @@
 ]
 Timezone = Union[str, tzinfo]
 
-# FrameOrSeries is stricter and ensures that the same subclass of NDFrame always is
-# used. E.g. `def func(a: FrameOrSeries) -> FrameOrSeries: ...` means that if a
+# NDFrameT is stricter and ensures that the same subclass of NDFrame always is
+# used. E.g. `def func(a: NDFrameT) -> NDFrameT: ...` means that if a
 # Series is passed into a function, a Series is always returned and if a DataFrame is
 # passed in, a DataFrame is always returned.
-FrameOrSeries = TypeVar("FrameOrSeries", bound="NDFrame")
+NDFrameT = TypeVar("NDFrameT", bound="NDFrame")
 
 Axis = Union[str, int]
 IndexLabel = Union[Hashable, Sequence[Hashable]]
diff --git a/pandas/core/apply.py b/pandas/core/apply.py
index 7dd8b54c0cabf..99df6d256bc75 100644
--- a/pandas/core/apply.py
+++ b/pandas/core/apply.py
@@ -30,7 +30,7 @@
     AggFuncTypeDict,
     AggObjType,
     Axis,
-    FrameOrSeries,
+    NDFrameT,
 )
 from pandas.util._decorators import cache_readonly
 from pandas.util._exceptions import find_stack_level
@@ -1120,7 +1120,7 @@ def apply_standard(self) -> DataFrame | Series:
 class GroupByApply(Apply):
     def __init__(
         self,
-        obj: GroupBy[FrameOrSeries],
+        obj: GroupBy[NDFrameT],
         func: AggFuncType,
         args,
         kwargs,
diff --git a/pandas/core/base.py b/pandas/core/base.py
index 790daa7e42b39..376360cfa392d 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -22,8 +22,8 @@
 from pandas._typing import (
     ArrayLike,
     DtypeObj,
-    FrameOrSeries,
     IndexLabel,
+    NDFrameT,
     Shape,
     npt,
 )
@@ -181,13 +181,13 @@ class SpecificationError(Exception):
     pass
 
 
-class SelectionMixin(Generic[FrameOrSeries]):
+class SelectionMixin(Generic[NDFrameT]):
     """
     mixin implementing the selection & aggregation interface on a group-like
     object sub-classes need to define: obj, exclusions
     """
 
-    obj: FrameOrSeries
+    obj: NDFrameT
     _selection: IndexLabel | None = None
     exclusions: frozenset[Hashable]
     _internal_names = ["_cache", "__setstate__"]
diff --git a/pandas/core/computation/align.py b/pandas/core/computation/align.py
index 148b37cafbf78..a4bd0270f9451 100644
--- a/pandas/core/computation/align.py
+++ b/pandas/core/computation/align.py
@@ -15,7 +15,6 @@
 
 import numpy as np
 
-from pandas._typing import FrameOrSeries
 from pandas.errors import PerformanceWarning
 
 from pandas.core.dtypes.generic import (
@@ -28,14 +27,15 @@
 from pandas.core.computation.common import result_type_many
 
 if TYPE_CHECKING:
+    from pandas.core.generic import NDFrame
     from pandas.core.indexes.api import Index
 
 
 def _align_core_single_unary_op(
     term,
-) -> tuple[partial | type[FrameOrSeries], dict[str, Index] | None]:
+) -> tuple[partial | type[NDFrame], dict[str, Index] | None]:
 
-    typ: partial | type[FrameOrSeries]
+    typ: partial | type[NDFrame]
     axes: dict[str, Index] | None = None
 
     if isinstance(term.value, np.ndarray):
@@ -49,7 +49,7 @@ def _align_core_single_unary_op(
 
 
 def _zip_axes_from_type(
-    typ: type[FrameOrSeries], new_axes: Sequence[Index]
+    typ: type[NDFrame], new_axes: Sequence[Index]
 ) -> dict[str, Index]:
     return {name: new_axes[i] for i, name in enumerate(typ._AXIS_ORDERS)}
 
diff --git a/pandas/core/describe.py b/pandas/core/describe.py
index fd45da4a3ccc7..2c4a340e8c8ea 100644
--- a/pandas/core/describe.py
+++ b/pandas/core/describe.py
@@ -22,7 +22,7 @@
 import numpy as np
 
 from pandas._libs.tslibs import Timestamp
-from pandas._typing import FrameOrSeries
+from pandas._typing import NDFrameT
 from pandas.util._validators import validate_percentile
 
 from pandas.core.dtypes.common import (
@@ -45,12 +45,12 @@
 
 def describe_ndframe(
     *,
-    obj: FrameOrSeries,
+    obj: NDFrameT,
     include: str | Sequence[str] | None,
     exclude: str | Sequence[str] | None,
     datetime_is_numeric: bool,
     percentiles: Sequence[float] | np.ndarray | None,
-) -> FrameOrSeries:
+) -> NDFrameT:
     """Describe series or dataframe.
 
     Called from pandas.core.generic.NDFrame.describe()
@@ -91,7 +91,7 @@ def describe_ndframe(
         )
 
     result = describer.describe(percentiles=percentiles)
-    return cast(FrameOrSeries, result)
+    return cast(NDFrameT, result)
 
 
 class NDFrameDescriberAbstract(ABC):
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index d770488e9ceb4..91a446dd99334 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -42,12 +42,12 @@
     DtypeArg,
     DtypeObj,
     FilePathOrBuffer,
-    FrameOrSeries,
     IndexKeyFunc,
     IndexLabel,
     JSONSerializable,
     Level,
     Manager,
+    NDFrameT,
     RandomState,
     Renamer,
     StorageOptions,
@@ -297,9 +297,7 @@ def _from_mgr(cls, mgr: Manager):
         object.__setattr__(obj, "_attrs", {})
         return obj
 
-    def _as_manager(
-        self: FrameOrSeries, typ: str, copy: bool_t = True
-    ) -> FrameOrSeries:
+    def _as_manager(self: NDFrameT, typ: str, copy: bool_t = True) -> NDFrameT:
         """
         Private helper function to create a DataFrame with specific manager.
 
