diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 966fda1ed710a..8df6d70a3bed4 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -268,7 +268,7 @@ repos:
             |/_testing/
     -   id: autotyping
         name: autotyping
-        entry: python -m libcst.tool codemod autotyping.AutotypeCommand --none-return --scalar-return --annotate-magics --annotate-imprecise-magics --bool-param --bytes-param --str-param --float-param
+        entry: python -m libcst.tool codemod autotyping.AutotypeCommand --aggressive
         types_or: [python, pyi]
         files: ^pandas
         exclude: ^(pandas/tests|pandas/_version.py|pandas/io/clipboard)
diff --git a/pandas/_config/config.py b/pandas/_config/config.py
index e1a6cf04a435e..3b17d6953d61a 100644
--- a/pandas/_config/config.py
+++ b/pandas/_config/config.py
@@ -704,7 +704,7 @@ def _build_option_description(k: str) -> str:
     return s
 
 
-def pp_options_list(keys: Iterable[str], width=80, _print: bool = False):
+def pp_options_list(keys: Iterable[str], width: int = 80, _print: bool = False):
     """Builds a concise listing of available options, grouped by prefix"""
     from itertools import groupby
     from textwrap import wrap
diff --git a/pandas/_testing/__init__.py b/pandas/_testing/__init__.py
index e9bf19899f31e..f5f2aa23459e4 100644
--- a/pandas/_testing/__init__.py
+++ b/pandas/_testing/__init__.py
@@ -341,11 +341,13 @@ def getCols(k) -> str:
 
 
 # make index
-def makeStringIndex(k=10, name=None) -> Index:
+def makeStringIndex(k: int = 10, name=None) -> Index:
     return Index(rands_array(nchars=10, size=k), name=name)
 
 
-def makeCategoricalIndex(k=10, n=3, name=None, **kwargs) -> CategoricalIndex:
+def makeCategoricalIndex(
+    k: int = 10, n: int = 3, name=None, **kwargs
+) -> CategoricalIndex:
     """make a length k index or n categories"""
     x = rands_array(nchars=4, size=n, replace=False)
     return CategoricalIndex(
@@ -353,13 +355,13 @@ def makeCategoricalIndex(k=10, n=3, name=None, **kwargs) -> CategoricalIndex:
     )
 
 
-def makeIntervalIndex(k=10, name=None, **kwargs) -> IntervalIndex:
+def makeIntervalIndex(k: int = 10, name=None, **kwargs) -> IntervalIndex:
     """make a length k IntervalIndex"""
     x = np.linspace(0, 100, num=(k + 1))
     return IntervalIndex.from_breaks(x, name=name, **kwargs)
 
 
-def makeBoolIndex(k=10, name=None) -> Index:
+def makeBoolIndex(k: int = 10, name=None) -> Index:
     if k == 1:
         return Index([True], name=name)
     elif k == 2:
@@ -367,7 +369,7 @@ def makeBoolIndex(k=10, name=None) -> Index:
     return Index([False, True] + [False] * (k - 2), name=name)
 
 
-def makeNumericIndex(k=10, name=None, *, dtype) -> NumericIndex:
+def makeNumericIndex(k: int = 10, name=None, *, dtype) -> NumericIndex:
     dtype = pandas_dtype(dtype)
     assert isinstance(dtype, np.dtype)
 
@@ -385,21 +387,21 @@ def makeNumericIndex(k=10, name=None, *, dtype) -> NumericIndex:
     return NumericIndex(values, dtype=dtype, name=name)
 
 
-def makeIntIndex(k=10, name=None) -> Int64Index:
+def makeIntIndex(k: int = 10, name=None) -> Int64Index:
     base_idx = makeNumericIndex(k, name=name, dtype="int64")
     return Int64Index(base_idx)
 
 
-def makeUIntIndex(k=10, name=None) -> UInt64Index:
+def makeUIntIndex(k: int = 10, name=None) -> UInt64Index:
     base_idx = makeNumericIndex(k, name=name, dtype="uint64")
     return UInt64Index(base_idx)
 
 
-def makeRangeIndex(k=10, name=None, **kwargs) -> RangeIndex:
+def makeRangeIndex(k: int = 10, name=None, **kwargs) -> RangeIndex:
     return RangeIndex(0, k, 1, name=name, **kwargs)
 
 
-def makeFloatIndex(k=10, name=None) -> Float64Index:
+def makeFloatIndex(k: int = 10, name=None) -> Float64Index:
     base_idx = makeNumericIndex(k, name=name, dtype="float64")
     return Float64Index(base_idx)
 
@@ -423,7 +425,7 @@ def makePeriodIndex(k: int = 10, name=None, **kwargs) -> PeriodIndex:
     return pd.period_range(start=dt, periods=k, freq="B", name=name, **kwargs)
 
 
-def makeMultiIndex(k=10, names=None, **kwargs):
+def makeMultiIndex(k: int = 10, names=None, **kwargs):
     N = (k // 2) + 1
     rng = range(N)
     mi = MultiIndex.from_product([("foo", "bar"), rng], names=names, **kwargs)
@@ -665,8 +667,8 @@ def makeCustomDataframe(
     ncols,
     c_idx_names: bool | list[str] = True,
     r_idx_names: bool | list[str] = True,
-    c_idx_nlevels=1,
-    r_idx_nlevels=1,
+    c_idx_nlevels: int = 1,
+    r_idx_nlevels: int = 1,
     data_gen_f=None,
     c_ndupe_l=None,
     r_ndupe_l=None,
diff --git a/pandas/core/arrays/_mixins.py b/pandas/core/arrays/_mixins.py
index 6860ba291bf73..74fc15a6fad63 100644
--- a/pandas/core/arrays/_mixins.py
+++ b/pandas/core/arrays/_mixins.py
@@ -250,7 +250,7 @@ def _validate_searchsorted_value(
             return value
 
     @doc(ExtensionArray.shift)
-    def shift(self, periods=1, fill_value=None, axis=0):
+    def shift(self, periods: int = 1, fill_value=None, axis: AxisInt = 0):
 
         fill_value = self._validate_shift_value(fill_value)
         new_values = shift(self._ndarray, periods, axis, fill_value)
diff --git a/pandas/core/arrays/masked.py b/pandas/core/arrays/masked.py
index b04a26120cabb..043e0baf3ec0e 100644
--- a/pandas/core/arrays/masked.py
+++ b/pandas/core/arrays/masked.py
@@ -1062,7 +1062,12 @@ def _wrap_reduction_result(self, name: str, result, skipna, **kwargs):
         return result
 
     def sum(
-        self, *, skipna: bool = True, min_count=0, axis: AxisInt | None = 0, **kwargs
+        self,
+        *,
+        skipna: bool = True,
+        min_count: int = 0,
+        axis: AxisInt | None = 0,
+        **kwargs,
     ):
         nv.validate_sum((), kwargs)
 
