diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index f8cb869e6ed89..f65c42dab1852 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -230,7 +230,7 @@ repos:
         language: python
         additional_dependencies:
         - flake8==4.0.1
-        - flake8-pyi==22.5.1
+        - flake8-pyi==22.7.0
     -   id: future-annotations
         name: import annotations from __future__
         entry: 'from __future__ import annotations'
diff --git a/pandas/_libs/algos.pyi b/pandas/_libs/algos.pyi
index f55ff0ae8b574..9ffcf25f6eacd 100644
--- a/pandas/_libs/algos.pyi
+++ b/pandas/_libs/algos.pyi
@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 from typing import Any
 
 import numpy as np
diff --git a/pandas/_libs/interval.pyi b/pandas/_libs/interval.pyi
index bad0f2bab93d8..b27d2b5f8fd4d 100644
--- a/pandas/_libs/interval.pyi
+++ b/pandas/_libs/interval.pyi
@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 from typing import (
     Any,
     Generic,
@@ -84,7 +82,7 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
         self: Interval[_OrderableTimesT], key: _OrderableTimesT
     ) -> bool: ...
     @overload
-    def __contains__(self: Interval[_OrderableScalarT], key: int | float) -> bool: ...
+    def __contains__(self: Interval[_OrderableScalarT], key: float) -> bool: ...
     @overload
     def __add__(
         self: Interval[_OrderableTimesT], y: Timedelta
@@ -94,7 +92,7 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __add__(self: Interval[float], y: int | float) -> Interval[float]: ...
+    def __add__(self: Interval[float], y: float) -> Interval[float]: ...
     @overload
     def __radd__(
         self: Interval[_OrderableTimesT], y: Timedelta
@@ -104,7 +102,7 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __radd__(self: Interval[float], y: int | float) -> Interval[float]: ...
+    def __radd__(self: Interval[float], y: float) -> Interval[float]: ...
     @overload
     def __sub__(
         self: Interval[_OrderableTimesT], y: Timedelta
@@ -114,7 +112,7 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __sub__(self: Interval[float], y: int | float) -> Interval[float]: ...
+    def __sub__(self: Interval[float], y: float) -> Interval[float]: ...
     @overload
     def __rsub__(
         self: Interval[_OrderableTimesT], y: Timedelta
@@ -124,31 +122,31 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __rsub__(self: Interval[float], y: int | float) -> Interval[float]: ...
+    def __rsub__(self: Interval[float], y: float) -> Interval[float]: ...
     @overload
     def __mul__(
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __mul__(self: Interval[float], y: int | float) -> Interval[float]: ...
+    def __mul__(self: Interval[float], y: float) -> Interval[float]: ...
     @overload
     def __rmul__(
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __rmul__(self: Interval[float], y: int | float) -> Interval[float]: ...
+    def __rmul__(self: Interval[float], y: float) -> Interval[float]: ...
     @overload
     def __truediv__(
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __truediv__(self: Interval[float], y: int | float) -> Interval[float]: ...
+    def __truediv__(self: Interval[float], y: float) -> Interval[float]: ...
     @overload
     def __floordiv__(
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __floordiv__(self: Interval[float], y: int | float) -> Interval[float]: ...
+    def __floordiv__(self: Interval[float], y: float) -> Interval[float]: ...
     def overlaps(self: Interval[_OrderableT], other: Interval[_OrderableT]) -> bool: ...
 