@@ -388,11 +386,11 @@ def flags(self) -> Flags:
 
     @final
     def set_flags(
-        self: FrameOrSeries,
+        self: NDFrameT,
         *,
         copy: bool_t = False,
         allows_duplicate_labels: bool_t | None = None,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Return a new object with updated flags.
 
@@ -457,7 +455,7 @@ def _validate_dtype(cls, dtype) -> DtypeObj | None:
     # Construction
 
     @property
-    def _constructor(self: FrameOrSeries) -> type[FrameOrSeries]:
+    def _constructor(self: NDFrameT) -> type[NDFrameT]:
         """
         Used when a manipulation result has the same dimensions as the
         original.
@@ -704,8 +702,8 @@ def size(self) -> int:
 
     @overload
     def set_axis(
-        self: FrameOrSeries, labels, axis: Axis = ..., inplace: Literal[False] = ...
-    ) -> FrameOrSeries:
+        self: NDFrameT, labels, axis: Axis = ..., inplace: Literal[False] = ...
+    ) -> NDFrameT:
         ...
 
     @overload
@@ -718,8 +716,8 @@ def set_axis(self, labels, *, inplace: Literal[True]) -> None:
 
     @overload
     def set_axis(
-        self: FrameOrSeries, labels, axis: Axis = ..., inplace: bool_t = ...
-    ) -> FrameOrSeries | None:
+        self: NDFrameT, labels, axis: Axis = ..., inplace: bool_t = ...
+    ) -> NDFrameT | None:
         ...
 
     def set_axis(self, labels, axis: Axis = 0, inplace: bool_t = False):
@@ -768,7 +766,7 @@ def _set_axis(self, axis: int, labels: Index) -> None:
         self._clear_item_cache()
 
     @final
-    def swapaxes(self: FrameOrSeries, axis1, axis2, copy=True) -> FrameOrSeries:
+    def swapaxes(self: NDFrameT, axis1, axis2, copy=True) -> NDFrameT:
         """
         Interchange axes and swap values axes appropriately.
 
@@ -806,7 +804,7 @@ def swapaxes(self: FrameOrSeries, axis1, axis2, copy=True) -> FrameOrSeries:
 
     @final
     @doc(klass=_shared_doc_kwargs["klass"])
-    def droplevel(self: FrameOrSeries, level, axis=0) -> FrameOrSeries:
+    def droplevel(self: NDFrameT, level, axis=0) -> NDFrameT:
         """
         Return {klass} with requested index / column level(s) removed.
 
@@ -989,7 +987,7 @@ def squeeze(self, axis=None):
     # Rename
 
     def rename(
-        self: FrameOrSeries,
+        self: NDFrameT,
         mapper: Renamer | None = None,
         *,
         index: Renamer | None = None,
@@ -999,7 +997,7 @@ def rename(
         inplace: bool_t = False,
         level: Level | None = None,
         errors: str = "ignore",
-    ) -> FrameOrSeries | None:
+    ) -> NDFrameT | None:
         """
         Alter axes input function or functions. Function / dict values must be
         unique (1-to-1). Labels not contained in a dict / Series will be left
@@ -1592,11 +1590,11 @@ def bool(self):
         self.__nonzero__()
 
     @final
-    def __abs__(self: FrameOrSeries) -> FrameOrSeries:
+    def __abs__(self: NDFrameT) -> NDFrameT:
         return self.abs()
 
     @final
-    def __round__(self: FrameOrSeries, decimals: int = 0) -> FrameOrSeries:
+    def __round__(self: NDFrameT, decimals: int = 0) -> NDFrameT:
         return self.round(decimals)
 
     # -------------------------------------------------------------------------
@@ -3538,8 +3536,8 @@ def _clear_item_cache(self) -> None:
     # Indexing Methods
 
     def take(
-        self: FrameOrSeries, indices, axis=0, is_copy: bool_t | None = None, **kwargs
-    ) -> FrameOrSeries:
+        self: NDFrameT, indices, axis=0, is_copy: bool_t | None = None, **kwargs
+    ) -> NDFrameT:
         """
         Return the elements in the given *positional* indices along an axis.
 
@@ -3636,7 +3634,7 @@ class  max_speed
         )
         return self._constructor(new_data).__finalize__(self, method="take")
 
-    def _take_with_is_copy(self: FrameOrSeries, indices, axis=0) -> FrameOrSeries:
+    def _take_with_is_copy(self: NDFrameT, indices, axis=0) -> NDFrameT:
         """
         Internal version of the `take` method that sets the `_is_copy`
         attribute to keep track of the parent dataframe (using in indexing
@@ -3836,7 +3834,7 @@ class   animal   locomotion
     def __getitem__(self, item):
         raise AbstractMethodError(self)
 
-    def _slice(self: FrameOrSeries, slobj: slice, axis=0) -> FrameOrSeries:
+    def _slice(self: NDFrameT, slobj: slice, axis=0) -> NDFrameT:
         """
         Construct a slice of this container.
 
@@ -4056,13 +4054,13 @@ def _is_view(self) -> bool_t:
 
     @final
     def reindex_like(
-        self: FrameOrSeries,
+        self: NDFrameT,
         other,
         method: str | None = None,
         copy: bool_t = True,
         limit=None,
         tolerance=None,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Return an object with matching indices as other object.
 
@@ -4204,14 +4202,14 @@ def drop(
 
     @final
     def _drop_axis(
-        self: FrameOrSeries,
+        self: NDFrameT,
         labels,
         axis,
         level=None,
         errors: str = "raise",
         consolidate: bool_t = True,
         only_slice: bool_t = False,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Drop labels from specified axis. Used in the ``drop`` method
         internally.
@@ -4307,7 +4305,7 @@ def _update_inplace(self, result, verify_is_copy: bool_t = True) -> None:
         self._maybe_update_cacher(verify_is_copy=verify_is_copy)
 
     @final
-    def add_prefix(self: FrameOrSeries, prefix: str) -> FrameOrSeries:
+    def add_prefix(self: NDFrameT, prefix: str) -> NDFrameT:
         """
         Prefix labels with string `prefix`.
 
