diff --git a/pandas/_testing/_io.py b/pandas/_testing/_io.py
index edbba9452b50a..95977edb600ad 100644
--- a/pandas/_testing/_io.py
+++ b/pandas/_testing/_io.py
@@ -118,7 +118,7 @@ def round_trip_localpath(writer, reader, path: str | None = None):
     return obj
 
 
-def write_to_compressed(compression, path, data, dest: str = "test"):
+def write_to_compressed(compression, path, data, dest: str = "test") -> None:
     """
     Write data to a compressed file.
 
diff --git a/pandas/arrays/__init__.py b/pandas/arrays/__init__.py
index 32e2afc0eef52..a11755275d00e 100644
--- a/pandas/arrays/__init__.py
+++ b/pandas/arrays/__init__.py
@@ -36,7 +36,7 @@
 ]
 
 
-def __getattr__(name: str):
+def __getattr__(name: str) -> type[NumpyExtensionArray]:
     if name == "PandasArray":
         # GH#53694
         import warnings
diff --git a/pandas/compat/pickle_compat.py b/pandas/compat/pickle_compat.py
index 8282ec25c1d58..4f067d958b799 100644
--- a/pandas/compat/pickle_compat.py
+++ b/pandas/compat/pickle_compat.py
@@ -26,7 +26,7 @@
     from collections.abc import Generator
 
 
-def load_reduce(self):
+def load_reduce(self) -> None:
     stack = self.stack
     args = stack.pop()
     func = stack[-1]
diff --git a/pandas/conftest.py b/pandas/conftest.py
index 10826f50d1fe1..ea59bbfd088a9 100644
--- a/pandas/conftest.py
+++ b/pandas/conftest.py
@@ -491,7 +491,7 @@ def box_with_array(request):
 
 
 @pytest.fixture
-def dict_subclass():
+def dict_subclass() -> type[dict]:
     """
     Fixture for a dictionary subclass.
     """
@@ -504,7 +504,7 @@ def __init__(self, *args, **kwargs) -> None:
 
 
 @pytest.fixture
-def non_dict_mapping_subclass():
+def non_dict_mapping_subclass() -> type[abc.Mapping]:
     """
     Fixture for a non-mapping dictionary subclass.
     """
diff --git a/pandas/core/apply.py b/pandas/core/apply.py
index 6ab2f958b8730..4d6dd8f4fd577 100644
--- a/pandas/core/apply.py
+++ b/pandas/core/apply.py
@@ -54,9 +54,9 @@
 
 if TYPE_CHECKING:
     from collections.abc import (
+        Generator,
         Hashable,
         Iterable,
-        Iterator,
         Sequence,
     )
 
@@ -253,7 +253,7 @@ def transform(self) -> DataFrame | Series:
 
         return result
 
-    def transform_dict_like(self, func):
+    def transform_dict_like(self, func) -> DataFrame:
         """
         Compute transform in the case of a dict-like func
         """
@@ -315,7 +315,7 @@ def compute_list_like(
         op_name: Literal["agg", "apply"],
         selected_obj: Series | DataFrame,
         kwargs: dict[str, Any],
-    ) -> tuple[list[Hashable], list[Any]]:
+    ) -> tuple[list[Hashable] | Index, list[Any]]:
         """
         Compute agg/apply results for like-like input.
 
@@ -330,7 +330,7 @@ def compute_list_like(
 
         Returns
         -------
-        keys : list[hashable]
+        keys : list[Hashable] or Index
             Index labels for result.
         results : list
             Data for result. When aggregating with a Series, this can contain any
@@ -370,12 +370,14 @@ def compute_list_like(
                 new_res = getattr(colg, op_name)(func, *args, **kwargs)
                 results.append(new_res)
                 indices.append(index)
-            keys = selected_obj.columns.take(indices)
+            # error: Incompatible types in assignment (expression has type "Any |
+            # Index", variable has type "list[Any | Callable[..., Any] | str]")
+            keys = selected_obj.columns.take(indices)  # type: ignore[assignment]
 
         return keys, results
 
     def wrap_results_list_like(
-        self, keys: list[Hashable], results: list[Series | DataFrame]
+        self, keys: Iterable[Hashable], results: list[Series | DataFrame]
     ):
         from pandas.core.reshape.concat import concat
 
@@ -772,7 +774,7 @@ def result_columns(self) -> Index:
 
     @property
     @abc.abstractmethod
-    def series_generator(self) -> Iterator[Series]:
+    def series_generator(self) -> Generator[Series, None, None]:
         pass
 
     @abc.abstractmethod
@@ -1014,7 +1016,7 @@ class FrameRowApply(FrameApply):
     axis: AxisInt = 0
 
     @property
-    def series_generator(self):
+    def series_generator(self) -> Generator[Series, None, None]:
         return (self.obj._ixs(i, axis=1) for i in range(len(self.columns)))
 
     @property
@@ -1075,7 +1077,7 @@ def apply_broadcast(self, target: DataFrame) -> DataFrame:
         return result.T
 
     @property
-    def series_generator(self):
+    def series_generator(self) -> Generator[Series, None, None]:
         values = self.values
         values = ensure_wrapped_if_datetimelike(values)
         assert len(values) > 0
diff --git a/pandas/core/arrays/arrow/extension_types.py b/pandas/core/arrays/arrow/extension_types.py
index 3249c1c829546..7814a77a1cdc5 100644
--- a/pandas/core/arrays/arrow/extension_types.py
+++ b/pandas/core/arrays/arrow/extension_types.py
@@ -48,7 +48,7 @@ def __ne__(self, other) -> bool:
     def __hash__(self) -> int:
         return hash((str(self), self.freq))
 
-    def to_pandas_dtype(self):
+    def to_pandas_dtype(self) -> PeriodDtype:
         return PeriodDtype(freq=self.freq)
 
 
@@ -105,7 +105,7 @@ def __ne__(self, other) -> bool:
     def __hash__(self) -> int:
         return hash((str(self), str(self.subtype), self.closed))
 
-    def to_pandas_dtype(self):
+    def to_pandas_dtype(self) -> IntervalDtype:
         return IntervalDtype(self.subtype.to_pandas_dtype(), self.closed)
 
 
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index dae0fb7782791..9f63d1f97c54f 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -2410,7 +2410,7 @@ def _mode(self, dropna: bool = True) -> Categorical:
     # ------------------------------------------------------------------
     # ExtensionArray Interface
 
-    def unique(self):
+    def unique(self) -> Self:
         """
         Return the ``Categorical`` which ``categories`` and ``codes`` are
         unique.
diff --git a/pandas/core/arrays/interval.py b/pandas/core/arrays/interval.py
index 73d4f6f38f102..58ade1ee935ec 100644
--- a/pandas/core/arrays/interval.py
+++ b/pandas/core/arrays/interval.py
@@ -110,7 +110,7 @@
     )
 
 
-IntervalSideT = Union[TimeArrayLike, np.ndarray]
+IntervalSide = Union[TimeArrayLike, np.ndarray]
 IntervalOrNA = Union[Interval, float]
 
 _interval_shared_docs: dict[str, str] = {}
@@ -219,8 +219,8 @@ def ndim(self) -> Literal[1]:
         return 1
 