@@ -1085,7 +1090,12 @@ def sum(
         )
 
     def prod(
-        self, *, skipna: bool = True, min_count=0, axis: AxisInt | None = 0, **kwargs
+        self,
+        *,
+        skipna: bool = True,
+        min_count: int = 0,
+        axis: AxisInt | None = 0,
+        **kwargs,
     ):
         nv.validate_prod((), kwargs)
         result = masked_reductions.prod(
diff --git a/pandas/core/arrays/numpy_.py b/pandas/core/arrays/numpy_.py
index 290860d897ea2..4d5286e7364f5 100644
--- a/pandas/core/arrays/numpy_.py
+++ b/pandas/core/arrays/numpy_.py
@@ -243,7 +243,12 @@ def max(
         return self._wrap_reduction_result(axis, result)
 
     def sum(
-        self, *, axis: AxisInt | None = None, skipna: bool = True, min_count=0, **kwargs
+        self,
+        *,
+        axis: AxisInt | None = None,
+        skipna: bool = True,
+        min_count: int = 0,
+        **kwargs,
     ) -> Scalar:
         nv.validate_sum((), kwargs)
         result = nanops.nansum(
@@ -252,7 +257,12 @@ def sum(
         return self._wrap_reduction_result(axis, result)
 
     def prod(
-        self, *, axis: AxisInt | None = None, skipna: bool = True, min_count=0, **kwargs
+        self,
+        *,
+        axis: AxisInt | None = None,
+        skipna: bool = True,
+        min_count: int = 0,
+        **kwargs,
     ) -> Scalar:
         nv.validate_prod((), kwargs)
         result = nanops.nanprod(
@@ -294,7 +304,7 @@ def std(
         axis: AxisInt | None = None,
         dtype: NpDtype | None = None,
         out=None,
-        ddof=1,
+        ddof: int = 1,
         keepdims: bool = False,
         skipna: bool = True,
     ):
@@ -310,7 +320,7 @@ def var(
         axis: AxisInt | None = None,
         dtype: NpDtype | None = None,
         out=None,
-        ddof=1,
+        ddof: int = 1,
         keepdims: bool = False,
         skipna: bool = True,
     ):
@@ -326,7 +336,7 @@ def sem(
         axis: AxisInt | None = None,
         dtype: NpDtype | None = None,
         out=None,
-        ddof=1,
+        ddof: int = 1,
         keepdims: bool = False,
         skipna: bool = True,
     ):
diff --git a/pandas/core/arrays/period.py b/pandas/core/arrays/period.py
index c0d476c2452b8..5e1b0c4b18718 100644
--- a/pandas/core/arrays/period.py
+++ b/pandas/core/arrays/period.py
@@ -1067,7 +1067,7 @@ def dt64arr_to_periodarr(
     return c_dt64arr_to_periodarr(data.view("i8"), base, tz, reso=reso), freq
 
 
-def _get_ordinal_range(start, end, periods, freq, mult=1):
+def _get_ordinal_range(start, end, periods, freq, mult: int = 1):
     if com.count_not_none(start, end, periods) != 2:
         raise ValueError(
             "Of the three parameters: start, end, and periods, "
diff --git a/pandas/core/arrays/sparse/array.py b/pandas/core/arrays/sparse/array.py
index c6d2cf9e25fa9..40a56e27c63f5 100644
--- a/pandas/core/arrays/sparse/array.py
+++ b/pandas/core/arrays/sparse/array.py
@@ -32,6 +32,7 @@
 from pandas._typing import (
     ArrayLike,
     AstypeArg,
+    Axis,
     AxisInt,
     Dtype,
     NpDtype,
@@ -1479,7 +1480,7 @@ def all(self, axis=None, *args, **kwargs):
 
         return values.all()
 
-    def any(self, axis=0, *args, **kwargs):
+    def any(self, axis: AxisInt = 0, *args, **kwargs):
         """
         Tests whether at least one of elements evaluate True
 
@@ -1576,7 +1577,7 @@ def cumsum(self, axis: AxisInt = 0, *args, **kwargs) -> SparseArray:
             fill_value=self.fill_value,
         )
 
-    def mean(self, axis=0, *args, **kwargs):
+    def mean(self, axis: Axis = 0, *args, **kwargs):
         """
         Mean of non-NA/null values
 
diff --git a/pandas/core/arrays/string_arrow.py b/pandas/core/arrays/string_arrow.py
index cfa61abcaa2a7..faa662611c0e1 100644
--- a/pandas/core/arrays/string_arrow.py
+++ b/pandas/core/arrays/string_arrow.py
@@ -310,7 +310,7 @@ def _str_map(
             return lib.map_infer_mask(arr, f, mask.view("uint8"))
 
     def _str_contains(
-        self, pat, case: bool = True, flags=0, na=np.nan, regex: bool = True
+        self, pat, case: bool = True, flags: int = 0, na=np.nan, regex: bool = True
     ):
         if flags:
             fallback_performancewarning()
diff --git a/pandas/core/base.py b/pandas/core/base.py
index a1ca8b59dcffa..4e2f6a77930a1 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -25,6 +25,7 @@
 import pandas._libs.lib as lib
 from pandas._typing import (
     ArrayLike,
+    Axis,
     AxisInt,
     DtypeObj,
     IndexLabel,
@@ -784,7 +785,7 @@ def _reduce(
         op,
         name: str,
         *,
-        axis=0,
+        axis: Axis = 0,
         skipna: bool = True,
         numeric_only=None,
         filter_type=None,
diff --git a/pandas/core/computation/eval.py b/pandas/core/computation/eval.py
index bcd39eab88590..2ed3ece05ebba 100644
--- a/pandas/core/computation/eval.py
+++ b/pandas/core/computation/eval.py
@@ -176,7 +176,7 @@ def eval(
     local_dict=None,
     global_dict=None,
     resolvers=(),
-    level=0,
+    level: int = 0,
     target=None,
     inplace: bool = False,
 ):
diff --git a/pandas/core/dtypes/concat.py b/pandas/core/dtypes/concat.py
index 8ea78ff68a291..004b1751b917f 100644
--- a/pandas/core/dtypes/concat.py
+++ b/pandas/core/dtypes/concat.py
@@ -337,7 +337,7 @@ def _concatenate_2d(to_concat, axis: AxisInt):
     return np.concatenate(to_concat, axis=axis)
 
 
-def _concat_datetime(to_concat, axis=0):
+def _concat_datetime(to_concat, axis: AxisInt = 0):
     """
     provide concatenation of an datetimelike array of arrays each of which is a
     single M8[ns], datetime64[ns, tz] or m8[ns] dtype
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 7064848233581..17bd50b9ad8f0 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -10867,7 +10867,7 @@ def func(values: np.ndarray):
             # We only use this in the case that operates on self.values
             return op(values, axis=axis, skipna=skipna, **kwds)
 
-        def blk_func(values, axis=1):
+        def blk_func(values, axis: Axis = 1):
             if isinstance(values, ExtensionArray):
                 if not is_1d_only_ea_dtype(values.dtype) and not isinstance(
                     self._mgr, ArrayManager
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index b520aab2cfa5b..d5f3a4ad080e5 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -1327,7 +1327,7 @@ class  name
             return None
 
     @final
-    def _set_axis_name(self, name, axis=0, inplace: bool_t = False):
+    def _set_axis_name(self, name, axis: Axis = 0, inplace: bool_t = False):
         """
         Set the name(s) of the axis.
 