@@ -4364,14 +4362,14 @@ def add_prefix(self: FrameOrSeries, prefix: str) -> FrameOrSeries:
         f = functools.partial("{prefix}{}".format, prefix=prefix)
 
         mapper = {self._info_axis_name: f}
-        # error: Incompatible return value type (got "Optional[FrameOrSeries]",
-        # expected "FrameOrSeries")
+        # error: Incompatible return value type (got "Optional[NDFrameT]",
+        # expected "NDFrameT")
         # error: Argument 1 to "rename" of "NDFrame" has incompatible type
         # "**Dict[str, partial[str]]"; expected "Union[str, int, None]"
         return self.rename(**mapper)  # type: ignore[return-value, arg-type]
 
     @final
-    def add_suffix(self: FrameOrSeries, suffix: str) -> FrameOrSeries:
+    def add_suffix(self: NDFrameT, suffix: str) -> NDFrameT:
         """
         Suffix labels with string `suffix`.
 
@@ -4428,8 +4426,8 @@ def add_suffix(self: FrameOrSeries, suffix: str) -> FrameOrSeries:
         f = functools.partial("{}{suffix}".format, suffix=suffix)
 
         mapper = {self._info_axis_name: f}
-        # error: Incompatible return value type (got "Optional[FrameOrSeries]",
-        # expected "FrameOrSeries")
+        # error: Incompatible return value type (got "Optional[NDFrameT]",
+        # expected "NDFrameT")
         # error: Argument 1 to "rename" of "NDFrame" has incompatible type
         # "**Dict[str, partial[str]]"; expected "Union[str, int, None]"
         return self.rename(**mapper)  # type: ignore[return-value, arg-type]
@@ -4642,7 +4640,7 @@ def sort_index(
         optional_labels="",
         optional_axis="",
     )
-    def reindex(self: FrameOrSeries, *args, **kwargs) -> FrameOrSeries:
+    def reindex(self: NDFrameT, *args, **kwargs) -> NDFrameT:
         """
         Conform {klass} to new index with optional filling logic.
 
@@ -4888,8 +4886,8 @@ def reindex(self: FrameOrSeries, *args, **kwargs) -> FrameOrSeries:
         ).__finalize__(self, method="reindex")
 
     def _reindex_axes(
-        self: FrameOrSeries, axes, level, limit, tolerance, method, fill_value, copy
-    ) -> FrameOrSeries:
+        self: NDFrameT, axes, level, limit, tolerance, method, fill_value, copy
+    ) -> NDFrameT:
         """Perform the reindex for all the axes."""
         obj = self
         for a in self._AXIS_ORDERS:
@@ -4928,12 +4926,12 @@ def _reindex_multi(self, axes, copy, fill_value):
 
     @final
     def _reindex_with_indexers(
-        self: FrameOrSeries,
+        self: NDFrameT,
         reindexers,
         fill_value=None,
         copy: bool_t = False,
         allow_dups: bool_t = False,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """allow_dups indicates an internal call here"""
         # reindex doing multiple operations on different axes if indicated
         new_data = self._mgr
@@ -4966,12 +4964,12 @@ def _reindex_with_indexers(
         return self._constructor(new_data).__finalize__(self)
 
     def filter(
-        self: FrameOrSeries,
+        self: NDFrameT,
         items=None,
         like: str | None = None,
         regex: str | None = None,
         axis=None,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Subset the dataframe rows or columns according to the specified index labels.
 
@@ -5069,7 +5067,7 @@ def f(x) -> bool_t:
             raise TypeError("Must pass either `items`, `like`, or `regex`")
 
     @final
-    def head(self: FrameOrSeries, n: int = 5) -> FrameOrSeries:
+    def head(self: NDFrameT, n: int = 5) -> NDFrameT:
         """
         Return the first `n` rows.
 
@@ -5142,7 +5140,7 @@ def head(self: FrameOrSeries, n: int = 5) -> FrameOrSeries:
         return self.iloc[:n]
 
     @final
-    def tail(self: FrameOrSeries, n: int = 5) -> FrameOrSeries:
+    def tail(self: NDFrameT, n: int = 5) -> NDFrameT:
         """
         Return the last `n` rows.
 
@@ -5218,7 +5216,7 @@ def tail(self: FrameOrSeries, n: int = 5) -> FrameOrSeries:
 
     @final
     def sample(
-        self: FrameOrSeries,
+        self: NDFrameT,
         n: int | None = None,
         frac: float | None = None,
         replace: bool_t = False,
@@ -5226,7 +5224,7 @@ def sample(
         random_state: RandomState | None = None,
         axis: Axis | None = None,
         ignore_index: bool_t = False,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Return a random sample of items from an axis of object.
 
@@ -5437,8 +5435,8 @@ def pipe(
 
     @final
     def __finalize__(
-        self: FrameOrSeries, other, method: str | None = None, **kwargs
-    ) -> FrameOrSeries:
+        self: NDFrameT, other, method: str | None = None, **kwargs
+    ) -> NDFrameT:
         """
         Propagate metadata from other to self.
 
@@ -5662,8 +5660,8 @@ def dtypes(self):
         return self._constructor_sliced(data, index=self._info_axis, dtype=np.object_)
 
     def astype(
-        self: FrameOrSeries, dtype, copy: bool_t = True, errors: str = "raise"
-    ) -> FrameOrSeries:
+        self: NDFrameT, dtype, copy: bool_t = True, errors: str = "raise"
+    ) -> NDFrameT:
         """
         Cast a pandas object to a specified dtype ``dtype``.
 
@@ -5826,10 +5824,10 @@ def astype(
         result = concat(results, axis=1, copy=False)
         result.columns = self.columns
         # https://github.com/python/mypy/issues/8354
-        return cast(FrameOrSeries, result)
+        return cast(NDFrameT, result)
 
     @final
-    def copy(self: FrameOrSeries, deep: bool_t = True) -> FrameOrSeries:
+    def copy(self: NDFrameT, deep: bool_t = True) -> NDFrameT:
         """
         Make a copy of this object's indices and data.
 