     # To make mypy recognize the fields
-    _left: IntervalSideT
-    _right: IntervalSideT
+    _left: IntervalSide
+    _right: IntervalSide
     _dtype: IntervalDtype
 
     # ---------------------------------------------------------------------
@@ -237,8 +237,8 @@ def __new__(
         data = extract_array(data, extract_numpy=True)
 
         if isinstance(data, cls):
-            left: IntervalSideT = data._left
-            right: IntervalSideT = data._right
+            left: IntervalSide = data._left
+            right: IntervalSide = data._right
             closed = closed or data.closed
             dtype = IntervalDtype(left.dtype, closed=closed)
         else:
@@ -280,8 +280,8 @@ def __new__(
     @classmethod
     def _simple_new(
         cls,
-        left: IntervalSideT,
-        right: IntervalSideT,
+        left: IntervalSide,
+        right: IntervalSide,
         dtype: IntervalDtype,
     ) -> Self:
         result = IntervalMixin.__new__(cls)
@@ -299,7 +299,7 @@ def _ensure_simple_new_inputs(
         closed: IntervalClosedType | None = None,
         copy: bool = False,
         dtype: Dtype | None = None,
-    ) -> tuple[IntervalSideT, IntervalSideT, IntervalDtype]:
+    ) -> tuple[IntervalSide, IntervalSide, IntervalDtype]:
         """Ensure correctness of input parameters for cls._simple_new."""
         from pandas.core.indexes.base import ensure_index
 
@@ -1031,8 +1031,8 @@ def _concat_same_type(cls, to_concat: Sequence[IntervalArray]) -> Self:
             raise ValueError("Intervals must all be closed on the same side.")
         closed = closed_set.pop()
 
-        left = np.concatenate([interval.left for interval in to_concat])
-        right = np.concatenate([interval.right for interval in to_concat])
+        left: IntervalSide = np.concatenate([interval.left for interval in to_concat])
+        right: IntervalSide = np.concatenate([interval.right for interval in to_concat])
 
         left, right, dtype = cls._ensure_simple_new_inputs(left, right, closed=closed)
 
@@ -1283,7 +1283,7 @@ def _format_space(self) -> str:
     # Vectorized Interval Properties/Attributes
 
     @property
-    def left(self):
+    def left(self) -> Index:
         """
         Return the left endpoints of each Interval in the IntervalArray as an Index.
 
@@ -1303,7 +1303,7 @@ def left(self):
         return Index(self._left, copy=False)
 
     @property
-    def right(self):
+    def right(self) -> Index:
         """
         Return the right endpoints of each Interval in the IntervalArray as an Index.
 
@@ -1855,11 +1855,17 @@ def isin(self, values) -> npt.NDArray[np.bool_]:
         return isin(self.astype(object), values.astype(object))
 
     @property
-    def _combined(self) -> IntervalSideT:
-        left = self.left._values.reshape(-1, 1)
-        right = self.right._values.reshape(-1, 1)
+    def _combined(self) -> IntervalSide:
+        # error: Item "ExtensionArray" of "ExtensionArray | ndarray[Any, Any]"
+        # has no attribute "reshape"  [union-attr]
+        left = self.left._values.reshape(-1, 1)  # type: ignore[union-attr]
+        right = self.right._values.reshape(-1, 1)  # type: ignore[union-attr]
         if needs_i8_conversion(left.dtype):
-            comb = left._concat_same_type([left, right], axis=1)
+            # error: Item "ndarray[Any, Any]" of "Any | ndarray[Any, Any]" has
+            # no attribute "_concat_same_type"
+            comb = left._concat_same_type(  # type: ignore[union-attr]
+                [left, right], axis=1
+            )
         else:
             comb = np.concatenate([left, right], axis=1)
         return comb
diff --git a/pandas/core/arrays/period.py b/pandas/core/arrays/period.py
index a2e4b595c42aa..eeede0ad9e6d2 100644
--- a/pandas/core/arrays/period.py
+++ b/pandas/core/arrays/period.py
@@ -948,7 +948,7 @@ def _check_timedeltalike_freq_compat(self, other):
         return lib.item_from_zerodim(delta)
 
 
-def raise_on_incompatible(left, right):
+def raise_on_incompatible(left, right) -> IncompatibleFrequency:
     """
     Helper function to render a consistent error message when raising
     IncompatibleFrequency.
@@ -1089,7 +1089,7 @@ def validate_dtype_freq(dtype, freq: timedelta | str | None) -> BaseOffset:
 
 
 def validate_dtype_freq(
-    dtype, freq: BaseOffsetT | timedelta | str | None
+    dtype, freq: BaseOffsetT | BaseOffset | timedelta | str | None
 ) -> BaseOffsetT:
     """
     If both a dtype and a freq are available, ensure they match.  If only
@@ -1110,10 +1110,7 @@ def validate_dtype_freq(
     IncompatibleFrequency : mismatch between dtype and freq
     """
     if freq is not None:
-        # error: Incompatible types in assignment (expression has type
-        # "BaseOffset", variable has type "Union[BaseOffsetT, timedelta,
-        # str, None]")
-        freq = to_offset(freq)  # type: ignore[assignment]
+        freq = to_offset(freq)
 
     if dtype is not None:
         dtype = pandas_dtype(dtype)
diff --git a/pandas/core/arrays/sparse/array.py b/pandas/core/arrays/sparse/array.py
index e38fa0a3bdae5..00cbe1286c195 100644
--- a/pandas/core/arrays/sparse/array.py
+++ b/pandas/core/arrays/sparse/array.py
@@ -702,7 +702,9 @@ def npoints(self) -> int:
         """
         return self.sp_index.npoints
 
-    def isna(self):
+    # error: Return type "SparseArray" of "isna" incompatible with return type
+    # "ndarray[Any, Any] | ExtensionArraySupportsAnyAll" in supertype "ExtensionArray"
+    def isna(self) -> Self:  # type: ignore[override]
         # If null fill value, we want SparseDtype[bool, true]
         # to preserve the same memory usage.
         dtype = SparseDtype(bool, self._null_fill_value)
@@ -1421,7 +1423,7 @@ def all(self, axis=None, *args, **kwargs):
 
         return values.all()
 
-    def any(self, axis: AxisInt = 0, *args, **kwargs):
+    def any(self, axis: AxisInt = 0, *args, **kwargs) -> bool:
         """
         Tests whether at least one of elements evaluate True
 
diff --git a/pandas/core/arrays/string_.py b/pandas/core/arrays/string_.py
index 72ba95e5fa258..c90127c0e9812 100644
--- a/pandas/core/arrays/string_.py
+++ b/pandas/core/arrays/string_.py
@@ -59,6 +59,7 @@
         NumpySorter,
         NumpyValueArrayLike,
         Scalar,
+        Self,
         npt,
         type_t,
     )
@@ -135,7 +136,7 @@ def type(self) -> type[str]:
         return str
 
     @classmethod
-    def construct_from_string(cls, string):
+    def construct_from_string(cls, string) -> Self:
         """
         Construct a StringDtype from a string.
 