@@ -1672,7 +1672,7 @@ def __round__(self: NDFrameT, decimals: int = 0) -> NDFrameT:
     # have consistent precedence and validation logic throughout the library.
 
     @final
-    def _is_level_reference(self, key: Level, axis=0) -> bool_t:
+    def _is_level_reference(self, key: Level, axis: Axis = 0) -> bool_t:
         """
         Test whether a key is a level reference for a given axis.
 
@@ -1693,17 +1693,17 @@ def _is_level_reference(self, key: Level, axis=0) -> bool_t:
         -------
         is_level : bool
         """
-        axis = self._get_axis_number(axis)
+        axis_int = self._get_axis_number(axis)
 
         return (
             key is not None
             and is_hashable(key)
-            and key in self.axes[axis].names
-            and not self._is_label_reference(key, axis=axis)
+            and key in self.axes[axis_int].names
+            and not self._is_label_reference(key, axis=axis_int)
         )
 
     @final
-    def _is_label_reference(self, key: Level, axis=0) -> bool_t:
+    def _is_label_reference(self, key: Level, axis: int = 0) -> bool_t:
         """
         Test whether a key is a label reference for a given axis.
 
@@ -1758,7 +1758,7 @@ def _is_label_or_level_reference(self, key: Level, axis: AxisInt = 0) -> bool_t:
         )
 
     @final
-    def _check_label_or_level_ambiguity(self, key: Level, axis: AxisInt = 0) -> None:
+    def _check_label_or_level_ambiguity(self, key: Level, axis: Axis = 0) -> None:
         """
         Check whether `key` is ambiguous.
 
@@ -1777,23 +1777,23 @@ def _check_label_or_level_ambiguity(self, key: Level, axis: AxisInt = 0) -> None
         ValueError: `key` is ambiguous
         """
 
-        axis = self._get_axis_number(axis)
-        other_axes = (ax for ax in range(self._AXIS_LEN) if ax != axis)
+        axis_int = self._get_axis_number(axis)
+        other_axes = (ax for ax in range(self._AXIS_LEN) if ax != axis_int)
 
         if (
             key is not None
             and is_hashable(key)
-            and key in self.axes[axis].names
+            and key in self.axes[axis_int].names
             and any(key in self.axes[ax] for ax in other_axes)
         ):
 
             # Build an informative and grammatical warning
             level_article, level_type = (
-                ("an", "index") if axis == 0 else ("a", "column")
+                ("an", "index") if axis_int == 0 else ("a", "column")
             )
 
             label_article, label_type = (
-                ("a", "column") if axis == 0 else ("an", "index")
+                ("a", "column") if axis_int == 0 else ("an", "index")
             )
 
             msg = (
@@ -3784,7 +3784,7 @@ def _clear_item_cache(self) -> None:
     # Indexing Methods
 
     def take(
-        self: NDFrameT, indices, axis=0, is_copy: bool_t | None = None, **kwargs
+        self: NDFrameT, indices, axis: Axis = 0, is_copy: bool_t | None = None, **kwargs
     ) -> NDFrameT:
         """
         Return the elements in the given *positional* indices along an axis.
@@ -3881,7 +3881,7 @@ class  max_speed
     def _take(
         self: NDFrameT,
         indices,
-        axis=0,
+        axis: Axis = 0,
         convert_indices: bool_t = True,
     ) -> NDFrameT:
         """
@@ -3899,7 +3899,7 @@ def _take(
         )
         return self._constructor(new_data).__finalize__(self, method="take")
 
-    def _take_with_is_copy(self: NDFrameT, indices, axis=0) -> NDFrameT:
+    def _take_with_is_copy(self: NDFrameT, indices, axis: 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
@@ -4102,7 +4102,7 @@ class   animal   locomotion
     def __getitem__(self, item):
         raise AbstractMethodError(self)
 
-    def _slice(self: NDFrameT, slobj: slice, axis=0) -> NDFrameT:
+    def _slice(self: NDFrameT, slobj: slice, axis: Axis = 0) -> NDFrameT:
         """
         Construct a slice of this container.
 
@@ -9052,7 +9052,7 @@ def last(self: NDFrameT, offset) -> NDFrameT:
     @final
     def rank(
         self: NDFrameT,
-        axis=0,
+        axis: Axis = 0,
         method: str = "average",
         numeric_only: bool_t | None | lib.NoDefault = lib.no_default,
         na_option: str = "keep",
@@ -9168,7 +9168,7 @@ def rank(
         elif numeric_only is lib.no_default:
             numeric_only = None
 
-        axis = self._get_axis_number(axis)
+        axis_int = self._get_axis_number(axis)
 
         if na_option not in {"keep", "top", "bottom"}:
             msg = "na_option must be one of 'keep', 'top', or 'bottom'"
@@ -9184,7 +9184,7 @@ def ranker(data):
 
             if isinstance(values, ExtensionArray):
                 ranks = values._rank(
-                    axis=axis,
+                    axis=axis_int,
                     method=method,
                     ascending=ascending,
                     na_option=na_option,
@@ -9193,7 +9193,7 @@ def ranker(data):
             else:
                 ranks = algos.rank(
                     values,
-                    axis=axis,
+                    axis=axis_int,
                     method=method,
                     ascending=ascending,
                     na_option=na_option,
@@ -9515,7 +9515,7 @@ def _align_frame(
         fill_value=None,
         method=None,
         limit=None,
-        fill_axis=0,
+        fill_axis: Axis = 0,
     ):
         # defaults
         join_index, join_columns = None, None
@@ -9579,7 +9579,7 @@ def _align_series(
         fill_value=None,
         method=None,
         limit=None,
-        fill_axis=0,
+        fill_axis: Axis = 0,
     ):
 
         is_series = isinstance(self, ABCSeries)
@@ -10247,7 +10247,7 @@ def shift(
         return result.__finalize__(self, method="shift")
 
     @final
-    def slice_shift(self: NDFrameT, periods: int = 1, axis=0) -> NDFrameT:
+    def slice_shift(self: NDFrameT, periods: int = 1, axis: Axis = 0) -> NDFrameT:
         """
         Equivalent to `shift` without copying data.
 