@@ -5939,11 +5937,11 @@ def copy(self: FrameOrSeries, deep: bool_t = True) -> FrameOrSeries:
         return self._constructor(data).__finalize__(self, method="copy")
 
     @final
-    def __copy__(self: FrameOrSeries, deep: bool_t = True) -> FrameOrSeries:
+    def __copy__(self: NDFrameT, deep: bool_t = True) -> NDFrameT:
         return self.copy(deep=deep)
 
     @final
-    def __deepcopy__(self: FrameOrSeries, memo=None) -> FrameOrSeries:
+    def __deepcopy__(self: NDFrameT, memo=None) -> NDFrameT:
         """
         Parameters
         ----------
@@ -5954,11 +5952,11 @@ def __deepcopy__(self: FrameOrSeries, memo=None) -> FrameOrSeries:
 
     @final
     def _convert(
-        self: FrameOrSeries,
+        self: NDFrameT,
         datetime: bool_t = False,
         numeric: bool_t = False,
         timedelta: bool_t = False,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Attempt to infer better dtype for object columns
 
@@ -5989,7 +5987,7 @@ def _convert(
         ).__finalize__(self)
 
     @final
-    def infer_objects(self: FrameOrSeries) -> FrameOrSeries:
+    def infer_objects(self: NDFrameT) -> NDFrameT:
         """
         Attempt to infer better dtypes for object columns.
 
@@ -6036,13 +6034,13 @@ def infer_objects(self: FrameOrSeries) -> FrameOrSeries:
 
     @final
     def convert_dtypes(
-        self: FrameOrSeries,
+        self: NDFrameT,
         infer_objects: bool_t = True,
         convert_string: bool_t = True,
         convert_integer: bool_t = True,
         convert_boolean: bool_t = True,
         convert_floating: bool_t = True,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Convert columns to best possible dtypes using dtypes supporting ``pd.NA``.
 
@@ -6190,7 +6188,7 @@ def convert_dtypes(
             ]
             if len(results) > 0:
                 # https://github.com/python/mypy/issues/8354
-                return cast(FrameOrSeries, concat(results, axis=1, copy=False))
+                return cast(NDFrameT, concat(results, axis=1, copy=False))
             else:
                 return self.copy()
 
@@ -6199,14 +6197,14 @@ def convert_dtypes(
 
     @doc(**_shared_doc_kwargs)
     def fillna(
-        self: FrameOrSeries,
+        self: NDFrameT,
         value=None,
         method=None,
         axis=None,
         inplace: bool_t = False,
         limit=None,
         downcast=None,
-    ) -> FrameOrSeries | None:
+    ) -> NDFrameT | None:
         """
         Fill NA/NaN values using the specified method.
 
@@ -6412,12 +6410,12 @@ def fillna(
 
     @doc(klass=_shared_doc_kwargs["klass"])
     def ffill(
-        self: FrameOrSeries,
+        self: NDFrameT,
         axis: None | Axis = None,
         inplace: bool_t = False,
         limit: None | int = None,
         downcast=None,
-    ) -> FrameOrSeries | None:
+    ) -> NDFrameT | None:
         """
         Synonym for :meth:`DataFrame.fillna` with ``method='ffill'``.
 
@@ -6434,12 +6432,12 @@ def ffill(
 
     @doc(klass=_shared_doc_kwargs["klass"])
     def bfill(
-        self: FrameOrSeries,
+        self: NDFrameT,
         axis: None | Axis = None,
         inplace: bool_t = False,
         limit: None | int = None,
         downcast=None,
-    ) -> FrameOrSeries | None:
+    ) -> NDFrameT | None:
         """
         Synonym for :meth:`DataFrame.fillna` with ``method='bfill'``.
 
@@ -6638,7 +6636,7 @@ def replace(
             return result.__finalize__(self, method="replace")
 
     def interpolate(
-        self: FrameOrSeries,
+        self: NDFrameT,
         method: str = "linear",
         axis: Axis = 0,
         limit: int | None = None,
@@ -6647,7 +6645,7 @@ def interpolate(
         limit_area: str | None = None,
         downcast: str | None = None,
         **kwargs,
-    ) -> FrameOrSeries | None:
+    ) -> NDFrameT | None:
         """
         Fill NaN values using an interpolation method.
 
@@ -7108,7 +7106,7 @@ def asof(self, where, subset=None):
     # Action Methods
 
     @doc(klass=_shared_doc_kwargs["klass"])
-    def isna(self: FrameOrSeries) -> FrameOrSeries:
+    def isna(self: NDFrameT) -> NDFrameT:
         """
         Detect missing values.
 
@@ -7171,11 +7169,11 @@ def isna(self: FrameOrSeries) -> FrameOrSeries:
         return isna(self).__finalize__(self, method="isna")
 
     @doc(isna, klass=_shared_doc_kwargs["klass"])
-    def isnull(self: FrameOrSeries) -> FrameOrSeries:
+    def isnull(self: NDFrameT) -> NDFrameT:
         return isna(self).__finalize__(self, method="isnull")
 
     @doc(klass=_shared_doc_kwargs["klass"])
-    def notna(self: FrameOrSeries) -> FrameOrSeries:
+    def notna(self: NDFrameT) -> NDFrameT:
         """
         Detect existing (non-missing) values.
 
@@ -7238,7 +7236,7 @@ def notna(self: FrameOrSeries) -> FrameOrSeries:
         return notna(self).__finalize__(self, method="notna")
 
     @doc(notna, klass=_shared_doc_kwargs["klass"])
-    def notnull(self: FrameOrSeries) -> FrameOrSeries:
+    def notnull(self: NDFrameT) -> NDFrameT:
         return notna(self).__finalize__(self, method="notnull")
 
     @final
@@ -7302,14 +7300,14 @@ def _clip_with_one_bound(self, threshold, method, axis, inplace):
         return self.where(subset, threshold, axis=axis, inplace=inplace)
 
     def clip(
-        self: FrameOrSeries,
+        self: NDFrameT,
         lower=None,
         upper=None,
         axis: Axis | None = None,
         inplace: bool_t = False,
         *args,
         **kwargs,
-    ) -> FrameOrSeries | None:
+    ) -> NDFrameT | None:
         """
         Trim values at input threshold(s).
 
@@ -7462,13 +7460,13 @@ def clip(
 
     @doc(**_shared_doc_kwargs)
     def asfreq(
-        self: FrameOrSeries,
+        self: NDFrameT,
         freq,
         method=None,
         how: str | None = None,
         normalize: bool_t = False,
         fill_value=None,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Convert time series to specified frequency.
 