diff --git a/pandas/core/arrays/string_arrow.py b/pandas/core/arrays/string_arrow.py
index cc3bc5900c4c2..f438f75707265 100644
--- a/pandas/core/arrays/string_arrow.py
+++ b/pandas/core/arrays/string_arrow.py
@@ -53,6 +53,8 @@
         npt,
     )
 
+    from pandas import Series
+
 
 ArrowStringScalarOrNAT = Union[str, libmissing.NAType]
 
@@ -547,7 +549,7 @@ def _cmp_method(self, other, op):
         result = super()._cmp_method(other, op)
         return result.to_numpy(np.bool_, na_value=False)
 
-    def value_counts(self, dropna: bool = True):
+    def value_counts(self, dropna: bool = True) -> Series:
         from pandas import Series
 
         result = super().value_counts(dropna)
diff --git a/pandas/core/computation/expr.py b/pandas/core/computation/expr.py
index 2f94856702465..4770f403b1bdb 100644
--- a/pandas/core/computation/expr.py
+++ b/pandas/core/computation/expr.py
@@ -12,6 +12,7 @@
 import tokenize
 from typing import (
     Callable,
+    ClassVar,
     TypeVar,
 )
 
@@ -349,8 +350,8 @@ class BaseExprVisitor(ast.NodeVisitor):
     preparser : callable
     """
 
-    const_type: type[Term] = Constant
-    term_type = Term
+    const_type: ClassVar[type[Term]] = Constant
+    term_type: ClassVar[type[Term]] = Term
 
     binary_ops = CMP_OPS_SYMS + BOOL_OPS_SYMS + ARITH_OPS_SYMS
     binary_op_nodes = (
@@ -540,7 +541,7 @@ def visit_UnaryOp(self, node, **kwargs):
         operand = self.visit(node.operand)
         return op(operand)
 
-    def visit_Name(self, node, **kwargs):
+    def visit_Name(self, node, **kwargs) -> Term:
         return self.term_type(node.id, self.env, **kwargs)
 
     # TODO(py314): deprecated since Python 3.8. Remove after Python 3.14 is min
@@ -555,11 +556,11 @@ def visit_Constant(self, node, **kwargs) -> Term:
         return self.const_type(node.value, self.env)
 
     # TODO(py314): deprecated since Python 3.8. Remove after Python 3.14 is min
-    def visit_Str(self, node, **kwargs):
+    def visit_Str(self, node, **kwargs) -> Term:
         name = self.env.add_tmp(node.s)
         return self.term_type(name, self.env)
 
-    def visit_List(self, node, **kwargs):
+    def visit_List(self, node, **kwargs) -> Term:
         name = self.env.add_tmp([self.visit(e)(self.env) for e in node.elts])
         return self.term_type(name, self.env)
 
@@ -569,7 +570,7 @@ def visit_Index(self, node, **kwargs):
         """df.index[4]"""
         return self.visit(node.value)
 
-    def visit_Subscript(self, node, **kwargs):
+    def visit_Subscript(self, node, **kwargs) -> Term:
         from pandas import eval as pd_eval
 
         value = self.visit(node.value)
@@ -589,7 +590,7 @@ def visit_Subscript(self, node, **kwargs):
         name = self.env.add_tmp(v)
         return self.term_type(name, env=self.env)
 
-    def visit_Slice(self, node, **kwargs):
+    def visit_Slice(self, node, **kwargs) -> slice:
         """df.index[slice(4,6)]"""
         lower = node.lower
         if lower is not None:
diff --git a/pandas/core/computation/ops.py b/pandas/core/computation/ops.py
index 852bfae1cc79a..95ac20ba39edc 100644
--- a/pandas/core/computation/ops.py
+++ b/pandas/core/computation/ops.py
@@ -617,5 +617,5 @@ def __init__(self, name: str) -> None:
         self.name = name
         self.func = getattr(np, name)
 
-    def __call__(self, *args):
+    def __call__(self, *args) -> MathCall:
         return MathCall(self, args)
diff --git a/pandas/core/computation/pytables.py b/pandas/core/computation/pytables.py
index 77d8d79506258..138a3ee42f686 100644
--- a/pandas/core/computation/pytables.py
+++ b/pandas/core/computation/pytables.py
@@ -10,6 +10,7 @@
 from typing import (
     TYPE_CHECKING,
     Any,
+    ClassVar,
 )
 
 import numpy as np
@@ -40,7 +41,10 @@
 )
 
 if TYPE_CHECKING:
-    from pandas._typing import npt
+    from pandas._typing import (
+        Self,
+        npt,
+    )
 
 
 class PyTablesScope(_scope.Scope):
@@ -283,7 +287,7 @@ def __repr__(self) -> str:
             return "Filter: Not Initialized"
         return pprint_thing(f"[Filter : [{self.filter[0]}] -> [{self.filter[1]}]")
 
-    def invert(self):
+    def invert(self) -> Self:
         """invert the filter"""
         if self.filter is not None:
             self.filter = (
@@ -297,7 +301,8 @@ def format(self):
         """return the actual filter format"""
         return [self.filter]
 
-    def evaluate(self):
+    # error: Signature of "evaluate" incompatible with supertype "BinOp"
+    def evaluate(self) -> Self | None:  # type: ignore[override]
         if not self.is_valid:
             raise ValueError(f"query term is not valid [{self}]")
 
@@ -336,7 +341,8 @@ class JointFilterBinOp(FilterBinOp):
     def format(self):
         raise NotImplementedError("unable to collapse Joint Filters")
 
-    def evaluate(self):
+    # error: Signature of "evaluate" incompatible with supertype "BinOp"
+    def evaluate(self) -> Self:  # type: ignore[override]
         return self
 
 
@@ -357,7 +363,8 @@ def format(self):
         """return the actual ne format"""
         return self.condition
 
-    def evaluate(self):
+    # error: Signature of "evaluate" incompatible with supertype "BinOp"
+    def evaluate(self) -> Self | None:  # type: ignore[override]
         if not self.is_valid:
             raise ValueError(f"query term is not valid [{self}]")
 
@@ -385,7 +392,8 @@ def evaluate(self):
 
 
 class JointConditionBinOp(ConditionBinOp):
-    def evaluate(self):
+    # error: Signature of "evaluate" incompatible with supertype "BinOp"
+    def evaluate(self) -> Self:  # type: ignore[override]
         self.condition = f"({self.lhs.condition} {self.op} {self.rhs.condition})"
         return self
 
@@ -410,8 +418,8 @@ def prune(self, klass):
 
 
 class PyTablesExprVisitor(BaseExprVisitor):
-    const_type = Constant
-    term_type = Term
+    const_type: ClassVar[type[ops.Term]] = Constant
+    term_type: ClassVar[type[Term]] = Term
 
     def __init__(self, env, engine, parser, **kwargs) -> None:
         super().__init__(env, engine, parser)
@@ -423,13 +431,15 @@ def __init__(self, env, engine, parser, **kwargs) -> None:
                 lambda node, bin_op=bin_op: partial(BinOp, bin_op, **kwargs),
             )
 