@@ -10506,7 +10506,7 @@ def truncate(
     @final
     @doc(klass=_shared_doc_kwargs["klass"])
     def tz_convert(
-        self: NDFrameT, tz, axis=0, level=None, copy: bool_t = True
+        self: NDFrameT, tz, axis: Axis = 0, level=None, copy: bool_t = True
     ) -> NDFrameT:
         """
         Convert tz-aware axis to target time zone.
@@ -10567,7 +10567,7 @@ def _tz_convert(ax, tz):
     def tz_localize(
         self: NDFrameT,
         tz,
-        axis=0,
+        axis: Axis = 0,
         level=None,
         copy: bool_t = True,
         ambiguous: TimeAmbiguous = "raise",
@@ -10995,7 +10995,7 @@ def describe(
     @final
     def pct_change(
         self: NDFrameT,
-        periods=1,
+        periods: int = 1,
         fill_method: Literal["backfill", "bfill", "pad", "ffill"] = "pad",
         limit=None,
         freq=None,
@@ -11542,7 +11542,7 @@ def sum(
         skipna: bool_t = True,
         level: Level | None = None,
         numeric_only: bool_t | None = None,
-        min_count=0,
+        min_count: int = 0,
         **kwargs,
     ):
         return self._min_count_stat_function(
@@ -11660,7 +11660,12 @@ def _add_numeric_operations(cls) -> None:
             empty_value=False,
         )
         def any(
-            self, axis=0, bool_only=None, skipna: bool_t = True, level=None, **kwargs
+            self,
+            axis: Axis = 0,
+            bool_only=None,
+            skipna: bool_t = True,
+            level=None,
+            **kwargs,
         ):
             return NDFrame.any(self, axis, bool_only, skipna, level, **kwargs)
 
@@ -11677,7 +11682,12 @@ def any(
             empty_value=True,
         )
         def all(
-            self, axis=0, bool_only=None, skipna: bool_t = True, level=None, **kwargs
+            self,
+            axis: Axis = 0,
+            bool_only=None,
+            skipna: bool_t = True,
+            level=None,
+            **kwargs,
         ):
             return NDFrame.all(self, axis, bool_only, skipna, level, **kwargs)
 
@@ -11714,7 +11724,7 @@ def sem(
             axis: Axis | None = None,
             skipna: bool_t = True,
             level=None,
-            ddof=1,
+            ddof: int = 1,
             numeric_only=None,
             **kwargs,
         ):
@@ -11737,7 +11747,7 @@ def var(
             axis: Axis | None = None,
             skipna: bool_t = True,
             level=None,
-            ddof=1,
+            ddof: int = 1,
             numeric_only=None,
             **kwargs,
         ):
@@ -11761,7 +11771,7 @@ def std(
             axis: Axis | None = None,
             skipna: bool_t = True,
             level=None,
-            ddof=1,
+            ddof: int = 1,
             numeric_only=None,
             **kwargs,
         ):
@@ -11851,7 +11861,7 @@ def sum(
             skipna: bool_t = True,
             level=None,
             numeric_only=None,
-            min_count=0,
+            min_count: int = 0,
             **kwargs,
         ):
             return NDFrame.sum(
@@ -11876,7 +11886,7 @@ def prod(
             skipna: bool_t = True,
             level=None,
             numeric_only=None,
-            min_count=0,
+            min_count: int = 0,
             **kwargs,
         ):
             return NDFrame.prod(
diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 4e17276a4eb1b..c81091ca36b52 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1765,7 +1765,7 @@ def nunique(self, dropna: bool = True) -> DataFrame:
     )
     def idxmax(
         self,
-        axis=0,
+        axis: Axis = 0,
         skipna: bool = True,
         numeric_only: bool | lib.NoDefault = lib.no_default,
     ) -> DataFrame:
@@ -1806,7 +1806,7 @@ def func(df):
     )
     def idxmin(
         self,
-        axis=0,
+        axis: Axis = 0,
         skipna: bool = True,
         numeric_only: bool | lib.NoDefault = lib.no_default,
     ) -> DataFrame:
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 77b0d2e486bc2..4ad5b0d927450 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -46,6 +46,7 @@ class providing the base-class of operations.
 from pandas._typing import (
     AnyArrayLike,
     ArrayLike,
+    Axis,
     AxisInt,
     Dtype,
     FillnaOptions,
@@ -920,7 +921,7 @@ def __init__(
         self,
         obj: NDFrameT,
         keys: _KeysArgType | None = None,
-        axis: AxisInt = 0,
+        axis: Axis = 0,
         level: IndexLabel | None = None,
         grouper: ops.BaseGrouper | None = None,
         exclusions: frozenset[Hashable] | None = None,
@@ -3677,7 +3678,7 @@ def rank(
     @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
-    def cumprod(self, axis=0, *args, **kwargs) -> NDFrameT:
+    def cumprod(self, axis: Axis = 0, *args, **kwargs) -> NDFrameT:
         """
         Cumulative product for each group.
 
@@ -3695,7 +3696,7 @@ def cumprod(self, axis=0, *args, **kwargs) -> NDFrameT:
     @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
-    def cumsum(self, axis=0, *args, **kwargs) -> NDFrameT:
+    def cumsum(self, axis: Axis = 0, *args, **kwargs) -> NDFrameT:
         """
         Cumulative sum for each group.
 
@@ -3713,7 +3714,9 @@ def cumsum(self, axis=0, *args, **kwargs) -> NDFrameT:
     @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
-    def cummin(self, axis=0, numeric_only: bool = False, **kwargs) -> NDFrameT:
+    def cummin(
+        self, axis: AxisInt = 0, numeric_only: bool = False, **kwargs
+    ) -> NDFrameT:
         """
         Cumulative min for each group.
 
@@ -3737,7 +3740,9 @@ def cummin(self, axis=0, numeric_only: bool = False, **kwargs) -> NDFrameT:
     @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
-    def cummax(self, axis=0, numeric_only: bool = False, **kwargs) -> NDFrameT:
+    def cummax(
+        self, axis: AxisInt = 0, numeric_only: bool = False, **kwargs
+    ) -> NDFrameT:
         """
         Cumulative max for each group.
 
@@ -3907,7 +3912,7 @@ def blk_func(values: ArrayLike) -> ArrayLike:
 
     @final
     @Substitution(name="groupby")
-    def shift(self, periods=1, freq=None, axis=0, fill_value=None):
+    def shift(self, periods: int = 1, freq=None, axis: Axis = 0, fill_value=None):
         """
         Shift each group by periods observations.
 