 def intervals_to_interval_bounds(
diff --git a/pandas/_libs/join.pyi b/pandas/_libs/join.pyi
index 8d02f8f57dee1..11b65b859095f 100644
--- a/pandas/_libs/join.pyi
+++ b/pandas/_libs/join.pyi
@@ -55,7 +55,7 @@ def asof_join_backward_on_X_by_Y(
     left_by_values: np.ndarray,  # by_t[:]
     right_by_values: np.ndarray,  # by_t[:]
     allow_exact_matches: bool = ...,
-    tolerance: np.number | int | float | None = ...,
+    tolerance: np.number | float | None = ...,
     use_hashtable: bool = ...,
 ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
 def asof_join_forward_on_X_by_Y(
@@ -64,7 +64,7 @@ def asof_join_forward_on_X_by_Y(
     left_by_values: np.ndarray,  # by_t[:]
     right_by_values: np.ndarray,  # by_t[:]
     allow_exact_matches: bool = ...,
-    tolerance: np.number | int | float | None = ...,
+    tolerance: np.number | float | None = ...,
     use_hashtable: bool = ...,
 ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
 def asof_join_nearest_on_X_by_Y(
@@ -73,6 +73,6 @@ def asof_join_nearest_on_X_by_Y(
     left_by_values: np.ndarray,  # by_t[:]
     right_by_values: np.ndarray,  # by_t[:]
     allow_exact_matches: bool = ...,
-    tolerance: np.number | int | float | None = ...,
+    tolerance: np.number | float | None = ...,
     use_hashtable: bool = ...,
 ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
diff --git a/pandas/_libs/json.pyi b/pandas/_libs/json.pyi
index 555484a37c83f..8e7ba60ccce24 100644
--- a/pandas/_libs/json.pyi
+++ b/pandas/_libs/json.pyi
@@ -12,7 +12,7 @@ def dumps(
     date_unit: str = ...,
     iso_dates: bool = ...,
     default_handler: None
-    | Callable[[Any], str | int | float | bool | list | dict | None] = ...,
+    | Callable[[Any], str | float | bool | list | dict | None] = ...,
 ) -> str: ...
 def loads(
     s: str,
diff --git a/pandas/_libs/tslibs/offsets.pyi b/pandas/_libs/tslibs/offsets.pyi
index c885b869f983a..c3d550c7a5ba9 100644
--- a/pandas/_libs/tslibs/offsets.pyi
+++ b/pandas/_libs/tslibs/offsets.pyi
@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 from datetime import (
     datetime,
     timedelta,
diff --git a/pandas/_libs/tslibs/timedeltas.pyi b/pandas/_libs/tslibs/timedeltas.pyi
index 1921329da9e24..7969c0901e08f 100644
--- a/pandas/_libs/tslibs/timedeltas.pyi
+++ b/pandas/_libs/tslibs/timedeltas.pyi
@@ -86,7 +86,7 @@ class Timedelta(timedelta):
         cls: type[_S],
         value=...,
         unit: str = ...,
-        **kwargs: int | float | np.integer | np.floating,
+        **kwargs: float | np.integer | np.floating,
     ) -> _S: ...
     # GH 46171
     # While Timedelta can return pd.NaT, having the constructor return
@@ -123,7 +123,7 @@ class Timedelta(timedelta):
     @overload  # type: ignore[override]
     def __floordiv__(self, other: timedelta) -> int: ...
     @overload
-    def __floordiv__(self, other: int | float) -> Timedelta: ...
+    def __floordiv__(self, other: float) -> Timedelta: ...
     @overload
     def __floordiv__(
         self, other: npt.NDArray[np.timedelta64]
diff --git a/pandas/_libs/tslibs/timestamps.pyi b/pandas/_libs/tslibs/timestamps.pyi
index 082f26cf6f213..f39d1f44d82c0 100644
--- a/pandas/_libs/tslibs/timestamps.pyi
+++ b/pandas/_libs/tslibs/timestamps.pyi
@@ -33,13 +33,7 @@ class Timestamp(datetime):
     value: int  # np.int64
     def __new__(
         cls: type[_DatetimeT],
-        ts_input: int
-        | np.integer
-        | float
-        | str
-        | _date
-        | datetime
-        | np.datetime64 = ...,
+        ts_input: np.integer | float | str | _date | datetime | np.datetime64 = ...,
         freq: int | None | str | BaseOffset = ...,
         tz: str | _tzinfo | None | int = ...,
         unit: str | int | None = ...,
diff --git a/pandas/_libs/writers.pyi b/pandas/_libs/writers.pyi
index 0d2096eee3573..611c0c7cd1512 100644
--- a/pandas/_libs/writers.pyi
+++ b/pandas/_libs/writers.pyi
@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 import numpy as np
 