@@ -7586,9 +7584,7 @@ def asfreq(
         )
 
     @final
-    def at_time(
-        self: FrameOrSeries, time, asof: bool_t = False, axis=None
-    ) -> FrameOrSeries:
+    def at_time(self: NDFrameT, time, asof: bool_t = False, axis=None) -> NDFrameT:
         """
         Select values at particular time of day (e.g., 9:30AM).
 
@@ -7644,14 +7640,14 @@ def at_time(
 
     @final
     def between_time(
-        self: FrameOrSeries,
+        self: NDFrameT,
         start_time,
         end_time,
         include_start: bool_t | lib.NoDefault = lib.no_default,
         include_end: bool_t | lib.NoDefault = lib.no_default,
         inclusive: str | None = None,
         axis=None,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Select values between particular times of the day (e.g., 9:00-9:30 AM).
 
@@ -8205,7 +8201,7 @@ def resample(
         )
 
     @final
-    def first(self: FrameOrSeries, offset) -> FrameOrSeries:
+    def first(self: NDFrameT, offset) -> NDFrameT:
         """
         Select initial periods of time series data based on a date offset.
 
@@ -8278,7 +8274,7 @@ def first(self: FrameOrSeries, offset) -> FrameOrSeries:
         return self.loc[:end]
 
     @final
-    def last(self: FrameOrSeries, offset) -> FrameOrSeries:
+    def last(self: NDFrameT, offset) -> NDFrameT:
         """
         Select final periods of time series data based on a date offset.
 
@@ -8343,14 +8339,14 @@ def last(self: FrameOrSeries, offset) -> FrameOrSeries:
 
     @final
     def rank(
-        self: FrameOrSeries,
+        self: NDFrameT,
         axis=0,
         method: str = "average",
         numeric_only: bool_t | None = None,
         na_option: str = "keep",
         ascending: bool_t = True,
         pct: bool_t = False,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Compute numerical data ranks (1 through n) along axis.
 
@@ -9205,8 +9201,8 @@ def mask(
 
     @doc(klass=_shared_doc_kwargs["klass"])
     def shift(
-        self: FrameOrSeries, periods=1, freq=None, axis=0, fill_value=None
-    ) -> FrameOrSeries:
+        self: NDFrameT, periods=1, freq=None, axis=0, fill_value=None
+    ) -> NDFrameT:
         """
         Shift index by desired number of periods with an optional time `freq`.
 
@@ -9350,7 +9346,7 @@ def shift(
         return result.__finalize__(self, method="shift")
 
     @final
-    def slice_shift(self: FrameOrSeries, periods: int = 1, axis=0) -> FrameOrSeries:
+    def slice_shift(self: NDFrameT, periods: int = 1, axis=0) -> NDFrameT:
         """
         Equivalent to `shift` without copying data.
         The shifted data will not include the dropped periods and the
@@ -9399,9 +9395,7 @@ def slice_shift(self: FrameOrSeries, periods: int = 1, axis=0) -> FrameOrSeries:
         return new_obj.__finalize__(self, method="slice_shift")
 
     @final
-    def tshift(
-        self: FrameOrSeries, periods: int = 1, freq=None, axis: Axis = 0
-    ) -> FrameOrSeries:
+    def tshift(self: NDFrameT, periods: int = 1, freq=None, axis: Axis = 0) -> NDFrameT:
         """
         Shift the time index, using the index's frequency if available.
 
@@ -9443,8 +9437,8 @@ def tshift(
         return self.shift(periods, freq, axis)
 
     def truncate(
-        self: FrameOrSeries, before=None, after=None, axis=None, copy: bool_t = True
-    ) -> FrameOrSeries:
+        self: NDFrameT, before=None, after=None, axis=None, copy: bool_t = True
+    ) -> NDFrameT:
         """
         Truncate a Series or DataFrame before and after some index value.
 
@@ -9600,8 +9594,8 @@ def truncate(
 
     @final
     def tz_convert(
-        self: FrameOrSeries, tz, axis=0, level=None, copy: bool_t = True
-    ) -> FrameOrSeries:
+        self: NDFrameT, tz, axis=0, level=None, copy: bool_t = True
+    ) -> NDFrameT:
         """
         Convert tz-aware axis to target time zone.
 
@@ -9658,14 +9652,14 @@ def _tz_convert(ax, tz):
 
     @final
     def tz_localize(
-        self: FrameOrSeries,
+        self: NDFrameT,
         tz,
         axis=0,
         level=None,
         copy: bool_t = True,
         ambiguous="raise",
         nonexistent: str = "raise",
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Localize tz-naive index of a Series or DataFrame to target time zone.
 
@@ -9829,7 +9823,7 @@ def _tz_localize(ax, tz, ambiguous, nonexistent):
     # Numeric Methods
 
     @final
-    def abs(self: FrameOrSeries) -> FrameOrSeries:
+    def abs(self: NDFrameT) -> NDFrameT:
         """
         Return a Series/DataFrame with absolute numeric value of each element.
 
@@ -9897,17 +9891,17 @@ def abs(self: FrameOrSeries) -> FrameOrSeries:
         3    7   40  -50
         """
         # error: Incompatible return value type (got "ndarray[Any, dtype[Any]]",
-        # expected "FrameOrSeries")
+        # expected "NDFrameT")
         return np.abs(self)  # type: ignore[return-value]
 
     @final
     def describe(
-        self: FrameOrSeries,
+        self: NDFrameT,
         percentiles=None,
         include=None,
         exclude=None,
         datetime_is_numeric=False,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Generate descriptive statistics.
 
@@ -10159,13 +10153,13 @@ def describe(
 
     @final
     def pct_change(
-        self: FrameOrSeries,
+        self: NDFrameT,
         periods=1,
         fill_method="pad",
         limit=None,
         freq=None,
         **kwargs,
-    ) -> FrameOrSeries:
+    ) -> NDFrameT:
         """
         Percentage change between the current and a prior element.
 