-    def visit_UnaryOp(self, node, **kwargs):
+    def visit_UnaryOp(self, node, **kwargs) -> ops.Term | UnaryOp | None:
         if isinstance(node.op, (ast.Not, ast.Invert)):
             return UnaryOp("~", self.visit(node.operand))
         elif isinstance(node.op, ast.USub):
             return self.const_type(-self.visit(node.operand).value, self.env)
         elif isinstance(node.op, ast.UAdd):
             raise NotImplementedError("Unary addition not supported")
+        # TODO: return None might never be reached
+        return None
 
     def visit_Index(self, node, **kwargs):
         return self.visit(node.value).value
@@ -440,7 +450,7 @@ def visit_Assign(self, node, **kwargs):
         )
         return self.visit(cmpr)
 
-    def visit_Subscript(self, node, **kwargs):
+    def visit_Subscript(self, node, **kwargs) -> ops.Term:
         # only allow simple subscripts
 
         value = self.visit(node.value)
diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index e3e38961a200b..66f00a7e9a805 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -77,6 +77,7 @@
         DtypeObj,
         IntervalClosedType,
         Ordered,
+        Self,
         npt,
         type_t,
     )
@@ -973,7 +974,7 @@ class PeriodDtype(PeriodDtypeBase, PandasExtensionDtype):
     __hash__ = PeriodDtypeBase.__hash__
     _freq: BaseOffset
 
-    def __new__(cls, freq):
+    def __new__(cls, freq) -> PeriodDtype:  # noqa: PYI034
         """
         Parameters
         ----------
@@ -1004,11 +1005,11 @@ def __new__(cls, freq):
         u._freq = freq
         return u
 
-    def __reduce__(self):
+    def __reduce__(self) -> tuple[type_t[Self], tuple[str_type]]:
         return type(self), (self.name,)
 
     @property
-    def freq(self):
+    def freq(self) -> BaseOffset:
         """
         The frequency object of this PeriodDtype.
 
@@ -1729,7 +1730,7 @@ def fill_value(self):
         """
         return self._fill_value
 
-    def _check_fill_value(self):
+    def _check_fill_value(self) -> None:
         if not lib.is_scalar(self._fill_value):
             raise ValueError(
                 f"fill_value must be a scalar. Got {self._fill_value} instead"
diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index 9c04e57be36fc..f551716772f61 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -401,7 +401,7 @@ def is_sequence(obj) -> bool:
         return False
 
 
-def is_dataclass(item):
+def is_dataclass(item) -> bool:
     """
     Checks if the object is a data-class instance
 
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 6fae6273be998..4bfa8a4415785 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -12247,8 +12247,7 @@ def _to_dict_of_blocks(self, copy: bool = True):
         """
         mgr = self._mgr
         # convert to BlockManager if needed -> this way support ArrayManager as well
-        mgr = mgr_to_mgr(mgr, "block")
-        mgr = cast(BlockManager, mgr)
+        mgr = cast(BlockManager, mgr_to_mgr(mgr, "block"))
         return {
             k: self._constructor_from_mgr(v, axes=v.axes).__finalize__(self)
             for k, v, in mgr.to_dict(copy=copy).items()
diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 8bef167b747e2..dbabd04a87c36 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -721,8 +721,10 @@ def nunique(self, dropna: bool = True) -> Series | DataFrame:
         return self._reindex_output(result, fill_value=0)
 
     @doc(Series.describe)
-    def describe(self, **kwargs):
-        return super().describe(**kwargs)
+    def describe(self, percentiles=None, include=None, exclude=None) -> Series:
+        return super().describe(
+            percentiles=percentiles, include=include, exclude=exclude
+        )
 
     def value_counts(
         self,
@@ -770,6 +772,7 @@ def value_counts(
         mask = ids != -1
         ids, val = ids[mask], val[mask]
 
+        lab: Index | np.ndarray
         if bins is None:
             lab, lev = algorithms.factorize(val, sort=True)
             llab = lambda lab, inc: lab[inc]
@@ -1152,7 +1155,7 @@ def alt(obj):
 
     @property
     @doc(Series.plot.__doc__)
-    def plot(self):
+    def plot(self) -> GroupByPlot:
         result = GroupByPlot(self)
         return result
 
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 7f77c0c4826fb..11c97e30ab5cd 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -143,6 +143,7 @@ class providing the base-class of operations.
 if TYPE_CHECKING:
     from typing import Any
 
+    from pandas.core.resample import Resampler
     from pandas.core.window import (
         ExpandingGroupby,
         ExponentialMovingWindowGroupby,
@@ -2094,7 +2095,7 @@ def _obj_1d_constructor(self) -> Callable:
     @final
     @Substitution(name="groupby")
     @Substitution(see_also=_common_see_also)
-    def any(self, skipna: bool = True):
+    def any(self, skipna: bool = True) -> NDFrameT:
         """
         Return True if any value in the group is truthful, else False.
 
@@ -2150,7 +2151,7 @@ def any(self, skipna: bool = True):
     @final
     @Substitution(name="groupby")
     @Substitution(see_also=_common_see_also)
-    def all(self, skipna: bool = True):
+    def all(self, skipna: bool = True) -> NDFrameT:
         """
         Return True if all values in the group are truthful, else False.
 
@@ -2399,7 +2400,7 @@ def mean(
             return result.__finalize__(self.obj, method="groupby")
 
     @final
-    def median(self, numeric_only: bool = False):
+    def median(self, numeric_only: bool = False) -> NDFrameT:
         """
         Compute median of groups, excluding missing values.
 
@@ -2828,7 +2829,7 @@ def _value_counts(
         return result.__finalize__(self.obj, method="value_counts")
 
     @final
-    def sem(self, ddof: int = 1, numeric_only: bool = False):
+    def sem(self, ddof: int = 1, numeric_only: bool = False) -> NDFrameT:
         """
         Compute standard error of the mean of groups, excluding missing values.
 
@@ -3119,7 +3120,7 @@ def sum(
         2   30   72"""
         ),
     )
-    def prod(self, numeric_only: bool = False, min_count: int = 0):
+    def prod(self, numeric_only: bool = False, min_count: int = 0) -> NDFrameT:
         return self._agg_general(
             numeric_only=numeric_only, min_count=min_count, alias="prod", npfunc=np.prod
         )
@@ -3261,7 +3262,7 @@ def max(
             )
 
     @final
-    def first(self, numeric_only: bool = False, min_count: int = -1):
+    def first(self, numeric_only: bool = False, min_count: int = -1) -> NDFrameT:
         """
         Compute the first non-null entry of each column.
 
@@ -3331,7 +3332,7 @@ def first(x: Series):
         )
 
     @final
-    def last(self, numeric_only: bool = False, min_count: int = -1):
+    def last(self, numeric_only: bool = False, min_count: int = -1) -> NDFrameT:
         """
         Compute the last non-null entry of each column.
 