@@ -3999,11 +4004,11 @@ def diff(self, periods: int = 1, axis: AxisInt = 0) -> NDFrameT:
     @Appender(_common_see_also)
     def pct_change(
         self,
-        periods=1,
+        periods: int = 1,
         fill_method: FillnaOptions = "ffill",
         limit=None,
         freq=None,
-        axis=0,
+        axis: Axis = 0,
     ):
         """
         Calculate pct_change of each value to previous entry in group.
diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py
index c54954e61096b..11eb12dbacbc7 100644
--- a/pandas/core/groupby/grouper.py
+++ b/pandas/core/groupby/grouper.py
@@ -18,7 +18,7 @@
 
 from pandas._typing import (
     ArrayLike,
-    AxisInt,
+    Axis,
     NDFrameT,
     npt,
 )
@@ -260,7 +260,6 @@ class Grouper:
     Freq: 17T, dtype: int64
     """
 
-    axis: AxisInt
     sort: bool
     dropna: bool
     _gpr_index: Index | None
@@ -281,7 +280,7 @@ def __init__(
         key=None,
         level=None,
         freq=None,
-        axis: AxisInt = 0,
+        axis: Axis = 0,
         sort: bool = False,
         dropna: bool = True,
     ) -> None:
@@ -705,7 +704,7 @@ def groups(self) -> dict[Hashable, np.ndarray]:
 def get_grouper(
     obj: NDFrameT,
     key=None,
-    axis: AxisInt = 0,
+    axis: Axis = 0,
     level=None,
     sort: bool = True,
     observed: bool = False,
diff --git a/pandas/core/indexes/api.py b/pandas/core/indexes/api.py
index b4f47f70c5a84..48d367b86b157 100644
--- a/pandas/core/indexes/api.py
+++ b/pandas/core/indexes/api.py
@@ -9,6 +9,7 @@
     NaT,
     lib,
 )
+from pandas._typing import Axis
 from pandas.errors import InvalidIndexError
 
 from pandas.core.dtypes.cast import find_common_type
@@ -76,7 +77,7 @@
 
 
 def get_objs_combined_axis(
-    objs, intersect: bool = False, axis=0, sort: bool = True, copy: bool = False
+    objs, intersect: bool = False, axis: Axis = 0, sort: bool = True, copy: bool = False
 ) -> Index:
     """
     Extract combined index: return intersection or union (depending on the
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 7dc04474cbcd8..0582d691ad584 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -49,12 +49,13 @@
     AnyAll,
     ArrayLike,
     Axes,
-    AxisInt,
+    Axis,
     DropKeep,
     Dtype,
     DtypeObj,
     F,
     IgnoreRaise,
+    IndexLabel,
     Level,
     Shape,
     npt,
@@ -1180,7 +1181,7 @@ def astype(self, dtype, copy: bool = True):
     def take(
         self,
         indices,
-        axis: AxisInt = 0,
+        axis: Axis = 0,
         allow_fill: bool = True,
         fill_value=None,
         **kwargs,
@@ -2167,7 +2168,7 @@ def _get_level_values(self, level) -> Index:
     get_level_values = _get_level_values
 
     @final
-    def droplevel(self, level=0):
+    def droplevel(self, level: IndexLabel = 0):
         """
         Return index with requested level(s) removed.
 
@@ -5867,7 +5868,7 @@ def sort(self, *args, **kwargs):
         """
         raise TypeError("cannot sort an Index object in-place, use sort_values instead")
 
-    def shift(self, periods=1, freq=None):
+    def shift(self, periods: int = 1, freq=None):
         """
         Shift index by desired number of time frequency increments.
 
diff --git a/pandas/core/indexes/datetimelike.py b/pandas/core/indexes/datetimelike.py
index f4077449a7907..147d1649e5e1b 100644
--- a/pandas/core/indexes/datetimelike.py
+++ b/pandas/core/indexes/datetimelike.py
@@ -30,6 +30,7 @@
     parsing,
     to_offset,
 )
+from pandas._typing import Axis
 from pandas.compat.numpy import function as nv
 from pandas.util._decorators import (
     Appender,
@@ -695,7 +696,14 @@ def insert(self, loc: int, item):
     # NDArray-Like Methods
 
     @Appender(_index_shared_docs["take"] % _index_doc_kwargs)
-    def take(self, indices, axis=0, allow_fill: bool = True, fill_value=None, **kwargs):
+    def take(
+        self,
+        indices,
+        axis: Axis = 0,
+        allow_fill: bool = True,
+        fill_value=None,
+        **kwargs,
+    ):
         nv.validate_take((), kwargs)
         indices = np.asarray(indices, dtype=np.intp)
 
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index 26dd957ff4d57..4b8842227db8c 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -32,11 +32,12 @@
 from pandas._typing import (
     AnyAll,
     AnyArrayLike,
-    AxisInt,
+    Axis,
     DropKeep,
     DtypeObj,
     F,
     IgnoreRaise,
+    IndexLabel,
     Scalar,
     Shape,
     npt,
@@ -2176,7 +2177,7 @@ def _getitem_slice(self: MultiIndex, slobj: slice) -> MultiIndex:
     def take(
         self: MultiIndex,
         indices,
-        axis: AxisInt = 0,
+        axis: Axis = 0,
         allow_fill: bool = True,
         fill_value=None,
         **kwargs,
@@ -2472,7 +2473,10 @@ def cats(level_codes):
         ]
 
     def sortlevel(
-        self, level=0, ascending: bool | list[bool] = True, sort_remaining: bool = True
+        self,
+        level: IndexLabel = 0,
+        ascending: bool | list[bool] = True,
+        sort_remaining: bool = True,
     ) -> tuple[MultiIndex, npt.NDArray[np.intp]]:
         """
         Sort MultiIndex at the requested level.
@@ -2525,9 +2529,13 @@ def sortlevel(
                     (0, 1)],
                    ), array([0, 1]))
         """
-        if isinstance(level, (str, int)):
+        if not is_list_like(level):
             level = [level]
-        level = [self._get_level_number(lev) for lev in level]
+        # error: Item "Hashable" of "Union[Hashable, Sequence[Hashable]]" has
+        # no attribute "__iter__" (not iterable)
+        level = [
+            self._get_level_number(lev) for lev in level  # type: ignore[union-attr]
+        ]
         sortorder = None
 
         # we have a directed ordering via ascending
@@ -3007,7 +3015,7 @@ def _maybe_to_slice(loc):
 
         return _maybe_to_slice(loc) if len(loc) != stop - start else slice(start, stop)
 
-    def get_loc_level(self, key, level=0, drop_level: bool = True):
+    def get_loc_level(self, key, level: IndexLabel = 0, drop_level: bool = True):
         """
         Get location and sliced index for requested label(s)/level(s).
 
diff --git a/pandas/core/missing.py b/pandas/core/missing.py
index 9a55076c71f5f..203260f99e547 100644
--- a/pandas/core/missing.py
+++ b/pandas/core/missing.py
@@ -543,7 +543,9 @@ def _interpolate_scipy_wrapper(
     return new_y
 
 
-def _from_derivatives(xi, yi, x, order=None, der=0, extrapolate: bool = False):
+def _from_derivatives(
+    xi, yi, x, order=None, der: int | list[int] | None = 0, extrapolate: bool = False
+):
     """
     Convenience function for interpolate.BPoly.from_derivatives.
 