@@ -10289,7 +10283,7 @@ def pct_change(
             data = _data
 
         shifted = data.shift(periods=periods, freq=freq, axis=axis, **kwargs)
-        # Unsupported left operand type for / ("FrameOrSeries")
+        # Unsupported left operand type for / ("NDFrameT")
         rs = data / shifted - 1  # type: ignore[operator]
         if freq is not None:
             # Shift method is implemented differently when freq is not None
@@ -11829,8 +11823,8 @@ def _doc_params(cls):
 
 
 def _align_as_utc(
-    left: FrameOrSeries, right: FrameOrSeries, join_index: Index | None
-) -> tuple[FrameOrSeries, FrameOrSeries]:
+    left: NDFrameT, right: NDFrameT, join_index: Index | None
+) -> tuple[NDFrameT, NDFrameT]:
     """
     If we are aligning timezone-aware DatetimeIndexes and the timezones
     do not match, convert both to UTC.
diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 37e5440903e5b..c5633b6809676 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -30,7 +30,6 @@
 from pandas._libs import reduction as libreduction
 from pandas._typing import (
     ArrayLike,
-    FrameOrSeries,
     Manager,
     Manager2D,
     SingleManager,
@@ -98,7 +97,7 @@
 ScalarResult = TypeVar("ScalarResult")
 
 
-def generate_property(name: str, klass: type[FrameOrSeries]):
+def generate_property(name: str, klass: type[DataFrame | Series]):
     """
     Create a property for a GroupBy subclass to dispatch to DataFrame/Series.
 
@@ -121,7 +120,9 @@ def prop(self):
     return property(prop)
 
 
-def pin_allowlisted_properties(klass: type[FrameOrSeries], allowlist: frozenset[str]):
+def pin_allowlisted_properties(
+    klass: type[DataFrame | Series], allowlist: frozenset[str]
+):
     """
     Create GroupBy member defs for DataFrame/Series names in a allowlist.
 
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 96448b319203f..89755ec5f7863 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -44,8 +44,8 @@ class providing the base-class of operations.
 import pandas._libs.groupby as libgroupby
 from pandas._typing import (
     ArrayLike,
-    FrameOrSeries,
     IndexLabel,
+    NDFrameT,
     RandomState,
     Scalar,
     T,
@@ -567,7 +567,7 @@ def group_selection_context(groupby: GroupBy) -> Iterator[GroupBy]:
 ]
 
 
-class BaseGroupBy(PandasObject, SelectionMixin[FrameOrSeries]):
+class BaseGroupBy(PandasObject, SelectionMixin[NDFrameT]):
     _group_selection: IndexLabel | None = None
     _apply_allowlist: frozenset[str] = frozenset()
     _hidden_attrs = PandasObject._hidden_attrs | {
@@ -755,7 +755,7 @@ def get_group(self, name, obj=None) -> DataFrame | Series:
         return obj._take_with_is_copy(inds, axis=self.axis)
 
     @final
-    def __iter__(self) -> Iterator[tuple[Hashable, FrameOrSeries]]:
+    def __iter__(self) -> Iterator[tuple[Hashable, NDFrameT]]:
         """
         Groupby iterator.
 
@@ -771,7 +771,7 @@ def __iter__(self) -> Iterator[tuple[Hashable, FrameOrSeries]]:
 OutputFrameOrSeries = TypeVar("OutputFrameOrSeries", bound=NDFrame)
 
 
-class GroupBy(BaseGroupBy[FrameOrSeries]):
+class GroupBy(BaseGroupBy[NDFrameT]):
     """
     Class for grouping and aggregating relational data.
 
@@ -845,7 +845,7 @@ class GroupBy(BaseGroupBy[FrameOrSeries]):
     @final
     def __init__(
         self,
-        obj: FrameOrSeries,
+        obj: NDFrameT,
         keys: _KeysArgType | None = None,
         axis: int = 0,
         level: IndexLabel | None = None,
@@ -1598,7 +1598,7 @@ def _transform(self, func, *args, engine=None, engine_kwargs=None, **kwargs):
             return self._transform_general(func, *args, **kwargs)
 
     @final
-    def _wrap_transform_fast_result(self, result: FrameOrSeries) -> FrameOrSeries:
+    def _wrap_transform_fast_result(self, result: NDFrameT) -> NDFrameT:
         """
         Fast transform path for aggregations.
         """
@@ -2061,7 +2061,7 @@ def max(self, numeric_only: bool = False, min_count: int = -1):
     @final
     @doc(_groupby_agg_method_template, fname="first", no=False, mc=-1)
     def first(self, numeric_only: bool = False, min_count: int = -1):
-        def first_compat(obj: FrameOrSeries, axis: int = 0):
+        def first_compat(obj: NDFrameT, axis: int = 0):
             def first(x: Series):
                 """Helper function for first item that isn't NA."""
                 arr = x.array[notna(x.array)]
@@ -2086,7 +2086,7 @@ def first(x: Series):
     @final
     @doc(_groupby_agg_method_template, fname="last", no=False, mc=-1)
     def last(self, numeric_only: bool = False, min_count: int = -1):
-        def last_compat(obj: FrameOrSeries, axis: int = 0):
+        def last_compat(obj: NDFrameT, axis: int = 0):
             def last(x: Series):
                 """Helper function for last item that isn't NA."""
                 arr = x.array[notna(x.array)]
diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py
index 22270fdca4b20..02f2024091877 100644
--- a/pandas/core/groupby/grouper.py
+++ b/pandas/core/groupby/grouper.py
@@ -16,7 +16,7 @@
 
 from pandas._typing import (
     ArrayLike,
-    FrameOrSeries,
+    NDFrameT,
 )
 from pandas.errors import InvalidIndexError
 from pandas.util._decorators import cache_readonly
@@ -305,8 +305,8 @@ def ax(self) -> Index:
         return index
 
     def _get_grouper(
-        self, obj: FrameOrSeries, validate: bool = True
-    ) -> tuple[Any, ops.BaseGrouper, FrameOrSeries]:
+        self, obj: NDFrameT, validate: bool = True
+    ) -> tuple[Any, ops.BaseGrouper, NDFrameT]:
         """
         Parameters
         ----------
@@ -319,7 +319,7 @@ def _get_grouper(
         a tuple of binner, grouper, obj (possibly sorted)
         """
         self._set_grouper(obj)
-        # error: Value of type variable "FrameOrSeries" of "get_grouper" cannot be
+        # error: Value of type variable "NDFrameT" of "get_grouper" cannot be
         # "Optional[Any]"
         # error: Incompatible types in assignment (expression has type "BaseGrouper",
         # variable has type "None")
@@ -334,7 +334,7 @@ def _get_grouper(
         )
 