@@ -3518,7 +3519,7 @@ def describe(
         return result
 
     @final
-    def resample(self, rule, *args, **kwargs):
+    def resample(self, rule, *args, **kwargs) -> Resampler:
         """
         Provide resampling when using a TimeGrouper.
 
diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py
index add6c3ac4ec20..c51c17e04796a 100644
--- a/pandas/core/groupby/grouper.py
+++ b/pandas/core/groupby/grouper.py
@@ -289,12 +289,12 @@ def __init__(
         self.dropna = dropna
 
         self._grouper_deprecated = None
-        self._indexer_deprecated = None
+        self._indexer_deprecated: npt.NDArray[np.intp] | None = None
         self._obj_deprecated = None
         self._gpr_index = None
         self.binner = None
         self._grouper = None
-        self._indexer = None
+        self._indexer: npt.NDArray[np.intp] | None = None
 
     def _get_grouper(
         self, obj: NDFrameT, validate: bool = True
@@ -329,8 +329,8 @@ def _get_grouper(
 
     @final
     def _set_grouper(
-        self, obj: NDFrame, sort: bool = False, *, gpr_index: Index | None = None
-    ):
+        self, obj: NDFrameT, sort: bool = False, *, gpr_index: Index | None = None
+    ) -> tuple[NDFrameT, Index, npt.NDArray[np.intp] | None]:
         """
         given an object and the specifications, setup the internal grouper
         for this particular specification
@@ -350,8 +350,6 @@ def _set_grouper(
         """
         assert obj is not None
 
-        indexer = None
-
         if self.key is not None and self.level is not None:
             raise ValueError("The Grouper cannot specify both a key and a level!")
 
@@ -398,6 +396,7 @@ def _set_grouper(
                         raise ValueError(f"The level {level} is not valid")
 
         # possibly sort
+        indexer: npt.NDArray[np.intp] | None = None
         if (self.sort or sort) and not ax.is_monotonic_increasing:
             # use stable sort to support first, last, nth
             # TODO: why does putting na_position="first" fix datetimelike cases?
diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index 71525c8c1a223..607059e5183ec 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -77,7 +77,7 @@
     from pandas.core.generic import NDFrame
 
 
-def check_result_array(obj, dtype):
+def check_result_array(obj, dtype) -> None:
     # Our operation is supposed to be an aggregation/reduction. If
     #  it returns an ndarray, this likely means an invalid operation has
     #  been passed. See test_apply_without_aggregation, test_agg_must_agg
diff --git a/pandas/core/indexes/accessors.py b/pandas/core/indexes/accessors.py
index 5134c506b8c61..af8fa441f8b3f 100644
--- a/pandas/core/indexes/accessors.py
+++ b/pandas/core/indexes/accessors.py
@@ -227,7 +227,7 @@ def to_pydatetime(self):
         )
         return cast(ArrowExtensionArray, self._parent.array)._dt_to_pydatetime()
 
-    def isocalendar(self):
+    def isocalendar(self) -> DataFrame:
         from pandas import DataFrame
 
         result = (
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index da16c3c54995a..6a397862712de 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -1121,7 +1121,7 @@ def take(
         allow_fill: bool = True,
         fill_value=None,
         **kwargs,
-    ):
+    ) -> Self:
         if kwargs:
             nv.validate_take((), kwargs)
         if is_scalar(indices):
@@ -1206,7 +1206,7 @@ def _maybe_disallow_fill(self, allow_fill: bool, fill_value, indices) -> bool:
         """
 
     @Appender(_index_shared_docs["repeat"] % _index_doc_kwargs)
-    def repeat(self, repeats, axis: None = None):
+    def repeat(self, repeats, axis: None = None) -> Self:
         repeats = ensure_platform_int(repeats)
         nv.validate_repeat((), {"axis": axis})
         res_values = self._values.repeat(repeats)
@@ -3527,7 +3527,7 @@ def _intersection_via_get_indexer(
 
         Returns
         -------
-        np.ndarray or ExtensionArray
+        np.ndarray or ExtensionArray or MultiIndex
             The returned array will be unique.
         """
         left_unique = self.unique()
@@ -3544,6 +3544,7 @@ def _intersection_via_get_indexer(
             # unnecessary in the case with sort=None bc we will sort later
             taker = np.sort(taker)
 
+        result: MultiIndex | ExtensionArray | np.ndarray
         if isinstance(left_unique, ABCMultiIndex):
             result = left_unique.take(taker)
         else:
@@ -4445,7 +4446,7 @@ def _reindex_non_unique(
 
         indexer, missing = self.get_indexer_non_unique(target)
         check = indexer != -1
-        new_labels = self.take(indexer[check])
+        new_labels: Index | np.ndarray = self.take(indexer[check])
         new_indexer = None
 
         if len(missing):
@@ -5005,7 +5006,7 @@ def _wrap_joined_index(
             # expected "Self")
             mask = lidx == -1
             join_idx = self.take(lidx)
-            right = other.take(ridx)
+            right = cast("MultiIndex", other.take(ridx))
             join_index = join_idx.putmask(mask, right)._sort_levels_monotonic()
             return join_index.set_names(name)  # type: ignore[return-value]
         else:
@@ -6990,7 +6991,7 @@ def infer_objects(self, copy: bool = True) -> Index:
             result._references.add_index_reference(result)
         return result
 
-    def diff(self, periods: int = 1):
+    def diff(self, periods: int = 1) -> Self:
         """
         Computes the difference between consecutive values in the Index object.
 
@@ -7018,7 +7019,7 @@ def diff(self, periods: int = 1):
         """
         return self._constructor(self.to_series().diff(periods))
 
-    def round(self, decimals: int = 0):
+    def round(self, decimals: int = 0) -> Self:
         """
         Round each value in the Index to the given number of decimals.
 
diff --git a/pandas/core/indexes/frozen.py b/pandas/core/indexes/frozen.py
index 2d1d2a81a8a71..9d528d34e3684 100644
--- a/pandas/core/indexes/frozen.py
+++ b/pandas/core/indexes/frozen.py
@@ -8,12 +8,18 @@
 """
 from __future__ import annotations
 
-from typing import NoReturn
+from typing import (
+    TYPE_CHECKING,
+    NoReturn,
+)
 
 from pandas.core.base import PandasObject
 
 from pandas.io.formats.printing import pprint_thing
 
+if TYPE_CHECKING:
+    from pandas._typing import Self
+
 
 class FrozenList(PandasObject, list):
     """
@@ -72,7 +78,7 @@ def __getitem__(self, n):
             return type(self)(super().__getitem__(n))
         return super().__getitem__(n)
 
-    def __radd__(self, other):
+    def __radd__(self, other) -> Self:
         if isinstance(other, tuple):
             other = list(other)
         return type(self)(other + list(self))
@@ -84,7 +90,7 @@ def __eq__(self, other: object) -> bool:
 
     __req__ = __eq__
 
-    def __mul__(self, other):
+    def __mul__(self, other) -> Self:
         return type(self)(super().__mul__(other))
 
     __imul__ = __mul__
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index c2dd16e550f6f..144045d40a086 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -1030,7 +1030,7 @@ def levshape(self) -> Shape:
     # Codes Methods
 
     @property
-    def codes(self):
+    def codes(self) -> FrozenList:
         return self._codes
 
     def _set_codes(
@@ -1074,7 +1074,9 @@ def _set_codes(
 
         self._reset_cache()
 
-    def set_codes(self, codes, *, level=None, verify_integrity: bool = True):
+    def set_codes(
+        self, codes, *, level=None, verify_integrity: bool = True
+    ) -> MultiIndex:
         """
         Set new codes on MultiIndex. Defaults to returning new index.
 