 from pandas._typing import ArrayLike
diff --git a/pandas/_typing.py b/pandas/_typing.py
index 4bc5f75400455..6e531d10336b5 100644
--- a/pandas/_typing.py
+++ b/pandas/_typing.py
@@ -82,7 +82,7 @@
 
 # scalars
 
-PythonScalar = Union[str, int, float, bool]
+PythonScalar = Union[str, float, bool]
 DatetimeLikeScalar = Union["Period", "Timestamp", "Timedelta"]
 PandasScalar = Union["Period", "Timestamp", "Timedelta", "Interval"]
 Scalar = Union[PythonScalar, PandasScalar, np.datetime64, np.timedelta64, datetime]
@@ -92,10 +92,10 @@
 # timestamp and timedelta convertible types
 
 TimestampConvertibleTypes = Union[
-    "Timestamp", datetime, np.datetime64, int, np.int64, float, str
+    "Timestamp", datetime, np.datetime64, np.int64, float, str
 ]
 TimedeltaConvertibleTypes = Union[
-    "Timedelta", timedelta, np.timedelta64, int, np.int64, float, str
+    "Timedelta", timedelta, np.timedelta64, np.int64, float, str
 ]
 Timezone = Union[str, tzinfo]
 
@@ -126,7 +126,7 @@
 ]
 
 # dtypes
-NpDtype = Union[str, np.dtype, type_t[Union[str, float, int, complex, bool, object]]]
+NpDtype = Union[str, np.dtype, type_t[Union[str, complex, bool, object]]]
 Dtype = Union["ExtensionDtype", NpDtype]
 AstypeArg = Union["ExtensionDtype", "npt.DTypeLike"]
 # DtypeArg specifies all allowable dtypes in a functions its dtype argument
diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py
index c3fbd716ad09d..ea9414aaaa1a8 100644
--- a/pandas/core/arrays/datetimelike.py
+++ b/pandas/core/arrays/datetimelike.py
@@ -2170,11 +2170,11 @@ def validate_periods(periods: None) -> None:
 
 
 @overload
-def validate_periods(periods: int | float) -> int:
+def validate_periods(periods: float) -> int:
     ...
 
 
-def validate_periods(periods: int | float | None) -> int | None:
+def validate_periods(periods: float | None) -> int | None:
     """
     If a `periods` argument is passed to the Datetime/Timedelta Array/Index
     constructor, cast it to an integer.
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 47203fbf315e5..a541cbfe502fb 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -2563,7 +2563,7 @@ def to_stata(
         compression: CompressionOptions = "infer",
         storage_options: StorageOptions = None,
         *,
-        value_labels: dict[Hashable, dict[float | int, str]] | None = None,
+        value_labels: dict[Hashable, dict[float, str]] | None = None,
     ) -> None:
         """
         Export DataFrame object to Stata dta format.
diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index 81766dc91f271..6658b25d09e6d 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -827,7 +827,7 @@ def _get_counts_nanvar(
     axis: int | None,
     ddof: int,
     dtype: np.dtype = np.dtype(np.float64),
-) -> tuple[int | float | np.ndarray, int | float | np.ndarray]:
+) -> tuple[float | np.ndarray, float | np.ndarray]:
     """
     Get the count of non-null values along an axis, accounting
     for degrees of freedom.
@@ -1414,7 +1414,7 @@ def _get_counts(
     mask: npt.NDArray[np.bool_] | None,
     axis: int | None,
     dtype: np.dtype = np.dtype(np.float64),
-) -> int | float | np.ndarray:
+) -> float | np.ndarray:
     """
     Get the count of non-null values along an axis
 
diff --git a/pandas/core/reshape/encoding.py b/pandas/core/reshape/encoding.py
index fc908a5648885..da4de8cc57e65 100644
--- a/pandas/core/reshape/encoding.py
+++ b/pandas/core/reshape/encoding.py
@@ -272,7 +272,7 @@ def get_empty_frame(data) -> DataFrame:
 
     if sparse:
 