         # error: Incompatible return value type (got "Tuple[None, None, None]",
-        # expected "Tuple[Any, BaseGrouper, FrameOrSeries]")
+        # expected "Tuple[Any, BaseGrouper, NDFrameT]")
         return self.binner, self.grouper, self.obj  # type: ignore[return-value]
 
     @final
@@ -409,7 +409,7 @@ def _set_grouper(self, obj: NDFrame, sort: bool = False):
             obj = obj.take(indexer, axis=self.axis)
 
         # error: Incompatible types in assignment (expression has type
-        # "FrameOrSeries", variable has type "None")
+        # "NDFrameT", variable has type "None")
         self.obj = obj  # type: ignore[assignment]
         self._gpr_index = ax
         return self._gpr_index
@@ -697,7 +697,7 @@ def groups(self) -> dict[Hashable, np.ndarray]:
 
 
 def get_grouper(
-    obj: FrameOrSeries,
+    obj: NDFrameT,
     key=None,
     axis: int = 0,
     level=None,
@@ -706,7 +706,7 @@ def get_grouper(
     mutated: bool = False,
     validate: bool = True,
     dropna: bool = True,
-) -> tuple[ops.BaseGrouper, frozenset[Hashable], FrameOrSeries]:
+) -> tuple[ops.BaseGrouper, frozenset[Hashable], NDFrameT]:
     """
     Create and return a BaseGrouper, which is an internal
     mapping of how to create the grouper indexers.
diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index a7ac2c7a1dba6..07353863cdc0b 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -30,7 +30,7 @@
 from pandas._typing import (
     ArrayLike,
     DtypeObj,
-    FrameOrSeries,
+    NDFrameT,
     Shape,
     npt,
 )
@@ -684,8 +684,8 @@ def nkeys(self) -> int:
         return len(self.groupings)
 
     def get_iterator(
-        self, data: FrameOrSeries, axis: int = 0
-    ) -> Iterator[tuple[Hashable, FrameOrSeries]]:
+        self, data: NDFrameT, axis: int = 0
+    ) -> Iterator[tuple[Hashable, NDFrameT]]:
         """
         Groupby iterator
 
@@ -1166,10 +1166,10 @@ def _is_indexed_like(obj, axes, axis: int) -> bool:
 # Splitting / application
 
 
-class DataSplitter(Generic[FrameOrSeries]):
+class DataSplitter(Generic[NDFrameT]):
     def __init__(
         self,
-        data: FrameOrSeries,
+        data: NDFrameT,
         labels: npt.NDArray[np.intp],
         ngroups: int,
         axis: int = 0,
@@ -1205,7 +1205,7 @@ def __iter__(self):
             yield self._chop(sdata, slice(start, end))
 
     @cache_readonly
-    def sorted_data(self) -> FrameOrSeries:
+    def sorted_data(self) -> NDFrameT:
         return self.data.take(self._sort_idx, axis=self.axis)
 
     def _chop(self, sdata, slice_obj: slice) -> NDFrame:
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 11ed7cb47ea3e..eb839a6e01266 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -25,8 +25,8 @@
     to_offset,
 )
 from pandas._typing import (
-    FrameOrSeries,
     IndexLabel,
+    NDFrameT,
     T,
     TimedeltaConvertibleTypes,
     TimestampConvertibleTypes,
@@ -198,9 +198,9 @@ def __getattr__(self, attr: str):
 
     # error: Signature of "obj" incompatible with supertype "BaseGroupBy"
     @property
-    def obj(self) -> FrameOrSeries:  # type: ignore[override]
+    def obj(self) -> NDFrameT:  # type: ignore[override]
         # error: Incompatible return value type (got "Optional[Any]",
-        # expected "FrameOrSeries")
+        # expected "NDFrameT")
         return self.groupby.obj  # type: ignore[return-value]
 
     @property
@@ -220,7 +220,7 @@ def _from_selection(self) -> bool:
             self.groupby.key is not None or self.groupby.level is not None
         )
 
-    def _convert_obj(self, obj: FrameOrSeries) -> FrameOrSeries:
+    def _convert_obj(self, obj: NDFrameT) -> NDFrameT:
         """
         Provide any conversions for the object in order to correctly handle.
 
@@ -1260,7 +1260,7 @@ def _get_binner_for_time(self):
             return super()._get_binner_for_time()
         return self.groupby._get_period_bins(self.ax)
 
-    def _convert_obj(self, obj: FrameOrSeries) -> FrameOrSeries:
+    def _convert_obj(self, obj: NDFrameT) -> NDFrameT:
         obj = super()._convert_obj(obj)
 
         if self._from_selection:
@@ -1795,12 +1795,12 @@ def _get_period_bins(self, ax: PeriodIndex):
 
 
 def _take_new_index(
-    obj: FrameOrSeries, indexer: npt.NDArray[np.intp], new_index: Index, axis: int = 0
-) -> FrameOrSeries:
+    obj: NDFrameT, indexer: npt.NDArray[np.intp], new_index: Index, axis: int = 0
+) -> NDFrameT:
 
     if isinstance(obj, ABCSeries):
         new_values = algos.take_nd(obj._values, indexer)
-        # error: Incompatible return value type (got "Series", expected "FrameOrSeries")
+        # error: Incompatible return value type (got "Series", expected "NDFrameT")
         return obj._constructor(  # type: ignore[return-value]
             new_values, index=new_index, name=obj.name
         )
@@ -1809,7 +1809,7 @@ def _take_new_index(
             raise NotImplementedError("axis 1 is not supported")
         new_mgr = obj._mgr.reindex_indexer(new_axis=new_index, indexer=indexer, axis=1)
         # error: Incompatible return value type
-        # (got "DataFrame", expected "FrameOrSeries")
+        # (got "DataFrame", expected "NDFrameT")
         return obj._constructor(new_mgr)  # type: ignore[return-value]
     else:
         raise ValueError("'obj' should be either a Series or a DataFrame")
@@ -2039,13 +2039,13 @@ def _adjust_dates_anchored(
 
 
 def asfreq(
-    obj: FrameOrSeries,
+    obj: NDFrameT,
     freq,
     method=None,
     how=None,
     normalize: bool = False,
     fill_value=None,
-) -> FrameOrSeries:
+) -> NDFrameT:
     """
     Utility frequency conversion method for Series/DataFrame.
 