@@ -586,7 +588,7 @@ def _from_derivatives(xi, yi, x, order=None, der=0, extrapolate: bool = False):
     return m(x)
 
 
-def _akima_interpolate(xi, yi, x, der=0, axis=0):
+def _akima_interpolate(xi, yi, x, der: int | list[int] | None = 0, axis: AxisInt = 0):
     """
     Convenience function for akima interpolation.
     xi and yi are arrays of values used to approximate some function f,
@@ -630,7 +632,12 @@ def _akima_interpolate(xi, yi, x, der=0, axis=0):
 
 
 def _cubicspline_interpolate(
-    xi, yi, x, axis=0, bc_type: str | tuple[Any, Any] = "not-a-knot", extrapolate=None
+    xi,
+    yi,
+    x,
+    axis: AxisInt = 0,
+    bc_type: str | tuple[Any, Any] = "not-a-knot",
+    extrapolate=None,
 ):
     """
     Convenience function for cubic spline data interpolator.
diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index 8e162a8249fd9..36a3281b7b931 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -872,7 +872,12 @@ def _get_counts_nanvar(
 
 @bottleneck_switch(ddof=1)
 def nanstd(
-    values, *, axis: AxisInt | None = None, skipna: bool = True, ddof=1, mask=None
+    values,
+    *,
+    axis: AxisInt | None = None,
+    skipna: bool = True,
+    ddof: int = 1,
+    mask=None,
 ):
     """
     Compute the standard deviation along given axis while ignoring NaNs
@@ -914,7 +919,12 @@ def nanstd(
 @disallow("M8", "m8")
 @bottleneck_switch(ddof=1)
 def nanvar(
-    values, *, axis: AxisInt | None = None, skipna: bool = True, ddof=1, mask=None
+    values,
+    *,
+    axis: AxisInt | None = None,
+    skipna: bool = True,
+    ddof: int = 1,
+    mask=None,
 ):
     """
     Compute the variance along given axis while ignoring NaNs
diff --git a/pandas/core/ops/__init__.py b/pandas/core/ops/__init__.py
index c2a76b9a9ae19..0dcccdbd3bb8b 100644
--- a/pandas/core/ops/__init__.py
+++ b/pandas/core/ops/__init__.py
@@ -14,6 +14,7 @@
 
 from pandas._libs.ops_dispatch import maybe_dispatch_ufunc_to_dunder_op
 from pandas._typing import (
+    Axis,
     AxisInt,
     Level,
 )
@@ -178,7 +179,7 @@ def flex_method_SERIES(op):
     doc = make_flex_doc(name, "series")
 
     @Appender(doc)
-    def flex_wrapper(self, other, level=None, fill_value=None, axis=0):
+    def flex_wrapper(self, other, level=None, fill_value=None, axis: Axis = 0):
         # validate axis
         if axis is not None:
             self._get_axis_number(axis)
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 0e0aa9e272c89..d752cb0b5b23f 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -28,6 +28,7 @@
 )
 from pandas._typing import (
     AnyArrayLike,
+    Axis,
     AxisInt,
     Frequency,
     IndexLabel,
@@ -152,7 +153,7 @@ def __init__(
         self,
         obj: DataFrame | Series,
         groupby: TimeGrouper,
-        axis: AxisInt = 0,
+        axis: Axis = 0,
         kind=None,
         *,
         group_keys: bool | lib.NoDefault = lib.no_default,
@@ -162,7 +163,9 @@ def __init__(
         self.groupby = groupby
         self.keys = None
         self.sort = True
-        self.axis = axis
+        # error: Incompatible types in assignment (expression has type "Union
+        # [int, Literal['index', 'columns', 'rows']]", variable has type "int")
+        self.axis = axis  # type: ignore[assignment]
         self.kind = kind
         self.squeeze = False
         self.group_keys = group_keys
@@ -926,7 +929,7 @@ def fillna(self, method, limit=None):
     def interpolate(
         self,
         method: QuantileInterpolation = "linear",
-        axis=0,
+        axis: Axis = 0,
         limit=None,
         inplace: bool = False,
         limit_direction: Literal["forward", "backward", "both"] = "forward",
@@ -973,7 +976,7 @@ def asfreq(self, fill_value=None):
 
     def std(
         self,
-        ddof=1,
+        ddof: int = 1,
         numeric_only: bool | lib.NoDefault = lib.no_default,
         *args,
         **kwargs,
@@ -1000,7 +1003,7 @@ def std(
 
     def var(
         self,
-        ddof=1,
+        ddof: int = 1,
         numeric_only: bool | lib.NoDefault = lib.no_default,
         *args,
         **kwargs,
@@ -1597,7 +1600,7 @@ def __init__(
         closed: Literal["left", "right"] | None = None,
         label: Literal["left", "right"] | None = None,
         how: str = "mean",
-        axis=0,
+        axis: Axis = 0,
         fill_method=None,
         limit=None,
         loffset=None,
diff --git a/pandas/core/reshape/concat.py b/pandas/core/reshape/concat.py
index 33f164efdd0c7..3c855b8291303 100644
--- a/pandas/core/reshape/concat.py
+++ b/pandas/core/reshape/concat.py
@@ -390,7 +390,7 @@ class _Concatenator:
     def __init__(
         self,
         objs: Iterable[NDFrame] | Mapping[HashableT, NDFrame],
-        axis=0,
+        axis: Axis = 0,
         join: str = "outer",
         keys=None,
         levels=None,
diff --git a/pandas/core/series.py b/pandas/core/series.py
index b91d5540335f1..25ce6ea739d0e 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -942,7 +942,7 @@ def take(
         result = self._constructor(new_values, index=new_index, fastpath=True)
         return result.__finalize__(self, method="take")
 
-    def _take_with_is_copy(self, indices, axis=0) -> Series:
+    def _take_with_is_copy(self, indices, axis: Axis = 0) -> Series:
         """
         Internal version of the `take` method that sets the `_is_copy`
         attribute to keep track of the parent dataframe (using in indexing
@@ -967,7 +967,7 @@ def _ixs(self, i: int, axis: AxisInt = 0) -> Any:
         """
         return self._values[i]
 
-    def _slice(self, slobj: slice, axis: AxisInt = 0) -> Series:
+    def _slice(self, slobj: slice, axis: Axis = 0) -> Series:
         # axis kwarg is retained for compat with NDFrame method
         #  _slice is *always* positional
         return self._get_values(slobj)
@@ -4784,7 +4784,7 @@ def _reduce(
         op,
         name: str,
         *,
-        axis=0,
+        axis: Axis = 0,
         skipna: bool = True,
         numeric_only=None,
         filter_type=None,
diff --git a/pandas/core/strings/accessor.py b/pandas/core/strings/accessor.py
index 3f1176f42e44c..acefb8c76c0d4 100644
--- a/pandas/core/strings/accessor.py
+++ b/pandas/core/strings/accessor.py
@@ -1133,7 +1133,9 @@ def join(self, sep):
         return self._wrap_result(result)
 
     @forbid_nonstring_types(["bytes"])
-    def contains(self, pat, case: bool = True, flags=0, na=None, regex: bool = True):
+    def contains(
+        self, pat, case: bool = True, flags: int = 0, na=None, regex: bool = True
+    ):
         r"""
         Test if pattern or regex is contained within a string of a Series or Index.
 
