diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 36ff38a849969..966fda1ed710a 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
+        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
         types_or: [python, pyi]
         files: ^pandas
         exclude: ^(pandas/tests|pandas/_version.py|pandas/io/clipboard)
diff --git a/pandas/_testing/__init__.py b/pandas/_testing/__init__.py
index 92c9c28058714..e9bf19899f31e 100644
--- a/pandas/_testing/__init__.py
+++ b/pandas/_testing/__init__.py
@@ -25,7 +25,10 @@
     set_locale,
 )
 
-from pandas._typing import Dtype
+from pandas._typing import (
+    Dtype,
+    Frequency,
+)
 from pandas.compat import pa_version_under1p01
 
 from pandas.core.dtypes.common import (
@@ -401,13 +404,17 @@ def makeFloatIndex(k=10, name=None) -> Float64Index:
     return Float64Index(base_idx)
 
 
-def makeDateIndex(k: int = 10, freq="B", name=None, **kwargs) -> DatetimeIndex:
+def makeDateIndex(
+    k: int = 10, freq: Frequency = "B", name=None, **kwargs
+) -> DatetimeIndex:
     dt = datetime(2000, 1, 1)
     dr = bdate_range(dt, periods=k, freq=freq, name=name)
     return DatetimeIndex(dr, name=name, **kwargs)
 
 
-def makeTimedeltaIndex(k: int = 10, freq="D", name=None, **kwargs) -> TimedeltaIndex:
+def makeTimedeltaIndex(
+    k: int = 10, freq: Frequency = "D", name=None, **kwargs
+) -> TimedeltaIndex:
     return pd.timedelta_range(start="1 day", periods=k, freq=freq, name=name, **kwargs)
 
 
@@ -484,7 +491,7 @@ def getSeriesData() -> dict[str, Series]:
     return {c: Series(np.random.randn(_N), index=index) for c in getCols(_K)}
 
 
-def makeTimeSeries(nper=None, freq="B", name=None) -> Series:
+def makeTimeSeries(nper=None, freq: Frequency = "B", name=None) -> Series:
     if nper is None:
         nper = _N
     return Series(
@@ -498,7 +505,7 @@ def makePeriodSeries(nper=None, name=None) -> Series:
     return Series(np.random.randn(nper), index=makePeriodIndex(nper), name=name)
 
 
-def getTimeSeriesData(nper=None, freq="B") -> dict[str, Series]:
+def getTimeSeriesData(nper=None, freq: Frequency = "B") -> dict[str, Series]:
     return {c: makeTimeSeries(nper, freq) for c in getCols(_K)}
 
 
@@ -507,7 +514,7 @@ def getPeriodData(nper=None) -> dict[str, Series]:
 
 
 # make frame
-def makeTimeDataFrame(nper=None, freq="B") -> DataFrame:
+def makeTimeDataFrame(nper=None, freq: Frequency = "B") -> DataFrame:
     data = getTimeSeriesData(nper, freq)
     return DataFrame(data)
 
@@ -542,7 +549,7 @@ def makePeriodFrame(nper=None) -> DataFrame:
 def makeCustomIndex(
     nentries,
     nlevels,
-    prefix="#",
+    prefix: str = "#",
     names: bool | str | list[str] | None = False,
     ndupe_l=None,
     idx_type=None,
@@ -760,7 +767,7 @@ def makeCustomDataframe(
     return DataFrame(data, index, columns, dtype=dtype)
 
 
-def _create_missing_idx(nrows, ncols, density, random_state=None):
+def _create_missing_idx(nrows, ncols, density: float, random_state=None):
     if random_state is None:
         random_state = np.random
     else:
@@ -787,7 +794,7 @@ def _gen_unique_rand(rng, _extra_size):
     return i.tolist(), j.tolist()
 
 
-def makeMissingDataframe(density=0.9, random_state=None) -> DataFrame:
+def makeMissingDataframe(density: float = 0.9, random_state=None) -> DataFrame:
     df = makeDataFrame()
     i, j = _create_missing_idx(*df.shape, density=density, random_state=random_state)
     df.values[i, j] = np.nan
diff --git a/pandas/_testing/_io.py b/pandas/_testing/_io.py
index ba94746b0ae6d..9ad0d13e7317e 100644
--- a/pandas/_testing/_io.py
+++ b/pandas/_testing/_io.py
@@ -117,7 +117,7 @@ def dec(f):
 @optional_args  # type: ignore[misc]
 def network(
     t,
-    url="https://www.google.com",
+    url: str = "https://www.google.com",
     raise_on_error: bool = False,
     check_before_test: bool = False,
     error_classes=None,
@@ -369,7 +369,7 @@ def round_trip_localpath(writer, reader, path: str | None = None):
     return obj
 
 
-def write_to_compressed(compression, path, data, dest="test"):
+def write_to_compressed(compression, path, data, dest: str = "test"):
     """
     Write data to a compressed file.
 
diff --git a/pandas/_testing/_random.py b/pandas/_testing/_random.py
index 81f3b33d266ee..218816308f95d 100644
--- a/pandas/_testing/_random.py
+++ b/pandas/_testing/_random.py
@@ -2,6 +2,8 @@
 
 import numpy as np
 
+from pandas._typing import NpDtype
+
 
 def randbool(size=(), p: float = 0.5):
     return np.random.rand(*size) <= p
@@ -14,7 +16,7 @@ def randbool(size=(), p: float = 0.5):
 )
 