diff --git a/pandas/core/window/ewm.py b/pandas/core/window/ewm.py
index fd53481778001..79102c2bc82ee 100644
--- a/pandas/core/window/ewm.py
+++ b/pandas/core/window/ewm.py
@@ -12,7 +12,6 @@
 import pandas._libs.window.aggregations as window_aggregations
 from pandas._typing import (
     Axis,
-    FrameOrSeries,
     TimedeltaConvertibleTypes,
 )
 
@@ -114,9 +113,9 @@ def _calculate_deltas(
     np.ndarray
         Diff of the times divided by the half-life
     """
-    # error: Item "str" of "Union[str, ndarray, FrameOrSeries, None]" has no
+    # error: Item "str" of "Union[str, ndarray, NDFrameT, None]" has no
     # attribute "view"
-    # error: Item "None" of "Union[str, ndarray, FrameOrSeries, None]" has no
+    # error: Item "None" of "Union[str, ndarray, NDFrameT, None]" has no
     # attribute "view"
     _times = np.asarray(
         times.view(np.int64), dtype=np.float64  # type: ignore[union-attr]
@@ -282,7 +281,7 @@ class ExponentialMovingWindow(BaseWindow):
 
     def __init__(
         self,
-        obj: FrameOrSeries,
+        obj: NDFrame,
         com: float | None = None,
         span: float | None = None,
         halflife: float | TimedeltaConvertibleTypes | None = None,
@@ -291,7 +290,7 @@ def __init__(
         adjust: bool = True,
         ignore_na: bool = False,
         axis: Axis = 0,
-        times: str | np.ndarray | FrameOrSeries | None = None,
+        times: str | np.ndarray | NDFrame | None = None,
         method: str = "single",
         *,
         selection=None,
@@ -330,7 +329,7 @@ def __init__(
             if not is_datetime64_ns_dtype(self.times):
                 raise ValueError("times must be datetime64[ns] dtype.")
             # error: Argument 1 to "len" has incompatible type "Union[str, ndarray,
-            # FrameOrSeries, None]"; expected "Sized"
+            # NDFrameT, None]"; expected "Sized"
             if len(self.times) != len(obj):  # type: ignore[arg-type]
                 raise ValueError("times must be the same length as the object.")
             if not isinstance(self.halflife, (str, datetime.timedelta)):
@@ -745,7 +744,7 @@ def _get_window_indexer(self) -> GroupbyIndexer:
 class OnlineExponentialMovingWindow(ExponentialMovingWindow):
     def __init__(
         self,
-        obj: FrameOrSeries,
+        obj: NDFrame,
         com: float | None = None,
         span: float | None = None,
         halflife: float | TimedeltaConvertibleTypes | None = None,
@@ -754,7 +753,7 @@ def __init__(
         adjust: bool = True,
         ignore_na: bool = False,
         axis: Axis = 0,
-        times: str | np.ndarray | FrameOrSeries | None = None,
+        times: str | np.ndarray | NDFrame | None = None,
         engine: str = "numba",
         engine_kwargs: dict[str, bool] | None = None,
         *,
diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index 94a5a9797d43d..ea40e8d816f45 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -27,7 +27,7 @@
 from pandas._typing import (
     ArrayLike,
     Axis,
-    FrameOrSeries,
+    NDFrameT,
     WindowingRankType,
 )
 from pandas.compat._optional import import_optional_dependency
@@ -227,7 +227,7 @@ def _validate(self) -> None:
         if self.method not in ["table", "single"]:
             raise ValueError("method must be 'table' or 'single")
 
-    def _create_data(self, obj: FrameOrSeries) -> FrameOrSeries:
+    def _create_data(self, obj: NDFrameT) -> NDFrameT:
         """
         Split data into blocks & return conformed data.
         """
@@ -796,7 +796,7 @@ def _apply_pairwise(
         result.index = result_index
         return result
 
-    def _create_data(self, obj: FrameOrSeries) -> FrameOrSeries:
+    def _create_data(self, obj: NDFrameT) -> NDFrameT:
         """
         Split data into blocks & return conformed data.
         """
diff --git a/pandas/io/formats/style.py b/pandas/io/formats/style.py
index 67f92c4a67e14..6e7a7593e56e0 100644
--- a/pandas/io/formats/style.py
+++ b/pandas/io/formats/style.py
@@ -22,7 +22,6 @@
 from pandas._typing import (
     Axis,
     FilePathOrBuffer,
-    FrameOrSeries,
     IndexLabel,
     Level,
     Scalar,
@@ -3190,10 +3189,10 @@ def pipe(self, func: Callable, *args, **kwargs):
 
 
 def _validate_apply_axis_arg(
-    arg: FrameOrSeries | Sequence | np.ndarray,
+    arg: NDFrame | Sequence | np.ndarray,
     arg_name: str,
     dtype: Any | None,
-    data: FrameOrSeries,
+    data: NDFrame,
 ) -> np.ndarray:
     """
     For the apply-type methods, ``axis=None`` creates ``data`` as DataFrame, and for
@@ -3310,10 +3309,10 @@ def css(rgba, text_only) -> str:
 
 
 def _highlight_between(
-    data: FrameOrSeries,
+    data: NDFrame,
     props: str,
-    left: Scalar | Sequence | np.ndarray | FrameOrSeries | None = None,
-    right: Scalar | Sequence | np.ndarray | FrameOrSeries | None = None,
+    left: Scalar | Sequence | np.ndarray | NDFrame | None = None,
+    right: Scalar | Sequence | np.ndarray | NDFrame | None = None,
     inclusive: bool | str = True,
 ) -> np.ndarray:
     """