@@ -1269,7 +1271,7 @@ def contains(self, pat, case: bool = True, flags=0, na=None, regex: bool = True)
         return self._wrap_result(result, fill_value=na, returns_string=False)
 
     @forbid_nonstring_types(["bytes"])
-    def match(self, pat, case: bool = True, flags=0, na=None):
+    def match(self, pat, case: bool = True, flags: int = 0, na=None):
         """
         Determine if each string starts with a match of a regular expression.
 
@@ -1301,7 +1303,7 @@ def match(self, pat, case: bool = True, flags=0, na=None):
         return self._wrap_result(result, fill_value=na, returns_string=False)
 
     @forbid_nonstring_types(["bytes"])
-    def fullmatch(self, pat, case: bool = True, flags=0, na=None):
+    def fullmatch(self, pat, case: bool = True, flags: int = 0, na=None):
         """
         Determine if each string entirely matches a regular expression.
 
@@ -2232,7 +2234,7 @@ def translate(self, table):
         return self._wrap_result(result)
 
     @forbid_nonstring_types(["bytes"])
-    def count(self, pat, flags=0):
+    def count(self, pat, flags: int = 0):
         r"""
         Count occurrences of pattern in each string of the Series/Index.
 
@@ -2440,7 +2442,7 @@ def endswith(
         return self._wrap_result(result, returns_string=False)
 
     @forbid_nonstring_types(["bytes"])
-    def findall(self, pat, flags=0):
+    def findall(self, pat, flags: int = 0):
         """
         Find all occurrences of pattern or regular expression in the Series/Index.
 
@@ -2661,7 +2663,7 @@ def extract(
         return self._wrap_result(result, name=name)
 
     @forbid_nonstring_types(["bytes"])
-    def extractall(self, pat, flags=0):
+    def extractall(self, pat, flags: int = 0):
         r"""
         Extract capture groups in the regex `pat` as columns in DataFrame.
 
@@ -2774,7 +2776,7 @@ def extractall(self, pat, flags=0):
         }
     )
     @forbid_nonstring_types(["bytes"])
-    def find(self, sub, start=0, end=None):
+    def find(self, sub, start: int = 0, end=None):
         if not isinstance(sub, str):
             msg = f"expected a string object, not {type(sub).__name__}"
             raise TypeError(msg)
@@ -2791,7 +2793,7 @@ def find(self, sub, start=0, end=None):
         }
     )
     @forbid_nonstring_types(["bytes"])
-    def rfind(self, sub, start=0, end=None):
+    def rfind(self, sub, start: int = 0, end=None):
         if not isinstance(sub, str):
             msg = f"expected a string object, not {type(sub).__name__}"
             raise TypeError(msg)
@@ -2858,7 +2860,7 @@ def normalize(self, form):
         }
     )
     @forbid_nonstring_types(["bytes"])
-    def index(self, sub, start=0, end=None):
+    def index(self, sub, start: int = 0, end=None):
         if not isinstance(sub, str):
             msg = f"expected a string object, not {type(sub).__name__}"
             raise TypeError(msg)
@@ -2876,7 +2878,7 @@ def index(self, sub, start=0, end=None):
         }
     )
     @forbid_nonstring_types(["bytes"])
-    def rindex(self, sub, start=0, end=None):
+    def rindex(self, sub, start: int = 0, end=None):
         if not isinstance(sub, str):
             msg = f"expected a string object, not {type(sub).__name__}"
             raise TypeError(msg)
@@ -3345,7 +3347,7 @@ def _get_group_names(regex: re.Pattern) -> list[Hashable]:
     return [names.get(1 + i, i) for i in range(regex.groups)]
 
 
-def str_extractall(arr, pat, flags=0):
+def str_extractall(arr, pat, flags: int = 0):
     regex = re.compile(pat, flags=flags)
     # the regex must contain capture groups.
     if regex.groups == 0:
diff --git a/pandas/core/strings/base.py b/pandas/core/strings/base.py
index ae39526871d63..b5618207ab9d8 100644
--- a/pandas/core/strings/base.py
+++ b/pandas/core/strings/base.py
@@ -39,7 +39,7 @@ def _str_getitem(self, key):
             return self._str_get(key)
 
     @abc.abstractmethod
-    def _str_count(self, pat, flags=0):
+    def _str_count(self, pat, flags: int = 0):
         pass
 
     @abc.abstractmethod
@@ -53,7 +53,7 @@ def _str_pad(
 
     @abc.abstractmethod
     def _str_contains(
-        self, pat, case: bool = True, flags=0, na=None, regex: bool = True
+        self, pat, case: bool = True, flags: int = 0, na=None, regex: bool = True
     ):
         pass
 
@@ -102,15 +102,15 @@ def _str_encode(self, encoding, errors: str = "strict"):
         pass
 
     @abc.abstractmethod
-    def _str_find(self, sub, start=0, end=None):
+    def _str_find(self, sub, start: int = 0, end=None):
         pass
 
     @abc.abstractmethod
-    def _str_rfind(self, sub, start=0, end=None):
+    def _str_rfind(self, sub, start: int = 0, end=None):
         pass
 
     @abc.abstractmethod
-    def _str_findall(self, pat, flags=0):
+    def _str_findall(self, pat, flags: int = 0):
         pass
 
     @abc.abstractmethod
@@ -118,11 +118,11 @@ def _str_get(self, i):
         pass
 
     @abc.abstractmethod
-    def _str_index(self, sub, start=0, end=None):
+    def _str_index(self, sub, start: int = 0, end=None):
         pass
 
     @abc.abstractmethod
-    def _str_rindex(self, sub, start=0, end=None):
+    def _str_rindex(self, sub, start: int = 0, end=None):
         pass
 
     @abc.abstractmethod
diff --git a/pandas/core/strings/object_array.py b/pandas/core/strings/object_array.py
index e9b05f0d4e0e4..3e8cdc12e7216 100644
--- a/pandas/core/strings/object_array.py
+++ b/pandas/core/strings/object_array.py
@@ -101,7 +101,7 @@ def g(x):
                 result = lib.maybe_convert_objects(result)
         return result
 