@@ -1199,7 +1201,7 @@ def copy(  # type: ignore[override]
         names=None,
         deep: bool = False,
         name=None,
-    ):
+    ) -> Self:
         """
         Make a copy of this object.
 
@@ -1262,7 +1264,7 @@ def __array__(self, dtype=None) -> np.ndarray:
         """the array interface, return my values"""
         return self.values
 
-    def view(self, cls=None):
+    def view(self, cls=None) -> Self:
         """this is defined as a copy with the same identity"""
         result = self.copy()
         result._id = self._id
@@ -1659,7 +1661,8 @@ def _get_level_values(self, level: int, unique: bool = False) -> Index:
         filled = algos.take_nd(lev._values, level_codes, fill_value=lev._na_value)
         return lev._shallow_copy(filled, name=name)
 
-    def get_level_values(self, level):
+    # error: Signature of "get_level_values" incompatible with supertype "Index"
+    def get_level_values(self, level) -> Index:  # type: ignore[override]
         """
         Return vector of label values for requested level.
 
@@ -3296,7 +3299,7 @@ def convert_indexer(start, stop, step, indexer=indexer, codes=level_codes):
                 raise KeyError(key)
             return slice(start, end)
 
-    def get_locs(self, seq):
+    def get_locs(self, seq) -> npt.NDArray[np.intp]:
         """
         Get location for a sequence of labels.
 
diff --git a/pandas/core/indexes/range.py b/pandas/core/indexes/range.py
index 9576997af6641..aeb7bb1813fef 100644
--- a/pandas/core/indexes/range.py
+++ b/pandas/core/indexes/range.py
@@ -407,7 +407,7 @@ def inferred_type(self) -> str:
     # Indexing Methods
 
     @doc(Index.get_loc)
-    def get_loc(self, key):
+    def get_loc(self, key) -> int:
         if is_integer(key) or (is_float(key) and key.is_integer()):
             new_key = int(key)
             try:
@@ -1107,14 +1107,16 @@ def _arith_method(self, other, op):
             # test_arithmetic_explicit_conversions
             return super()._arith_method(other, op)
 
-    def take(
+    # error: Return type "Index" of "take" incompatible with return type
+    # "RangeIndex" in supertype "Index"
+    def take(  # type: ignore[override]
         self,
         indices,
         axis: Axis = 0,
         allow_fill: bool = True,
         fill_value=None,
         **kwargs,
-    ):
+    ) -> Index:
         if kwargs:
             nv.validate_take((), kwargs)
         if is_scalar(indices):
diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index 97578e3f1668b..871e5817fdf0d 100644
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -82,6 +82,7 @@
         Axis,
         AxisInt,
         Self,
+        npt,
     )
 
     from pandas import (
@@ -1384,7 +1385,7 @@ def _getitem_axis(self, key, axis: AxisInt):
             # nested tuple slicing
             if is_nested_tuple(key, labels):
                 locs = labels.get_locs(key)
-                indexer = [slice(None)] * self.ndim
+                indexer: list[slice | npt.NDArray[np.intp]] = [slice(None)] * self.ndim
                 indexer[axis] = locs
                 return self.obj.iloc[tuple(indexer)]
 
diff --git a/pandas/core/internals/array_manager.py b/pandas/core/internals/array_manager.py
index 14969425e75a7..b4e3fdb78b77b 100644
--- a/pandas/core/internals/array_manager.py
+++ b/pandas/core/internals/array_manager.py
@@ -1103,7 +1103,7 @@ def _verify_integrity(self) -> None:
     def _normalize_axis(axis):
         return axis
 
-    def make_empty(self, axes=None) -> SingleArrayManager:
+    def make_empty(self, axes=None) -> Self:
         """Return an empty ArrayManager with index/array of length 0"""
         if axes is None:
             axes = [Index([], dtype=object)]
diff --git a/pandas/core/internals/blocks.py b/pandas/core/internals/blocks.py
index 43f4f527afc3a..61aa8549a6790 100644
--- a/pandas/core/internals/blocks.py
+++ b/pandas/core/internals/blocks.py
@@ -2126,8 +2126,9 @@ def is_view(self) -> bool:
         """Extension arrays are never treated as views."""
         return False
 
+    # error: Cannot override writeable attribute with read-only property
     @cache_readonly
-    def is_numeric(self):
+    def is_numeric(self) -> bool:  # type: ignore[override]
         return self.values.dtype._is_numeric
 
     def _slice(
diff --git a/pandas/core/internals/construction.py b/pandas/core/internals/construction.py
index 3b9e546a99b32..6f30bc650aa36 100644
--- a/pandas/core/internals/construction.py
+++ b/pandas/core/internals/construction.py
@@ -193,7 +193,7 @@ def rec_array_to_mgr(
     return mgr
 
 
-def mgr_to_mgr(mgr, typ: str, copy: bool = True):
+def mgr_to_mgr(mgr, typ: str, copy: bool = True) -> Manager:
     """
     Convert to specific type of Manager. Does not copy if the type is already
     correct. Does not guarantee a copy otherwise. `copy` keyword only controls
diff --git a/pandas/core/internals/managers.py b/pandas/core/internals/managers.py
index b315a318a9a0a..4cb7b610074ba 100644
--- a/pandas/core/internals/managers.py
+++ b/pandas/core/internals/managers.py
@@ -93,6 +93,8 @@
         npt,
     )
 
+    from pandas.api.extensions import ExtensionArray
+
 
 class BaseBlockManager(DataManager):
     """
@@ -1046,7 +1048,7 @@ def iset(
         value: ArrayLike,
         inplace: bool = False,
         refs: BlockValuesRefs | None = None,
-    ):
+    ) -> None:
         """
         Set new item in-place. Does not consolidate. Adds new Block if not
         contained in the current set of items
@@ -1870,7 +1872,7 @@ def __getstate__(self):
         # compatibility with 0.13.1.
         return axes_array, block_values, block_items, extra_state
 
-    def __setstate__(self, state):
+    def __setstate__(self, state) -> None:
         def unpickle_block(values, mgr_locs, ndim: int) -> Block:
             # TODO(EA2D): ndim would be unnecessary with 2D EAs
             # older pickles may store e.g. DatetimeIndex instead of DatetimeArray
@@ -1959,7 +1961,7 @@ def internal_values(self):
         """The array that Series._values returns"""
         return self._block.values
 
-    def array_values(self):
+    def array_values(self) -> ExtensionArray:
         """The array that Series.array returns"""
         return self._block.array_values
 
diff --git a/pandas/core/missing.py b/pandas/core/missing.py
index 58b0e2907b8ce..d275445983b6f 100644
--- a/pandas/core/missing.py
+++ b/pandas/core/missing.py
@@ -12,6 +12,7 @@
     Any,
     Literal,
     cast,
+    overload,
 )
 
 import numpy as np
@@ -124,9 +125,33 @@ def mask_missing(arr: ArrayLike, values_to_mask) -> npt.NDArray[np.bool_]:
     return mask
 