-        fill_value: bool | float | int
+        fill_value: bool | float
         if is_integer_dtype(dtype):
             fill_value = 0
         elif dtype == np.dtype(bool):
diff --git a/pandas/core/tools/datetimes.py b/pandas/core/tools/datetimes.py
index 1ec0e6ca83d8f..7ec4bc1016a9d 100644
--- a/pandas/core/tools/datetimes.py
+++ b/pandas/core/tools/datetimes.py
@@ -91,7 +91,7 @@
 # types used in annotations
 
 ArrayConvertible = Union[List, Tuple, AnyArrayLike]
-Scalar = Union[int, float, str]
+Scalar = Union[float, str]
 DatetimeScalar = Union[Scalar, datetime]
 
 DatetimeScalarOrArrayConvertible = Union[DatetimeScalar, ArrayConvertible]
diff --git a/pandas/core/tools/timedeltas.py b/pandas/core/tools/timedeltas.py
index 720d02f0cf59e..5026c97c0b2b0 100644
--- a/pandas/core/tools/timedeltas.py
+++ b/pandas/core/tools/timedeltas.py
@@ -45,7 +45,7 @@
 
 @overload
 def to_timedelta(
-    arg: str | int | float | timedelta,
+    arg: str | float | timedelta,
     unit: UnitChoices | None = ...,
     errors: DateTimeErrorChoices = ...,
 ) -> Timedelta:
diff --git a/pandas/io/formats/excel.py b/pandas/io/formats/excel.py
index 3f9f6c7a5fee7..4279a9707e692 100644
--- a/pandas/io/formats/excel.py
+++ b/pandas/io/formats/excel.py
@@ -331,7 +331,7 @@ def build_number_format(self, props: Mapping[str, str]) -> dict[str, str | None]
 
     def build_font(
         self, props: Mapping[str, str]
-    ) -> dict[str, bool | int | float | str | None]:
+    ) -> dict[str, bool | float | str | None]:
         font_names = self._get_font_names(props)
         decoration = self._get_decoration(props)
         return {
diff --git a/pandas/io/formats/format.py b/pandas/io/formats/format.py
index 57bc534bd67c4..58beba4ddcb44 100644
--- a/pandas/io/formats/format.py
+++ b/pandas/io/formats/format.py
@@ -1447,7 +1447,7 @@ def __init__(self, *args, **kwargs) -> None:
     def _value_formatter(
         self,
         float_format: FloatFormatType | None = None,
-        threshold: float | int | None = None,
+        threshold: float | None = None,
     ) -> Callable:
         """Returns a function to be applied on each value to format it"""
         # the float_format parameter supersedes self.float_format
@@ -2047,7 +2047,7 @@ def __init__(
         self.accuracy = accuracy
         self.use_eng_prefix = use_eng_prefix
 
-    def __call__(self, num: int | float) -> str:
+    def __call__(self, num: float) -> str:
         """
         Formats a number in engineering notation, appending a letter
         representing the power of 1000 of the original number. Some examples:
diff --git a/pandas/io/formats/info.py b/pandas/io/formats/info.py
index 07ec50a2cd6a8..543df8bec657b 100644
--- a/pandas/io/formats/info.py
+++ b/pandas/io/formats/info.py
@@ -325,7 +325,7 @@ def _put_str(s: str | Dtype, space: int) -> str:
     return str(s)[:space].ljust(space)
 
 
-def _sizeof_fmt(num: int | float, size_qualifier: str) -> str:
+def _sizeof_fmt(num: float, size_qualifier: str) -> str:
     """
     Return size in human readable format.
 