-    def _str_count(self, pat, flags=0):
+    def _str_count(self, pat, flags: int = 0):
         regex = re.compile(pat, flags=flags)
         f = lambda x: len(regex.findall(x))
         return self._str_map(f, dtype="int64")
@@ -123,7 +123,7 @@ def _str_pad(
         return self._str_map(f)
 
     def _str_contains(
-        self, pat, case: bool = True, flags=0, na=np.nan, regex: bool = True
+        self, pat, case: bool = True, flags: int = 0, na=np.nan, regex: bool = True
     ):
         if regex:
             if not case:
@@ -232,10 +232,10 @@ def _str_encode(self, encoding, errors: str = "strict"):
         f = lambda x: x.encode(encoding, errors=errors)
         return self._str_map(f, dtype=object)
 
-    def _str_find(self, sub, start=0, end=None):
+    def _str_find(self, sub, start: int = 0, end=None):
         return self._str_find_(sub, start, end, side="left")
 
-    def _str_rfind(self, sub, start=0, end=None):
+    def _str_rfind(self, sub, start: int = 0, end=None):
         return self._str_find_(sub, start, end, side="right")
 
     def _str_find_(self, sub, start, end, side):
@@ -252,7 +252,7 @@ def _str_find_(self, sub, start, end, side):
             f = lambda x: getattr(x, method)(sub, start, end)
         return self._str_map(f, dtype="int64")
 
-    def _str_findall(self, pat, flags=0):
+    def _str_findall(self, pat, flags: int = 0):
         regex = re.compile(pat, flags=flags)
         return self._str_map(regex.findall, dtype="object")
 
@@ -266,14 +266,14 @@ def f(x):
 
         return self._str_map(f)
 
-    def _str_index(self, sub, start=0, end=None):
+    def _str_index(self, sub, start: int = 0, end=None):
         if end:
             f = lambda x: x.index(sub, start, end)
         else:
             f = lambda x: x.index(sub, start, end)
         return self._str_map(f, dtype="int64")
 
-    def _str_rindex(self, sub, start=0, end=None):
+    def _str_rindex(self, sub, start: int = 0, end=None):
         if end:
             f = lambda x: x.rindex(sub, start, end)
         else:
diff --git a/pandas/io/json/_normalize.py b/pandas/io/json/_normalize.py
index 627092f632042..03afdcda35021 100644
--- a/pandas/io/json/_normalize.py
+++ b/pandas/io/json/_normalize.py
@@ -485,7 +485,7 @@ def _pull_records(js: dict[str, Any], spec: list | str) -> list:
     meta_vals: DefaultDict = defaultdict(list)
     meta_keys = [sep.join(val) for val in _meta]
 
-    def _recursive_extract(data, path, seen_meta, level=0) -> None:
+    def _recursive_extract(data, path, seen_meta, level: int = 0) -> None:
         if isinstance(data, dict):
             data = [data]
         if len(path) > 1:
diff --git a/pandas/io/parsers/readers.py b/pandas/io/parsers/readers.py
index 754200d2628ad..bacdbbecc3011 100644
--- a/pandas/io/parsers/readers.py
+++ b/pandas/io/parsers/readers.py
@@ -502,21 +502,21 @@ class _DeprecationConfig(NamedTuple):
 
 
 @overload
-def validate_integer(name, val: None, min_val=...) -> None:
+def validate_integer(name, val: None, min_val: int = ...) -> None:
     ...
 
 
 @overload
-def validate_integer(name, val: float, min_val=...) -> int:
+def validate_integer(name, val: float, min_val: int = ...) -> int:
     ...
 
 
 @overload
-def validate_integer(name, val: int | None, min_val=...) -> int | None:
+def validate_integer(name, val: int | None, min_val: int = ...) -> int | None:
     ...
 
 
-def validate_integer(name, val: int | float | None, min_val=0) -> int | None:
+def validate_integer(name, val: int | float | None, min_val: int = 0) -> int | None:
     """
     Checks whether the 'name' parameter for parsing is either
     an integer OR float that can SAFELY be cast to an integer
diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index f8862dd661ba1..201fdff249d67 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -21,6 +21,7 @@
 from pandas._typing import (
     IndexLabel,
     PlottingOrientation,
+    npt,
 )
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import cache_readonly
@@ -1657,7 +1658,14 @@ def _args_adjust(self) -> None:
     # error: Signature of "_plot" incompatible with supertype "MPLPlot"
     @classmethod
     def _plot(  # type: ignore[override]
-        cls, ax: Axes, x, y, w, start=0, log: bool = False, **kwds
+        cls,
+        ax: Axes,
+        x,
+        y,
+        w,
+        start: int | npt.NDArray[np.intp] = 0,
+        log: bool = False,
+        **kwds,
     ):
         return ax.bar(x, y, w, bottom=start, log=log, **kwds)
 
@@ -1783,7 +1791,14 @@ def _start_base(self):
     # error: Signature of "_plot" incompatible with supertype "MPLPlot"
     @classmethod
     def _plot(  # type: ignore[override]
-        cls, ax: Axes, x, y, w, start=0, log: bool = False, **kwds
+        cls,
+        ax: Axes,
+        x,
+        y,
+        w,
+        start: int | npt.NDArray[np.intp] = 0,
+        log: bool = False,
+        **kwds,
     ):
         return ax.barh(x, y, w, left=start, log=log, **kwds)
 
diff --git a/pandas/plotting/_matplotlib/hist.py b/pandas/plotting/_matplotlib/hist.py
index 1bebea357ad68..9aad516d308c3 100644
--- a/pandas/plotting/_matplotlib/hist.py
+++ b/pandas/plotting/_matplotlib/hist.py
@@ -87,16 +87,18 @@ def _calculate_bins(self, data: DataFrame) -> np.ndarray:
         )
         return bins
 
+    # error: Signature of "_plot" incompatible with supertype "LinePlot"
     @classmethod
-    def _plot(
+    def _plot(  # type: ignore[override]
         cls,
         ax,
         y,
         style=None,
-        bins=None,
-        bottom=0,
-        column_num=0,
+        bottom: int | np.ndarray = 0,
+        column_num: int = 0,
         stacking_id=None,
+        *,
+        bins,
         **kwds,
     ):
         if column_num == 0:
@@ -257,7 +259,7 @@ def _grouped_plot(
     sharex: bool = True,
     sharey: bool = True,
     layout=None,
-    rot=0,
+    rot: float = 0,
     ax=None,
     **kwargs,
 ):
@@ -295,12 +297,12 @@ def _grouped_hist(
     column=None,
     by=None,
     ax=None,
-    bins=50,
+    bins: int = 50,
     figsize=None,
     layout=None,
     sharex: bool = False,
     sharey: bool = False,
-    rot=90,
+    rot: float = 90,
     grid: bool = True,
     xlabelsize=None,
     xrot=None,