 
-def clean_fill_method(method: str, allow_nearest: bool = False):
+@overload
+def clean_fill_method(
+    method: Literal["ffill", "pad", "bfill", "backfill"],
+    *,
+    allow_nearest: Literal[False] = ...,
+) -> Literal["pad", "backfill"]:
+    ...
+
+
+@overload
+def clean_fill_method(
+    method: Literal["ffill", "pad", "bfill", "backfill", "nearest"],
+    *,
+    allow_nearest: Literal[True],
+) -> Literal["pad", "backfill", "nearest"]:
+    ...
+
+
+def clean_fill_method(
+    method: Literal["ffill", "pad", "bfill", "backfill", "nearest"],
+    *,
+    allow_nearest: bool = False,
+) -> Literal["pad", "backfill", "nearest"]:
     if isinstance(method, str):
-        method = method.lower()
+        # error: Incompatible types in assignment (expression has type "str", variable
+        # has type "Literal['ffill', 'pad', 'bfill', 'backfill', 'nearest']")
+        method = method.lower()  # type: ignore[assignment]
         if method == "ffill":
             method = "pad"
         elif method == "bfill":
@@ -252,7 +277,9 @@ def validate_limit_area(limit_area: str | None) -> Literal["inside", "outside"]
     return limit_area  # type: ignore[return-value]
 
 
-def infer_limit_direction(limit_direction, method):
+def infer_limit_direction(
+    limit_direction: Literal["backward", "forward", "both"] | None, method: str
+) -> Literal["backward", "forward", "both"]:
     # Set `limit_direction` depending on `method`
     if limit_direction is None:
         if method in ("backfill", "bfill"):
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index e45cff0b0679f..5ff18d8a25e36 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -1676,6 +1676,8 @@ def _gotitem(self, key, ndim, subset=None):
 
 
 class DatetimeIndexResampler(Resampler):
+    ax: DatetimeIndex
+
     @property
     def _resampler_for_grouping(self):
         return DatetimeIndexResamplerGroupby
@@ -1807,7 +1809,11 @@ def _wrap_result(self, result):
         return result
 
 
-class DatetimeIndexResamplerGroupby(_GroupByMixin, DatetimeIndexResampler):
+# error: Definition of "ax" in base class "_GroupByMixin" is incompatible
+# with definition in base class "DatetimeIndexResampler"
+class DatetimeIndexResamplerGroupby(  # type: ignore[misc]
+    _GroupByMixin, DatetimeIndexResampler
+):
     """
     Provides a resample of a groupby implementation
     """
@@ -1818,6 +1824,10 @@ def _resampler_cls(self):
 
 
 class PeriodIndexResampler(DatetimeIndexResampler):
+    # error: Incompatible types in assignment (expression has type "PeriodIndex", base
+    # class "DatetimeIndexResampler" defined the type as "DatetimeIndex")
+    ax: PeriodIndex  # type: ignore[assignment]
+
     @property
     def _resampler_for_grouping(self):
         return PeriodIndexResamplerGroupby
@@ -1924,7 +1934,11 @@ def _upsample(self, method, limit: int | None = None, fill_value=None):
         return self._wrap_result(new_obj)
 
 
-class PeriodIndexResamplerGroupby(_GroupByMixin, PeriodIndexResampler):
+# error: Definition of "ax" in base class "_GroupByMixin" is incompatible with
+# definition in base class "PeriodIndexResampler"
+class PeriodIndexResamplerGroupby(  # type: ignore[misc]
+    _GroupByMixin, PeriodIndexResampler
+):
     """
     Provides a resample of a groupby implementation.
     """
@@ -1935,6 +1949,10 @@ def _resampler_cls(self):
 
 
 class TimedeltaIndexResampler(DatetimeIndexResampler):
+    # error: Incompatible types in assignment (expression has type "TimedeltaIndex",
+    # base class "DatetimeIndexResampler" defined the type as "DatetimeIndex")
+    ax: TimedeltaIndex  # type: ignore[assignment]
+
     @property
     def _resampler_for_grouping(self):
         return TimedeltaIndexResamplerGroupby
@@ -1952,7 +1970,11 @@ def _adjust_binner_for_upsample(self, binner):
         return binner
 
 
-class TimedeltaIndexResamplerGroupby(_GroupByMixin, TimedeltaIndexResampler):
+# error: Definition of "ax" in base class "_GroupByMixin" is incompatible with
+# definition in base class "DatetimeIndexResampler"
+class TimedeltaIndexResamplerGroupby(  # type: ignore[misc]
+    _GroupByMixin, TimedeltaIndexResampler
+):
     """
     Provides a resample of a groupby implementation.
     """
diff --git a/pandas/core/reshape/concat.py b/pandas/core/reshape/concat.py
index ffa7199921298..1bc548de91f01 100644
--- a/pandas/core/reshape/concat.py
+++ b/pandas/core/reshape/concat.py
@@ -76,7 +76,7 @@ def concat(
     axis: Literal[0, "index"] = ...,
     join: str = ...,
     ignore_index: bool = ...,
-    keys=...,
+    keys: Iterable[Hashable] | None = ...,
     levels=...,
     names: list[HashableT] | None = ...,
     verify_integrity: bool = ...,
@@ -93,7 +93,7 @@ def concat(
     axis: Literal[0, "index"] = ...,
     join: str = ...,
     ignore_index: bool = ...,
-    keys=...,
+    keys: Iterable[Hashable] | None = ...,
     levels=...,
     names: list[HashableT] | None = ...,
     verify_integrity: bool = ...,
@@ -110,7 +110,7 @@ def concat(
     axis: Literal[0, "index"] = ...,
     join: str = ...,
     ignore_index: bool = ...,
-    keys=...,
+    keys: Iterable[Hashable] | None = ...,
     levels=...,
     names: list[HashableT] | None = ...,
     verify_integrity: bool = ...,
@@ -127,7 +127,7 @@ def concat(
     axis: Literal[1, "columns"],
     join: str = ...,
     ignore_index: bool = ...,
-    keys=...,
+    keys: Iterable[Hashable] | None = ...,
     levels=...,
     names: list[HashableT] | None = ...,
     verify_integrity: bool = ...,
@@ -144,7 +144,7 @@ def concat(
     axis: Axis = ...,
     join: str = ...,
     ignore_index: bool = ...,
-    keys=...,
+    keys: Iterable[Hashable] | None = ...,
     levels=...,
     names: list[HashableT] | None = ...,
     verify_integrity: bool = ...,
@@ -160,7 +160,7 @@ def concat(
     axis: Axis = 0,
     join: str = "outer",
     ignore_index: bool = False,
-    keys=None,
+    keys: Iterable[Hashable] | None = None,
     levels=None,
     names: list[HashableT] | None = None,
     verify_integrity: bool = False,
@@ -405,7 +405,7 @@ def __init__(
         objs: Iterable[Series | DataFrame] | Mapping[HashableT, Series | DataFrame],
         axis: Axis = 0,
         join: str = "outer",
-        keys=None,
+        keys: Iterable[Hashable] | None = None,
         levels=None,
         names: list[HashableT] | None = None,
         ignore_index: bool = False,
diff --git a/pandas/core/reshape/merge.py b/pandas/core/reshape/merge.py
index 13bc1008698b2..f3695fb87ea78 100644
--- a/pandas/core/reshape/merge.py
+++ b/pandas/core/reshape/merge.py
@@ -105,6 +105,7 @@
     from pandas import DataFrame
     from pandas.core import groupby
     from pandas.core.arrays import DatetimeArray
+    from pandas.core.indexes.frozen import FrozenList
 