diff --git a/pandas/io/formats/style.py b/pandas/io/formats/style.py
index a557f9b5c0a0d..01b4812d3dc2a 100644
--- a/pandas/io/formats/style.py
+++ b/pandas/io/formats/style.py
@@ -3213,7 +3213,7 @@ def bar(
         cmap: Any | None = None,
         width: float = 100,
         height: float = 100,
-        align: str | float | int | Callable = "mid",
+        align: str | float | Callable = "mid",
         vmin: float | None = None,
         vmax: float | None = None,
         props: str = "width: 10em;",
@@ -4039,7 +4039,7 @@ def _highlight_value(data: DataFrame | Series, op: str, props: str) -> np.ndarra
 
 def _bar(
     data: NDFrame,
-    align: str | float | int | Callable,
+    align: str | float | Callable,
     colors: str | list | tuple,
     cmap: Any,
     width: float,
diff --git a/pandas/io/formats/style_render.py b/pandas/io/formats/style_render.py
index 65720e675a77a..dba161cf6d45c 100644
--- a/pandas/io/formats/style_render.py
+++ b/pandas/io/formats/style_render.py
@@ -48,7 +48,7 @@
 
 BaseFormatter = Union[str, Callable]
 ExtFormatter = Union[BaseFormatter, Dict[Any, Optional[BaseFormatter]]]
-CSSPair = Tuple[str, Union[str, int, float]]
+CSSPair = Tuple[str, Union[str, float]]
 CSSList = List[CSSPair]
 CSSProperties = Union[str, CSSList]
 
@@ -2055,7 +2055,7 @@ def _parse_latex_header_span(
         return display_val
 
 
-def _parse_latex_options_strip(value: str | int | float, arg: str) -> str:
+def _parse_latex_options_strip(value: str | float, arg: str) -> str:
     """
     Strip a css_value which may have latex wrapping arguments, css comment identifiers,
     and whitespaces, to a valid string for latex options parsing.
diff --git a/pandas/io/parsers/readers.py b/pandas/io/parsers/readers.py
index 4858d56d71c42..dc4556542d8e2 100644
--- a/pandas/io/parsers/readers.py
+++ b/pandas/io/parsers/readers.py
@@ -499,7 +499,7 @@ def validate_integer(name, val: None, min_val=...) -> None:
 
 
 @overload
-def validate_integer(name, val: int | float, min_val=...) -> int:
+def validate_integer(name, val: float, min_val=...) -> int:
     ...
 
 
@@ -1910,7 +1910,7 @@ def _floatify_na_values(na_values):
 
 def _stringify_na_values(na_values):
     """return a stringified and numeric for these values"""
-    result: list[int | str | float] = []
+    result: list[str | float] = []
     for x in na_values:
         result.append(str(x))
         result.append(x)
diff --git a/pandas/io/stata.py b/pandas/io/stata.py
index 2662df0361b55..80b6db2500d28 100644
--- a/pandas/io/stata.py
+++ b/pandas/io/stata.py
@@ -678,7 +678,7 @@ def __init__(
         self.labname = catarray.name
         self._encoding = encoding
         categories = catarray.cat.categories
-        self.value_labels: list[tuple[int | float, str]] = list(
+        self.value_labels: list[tuple[float, str]] = list(
             zip(np.arange(len(categories)), categories)
         )
         self.value_labels.sort(key=lambda x: x[0])
@@ -699,7 +699,7 @@ def _prepare_value_labels(self):
 
         # Compute lengths and setup lists of offsets and labels
         offsets: list[int] = []
-        values: list[int | float] = []
+        values: list[float] = []
         for vl in self.value_labels:
             category: str | bytes = vl[1]
             if not isinstance(category, str):
@@ -798,7 +798,7 @@ class StataNonCatValueLabel(StataValueLabel):
     def __init__(
         self,
         labname: str,
-        value_labels: dict[float | int, str],
+        value_labels: dict[float, str],
         encoding: Literal["latin-1", "utf-8"] = "latin-1",
     ) -> None:
 