 _factorizers = {
     np.int64: libhashtable.Int64Factorizer,
@@ -1738,7 +1739,7 @@ def restore_dropped_levels_multijoin(
     join_index: Index,
     lindexer: npt.NDArray[np.intp],
     rindexer: npt.NDArray[np.intp],
-) -> tuple[list[Index], npt.NDArray[np.intp], list[Hashable]]:
+) -> tuple[FrozenList, FrozenList, FrozenList]:
     """
     *this is an internal non-public method*
 
@@ -1814,7 +1815,7 @@ def _convert_to_multiindex(index: Index) -> MultiIndex:
 
         # error: Cannot determine type of "__add__"
         join_levels = join_levels + [restore_levels]  # type: ignore[has-type]
-        join_codes = join_codes + [restore_codes]
+        join_codes = join_codes + [restore_codes]  # type: ignore[has-type]
         join_names = join_names + [dropped_level_name]
 
     return join_levels, join_codes, join_names
diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index 71e3ea5b2588e..924b56f7a14d5 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -522,6 +522,7 @@ def pivot(
             cols + columns_listlike, append=append  # type: ignore[operator]
         )
     else:
+        index_list: list[Index] | list[Series]
         if index is lib.no_default:
             if isinstance(data.index, MultiIndex):
                 # GH 23955
diff --git a/pandas/core/series.py b/pandas/core/series.py
index a44f6bc01328d..9b5c8829fd5ff 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -4398,7 +4398,7 @@ def explode(self, ignore_index: bool = False) -> Series:
             return result.reset_index(drop=True) if ignore_index else result
 
         if ignore_index:
-            index = default_index(len(values))
+            index: Index = default_index(len(values))
         else:
             index = self.index.repeat(counts)
 
diff --git a/pandas/core/strings/accessor.py b/pandas/core/strings/accessor.py
index 124ca546c4583..71d6f9c58e2c2 100644
--- a/pandas/core/strings/accessor.py
+++ b/pandas/core/strings/accessor.py
@@ -372,7 +372,7 @@ def cons_row(x):
 
             if expand:
                 result = list(result)
-                out = MultiIndex.from_tuples(result, names=name)
+                out: Index = MultiIndex.from_tuples(result, names=name)
                 if out.nlevels == 1:
                     # We had all tuples of length-one, which are
                     # better represented as a regular Index.
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index fb0354ef9df6c..c0a27ecfec803 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -2823,7 +2823,7 @@ def read(
             "cannot read on an abstract storer: subclasses should implement"
         )
 
-    def write(self, **kwargs):
+    def write(self, obj, **kwargs) -> None:
         raise NotImplementedError(
             "cannot write on an abstract storer: subclasses should implement"
         )
@@ -2937,8 +2937,7 @@ def get_attrs(self) -> None:
         for n in self.attributes:
             setattr(self, n, _ensure_decoded(getattr(self.attrs, n, None)))
 
-    # error: Signature of "write" incompatible with supertype "Fixed"
-    def write(self, obj, **kwargs) -> None:  # type: ignore[override]
+    def write(self, obj, **kwargs) -> None:
         self.set_attrs()
 
     def read_array(self, key: str, start: int | None = None, stop: int | None = None):
@@ -3226,8 +3225,7 @@ def read(
             result = result.astype("string[pyarrow_numpy]")
         return result
 
-    # error: Signature of "write" incompatible with supertype "Fixed"
-    def write(self, obj, **kwargs) -> None:  # type: ignore[override]
+    def write(self, obj, **kwargs) -> None:
         super().write(obj, **kwargs)
         self.write_index("index", obj.index)
         self.write_array("values", obj)
@@ -3303,8 +3301,7 @@ def read(
 
         return DataFrame(columns=axes[0], index=axes[1])
 
-    # error: Signature of "write" incompatible with supertype "Fixed"
-    def write(self, obj, **kwargs) -> None:  # type: ignore[override]
+    def write(self, obj, **kwargs) -> None:
         super().write(obj, **kwargs)
 
         # TODO(ArrayManager) HDFStore relies on accessing the blocks
@@ -4355,7 +4352,7 @@ def read(
         """
         raise NotImplementedError("WORMTable needs to implement read")
 
-    def write(self, **kwargs) -> None:
+    def write(self, obj, **kwargs) -> None:
         """
         write in a format that we can search later on (but cannot append
         to): write out the indices and the values using _write_array
@@ -4712,12 +4709,13 @@ def is_transposed(self) -> bool:
     def get_object(cls, obj, transposed: bool):
         return obj
 
-    def write(self, obj, data_columns=None, **kwargs):
+    # error: Signature of "write" incompatible with supertype "Fixed"
+    def write(self, obj, data_columns=None, **kwargs) -> None:  # type: ignore[override]
         """we are going to write this as a frame table"""
         if not isinstance(obj, DataFrame):
             name = obj.name or "values"
             obj = obj.to_frame(name)
-        return super().write(obj=obj, data_columns=obj.columns.tolist(), **kwargs)
+        super().write(obj=obj, data_columns=obj.columns.tolist(), **kwargs)
 
     def read(
         self,
@@ -4750,7 +4748,8 @@ class AppendableMultiSeriesTable(AppendableSeriesTable):
     pandas_kind = "series_table"
     table_type = "appendable_multiseries"
 
-    def write(self, obj, **kwargs):
+    #  error: Signature of "write" incompatible with supertype "Fixed"
+    def write(self, obj, **kwargs) -> None:  # type: ignore[override]
         """we are going to write this as a frame table"""
         name = obj.name or "values"
         newobj, self.levels = self.validate_multiindex(obj)
@@ -4758,7 +4757,7 @@ def write(self, obj, **kwargs):
         cols = list(self.levels)
         cols.append(name)
         newobj.columns = Index(cols)
-        return super().write(obj=newobj, **kwargs)
+        super().write(obj=newobj, **kwargs)
 
 
 class GenericTable(AppendableFrameTable):
@@ -4823,7 +4822,8 @@ def indexables(self):
 
         return _indexables
 
-    def write(self, **kwargs):
+    # error: Signature of "write" incompatible with supertype "AppendableTable"
+    def write(self, **kwargs) -> None:  # type: ignore[override]
         raise NotImplementedError("cannot write on an generic table")
 
 
@@ -4839,7 +4839,8 @@ class AppendableMultiFrameTable(AppendableFrameTable):
     def table_type_short(self) -> str:
         return "appendable_multi"
 
-    def write(self, obj, data_columns=None, **kwargs):
+    # error: Signature of "write" incompatible with supertype "Fixed"
+    def write(self, obj, data_columns=None, **kwargs) -> None:  # type: ignore[override]
         if data_columns is None:
             data_columns = []
         elif data_columns is True:
@@ -4849,7 +4850,7 @@ def write(self, obj, data_columns=None, **kwargs):
         for n in self.levels:
             if n not in data_columns:
                 data_columns.insert(0, n)
-        return super().write(obj=obj, data_columns=data_columns, **kwargs)
+        super().write(obj=obj, data_columns=data_columns, **kwargs)
 
     def read(
         self,