@@ -807,7 +807,7 @@ def __init__(
 
         self.labname = labname
         self._encoding = encoding
-        self.value_labels: list[tuple[int | float, str]] = sorted(
+        self.value_labels: list[tuple[float, str]] = sorted(
             value_labels.items(), key=lambda x: x[0]
         )
         self._prepare_value_labels()
@@ -887,7 +887,7 @@ class StataMissingValue:
         "float64": struct.unpack("<d", float64_base)[0],
     }
 
-    def __init__(self, value: int | float) -> None:
+    def __init__(self, value: float) -> None:
         self._value = value
         # Conversion to int to avoid hash issues on 32 bit platforms #8968
         value = int(value) if value < 2147483648 else float(value)
@@ -906,7 +906,7 @@ def string(self) -> str:
         return self._str
 
     @property
-    def value(self) -> int | float:
+    def value(self) -> float:
         """
         The binary representation of the missing value.
 
@@ -931,7 +931,7 @@ def __eq__(self, other: Any) -> bool:
         )
 
     @classmethod
-    def get_base_missing_value(cls, dtype: np.dtype) -> int | float:
+    def get_base_missing_value(cls, dtype: np.dtype) -> float:
         if dtype.type is np.int8:
             value = cls.BASE_MISSING_VALUES["int8"]
         elif dtype.type is np.int16:
@@ -1526,7 +1526,7 @@ def _read_value_labels(self) -> None:
         if self.format_version <= 108:
             # Value labels are not supported in version 108 and earlier.
             self._value_labels_read = True
-            self.value_label_dict: dict[str, dict[float | int, str]] = {}
+            self.value_label_dict: dict[str, dict[float, str]] = {}
             return
 
         if self.format_version >= 117:
@@ -1886,7 +1886,7 @@ def _do_select_columns(self, data: DataFrame, columns: Sequence[str]) -> DataFra
     def _do_convert_categoricals(
         self,
         data: DataFrame,
-        value_label_dict: dict[str, dict[float | int, str]],
+        value_label_dict: dict[str, dict[float, str]],
         lbllist: Sequence[str],
         order_categoricals: bool,
     ) -> DataFrame:
@@ -1977,7 +1977,7 @@ def variable_labels(self) -> dict[str, str]:
         """
         return dict(zip(self.varlist, self._variable_labels))
 
-    def value_labels(self) -> dict[str, dict[float | int, str]]:
+    def value_labels(self) -> dict[str, dict[float, str]]:
         """
         Return a dict, associating each variable name a dict, associating
         each value its corresponding label.
@@ -2270,7 +2270,7 @@ def __init__(
         compression: CompressionOptions = "infer",
         storage_options: StorageOptions = None,
         *,
-        value_labels: dict[Hashable, dict[float | int, str]] | None = None,
+        value_labels: dict[Hashable, dict[float, str]] | None = None,
     ) -> None:
         super().__init__()
         self.data = data
@@ -3200,7 +3200,7 @@ def __init__(
         compression: CompressionOptions = "infer",
         storage_options: StorageOptions = None,
         *,
-        value_labels: dict[Hashable, dict[float | int, str]] | None = None,
+        value_labels: dict[Hashable, dict[float, str]] | None = None,
     ) -> None:
         # Copy to new list since convert_strl might be modified later
         self._convert_strl: list[Hashable] = []
@@ -3597,7 +3597,7 @@ def __init__(
         compression: CompressionOptions = "infer",
         storage_options: StorageOptions = None,
         *,
-        value_labels: dict[Hashable, dict[float | int, str]] | None = None,
+        value_labels: dict[Hashable, dict[float, str]] | None = None,
     ) -> None:
         if version is None:
             version = 118 if data.shape[1] <= 32767 else 119