 
-def rands_array(nchars, size, dtype="O", replace: bool = True) -> np.ndarray:
+def rands_array(nchars, size, dtype: NpDtype = "O", replace: bool = True) -> np.ndarray:
     """
     Generate an array of byte strings.
     """
diff --git a/pandas/_testing/asserters.py b/pandas/_testing/asserters.py
index f05bcc74e6c5d..db850ffdc4e1f 100644
--- a/pandas/_testing/asserters.py
+++ b/pandas/_testing/asserters.py
@@ -311,7 +311,7 @@ def assert_index_equal(
     """
     __tracebackhide__ = True
 
-    def _check_types(left, right, obj="Index") -> None:
+    def _check_types(left, right, obj: str = "Index") -> None:
         if not exact:
             return
 
@@ -429,7 +429,9 @@ def _get_ilevel_values(index, level):
             assert_categorical_equal(left._values, right._values, obj=f"{obj} category")
 
 
-def assert_class_equal(left, right, exact: bool | str = True, obj="Input") -> None:
+def assert_class_equal(
+    left, right, exact: bool | str = True, obj: str = "Input"
+) -> None:
     """
     Checks classes are equal.
     """
@@ -527,7 +529,7 @@ def assert_categorical_equal(
     right,
     check_dtype: bool = True,
     check_category_order: bool = True,
-    obj="Categorical",
+    obj: str = "Categorical",
 ) -> None:
     """
     Test that Categoricals are equivalent.
@@ -584,7 +586,7 @@ def assert_categorical_equal(
 
 
 def assert_interval_array_equal(
-    left, right, exact="equiv", obj="IntervalArray"
+    left, right, exact: bool | Literal["equiv"] = "equiv", obj: str = "IntervalArray"
 ) -> None:
     """
     Test that two IntervalArrays are equivalent.
@@ -614,7 +616,7 @@ def assert_interval_array_equal(
     assert_attr_equal("closed", left, right, obj=obj)
 
 
-def assert_period_array_equal(left, right, obj="PeriodArray") -> None:
+def assert_period_array_equal(left, right, obj: str = "PeriodArray") -> None:
     _check_isinstance(left, right, PeriodArray)
 
     assert_numpy_array_equal(left._data, right._data, obj=f"{obj}._data")
@@ -622,7 +624,7 @@ def assert_period_array_equal(left, right, obj="PeriodArray") -> None:
 
 
 def assert_datetime_array_equal(
-    left, right, obj="DatetimeArray", check_freq: bool = True
+    left, right, obj: str = "DatetimeArray", check_freq: bool = True
 ) -> None:
     __tracebackhide__ = True
     _check_isinstance(left, right, DatetimeArray)
@@ -634,7 +636,7 @@ def assert_datetime_array_equal(
 
 
 def assert_timedelta_array_equal(
-    left, right, obj="TimedeltaArray", check_freq: bool = True
+    left, right, obj: str = "TimedeltaArray", check_freq: bool = True
 ) -> None:
     __tracebackhide__ = True
     _check_isinstance(left, right, TimedeltaArray)
@@ -693,7 +695,7 @@ def assert_numpy_array_equal(
     check_dtype: bool | Literal["equiv"] = True,
     err_msg=None,
     check_same=None,
-    obj="numpy array",
+    obj: str = "numpy array",
     index_values=None,
 ) -> None:
     """
@@ -887,7 +889,7 @@ def assert_series_equal(
     check_flags: bool = True,
     rtol: float = 1.0e-5,
     atol: float = 1.0e-8,
-    obj="Series",
+    obj: str = "Series",
     *,
     check_index: bool = True,
     check_like: bool = False,
@@ -1157,7 +1159,7 @@ def assert_frame_equal(
     check_flags: bool = True,
     rtol: float = 1.0e-5,
     atol: float = 1.0e-8,
-    obj="DataFrame",
+    obj: str = "DataFrame",
 ) -> None:
     """
     Check that left and right DataFrame are equal.
diff --git a/pandas/_typing.py b/pandas/_typing.py
index c7d82be4e24a1..af037ff0473e3 100644
--- a/pandas/_typing.py
+++ b/pandas/_typing.py
@@ -332,3 +332,17 @@ def closed(self) -> bool:
 
 # dropna
 AnyAll = Literal["any", "all"]
+
+MatplotlibColor = Union[str, Sequence[float]]
+TimeGrouperOrigin = Union[
+    "Timestamp", Literal["epoch", "start", "start_day", "end", "end_day"]
+]
+TimeAmbiguous = Union[Literal["infer", "NaT", "raise"], "npt.NDArray[np.bool_]"]
+TimeNonexistent = Union[
+    Literal["shift_forward", "shift_backward", "NaT", "raise"], timedelta
+]
+DropKeep = Literal["first", "last", False]
+CorrelationMethod = Union[
+    Literal["pearson", "kendall", "spearman"], Callable[[np.ndarray, np.ndarray], float]
+]
+AlignJoin = Literal["outer", "inner", "left", "right"]
diff --git a/pandas/core/arrays/arrow/array.py b/pandas/core/arrays/arrow/array.py
index 9ac77a7d48604..03f734730a0f9 100644
--- a/pandas/core/arrays/arrow/array.py
+++ b/pandas/core/arrays/arrow/array.py
@@ -12,6 +12,7 @@
 from pandas._typing import (
     Dtype,
     PositionalIndexer,
+    SortKind,
     TakeIndexer,
     npt,
 )
@@ -472,7 +473,7 @@ def isna(self) -> npt.NDArray[np.bool_]:
     def argsort(
         self,
         ascending: bool = True,
-        kind: str = "quicksort",
+        kind: SortKind = "quicksort",
         na_position: str = "last",
         *args,
         **kwargs,
diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py
index efce69439ea43..77dfc82e640f2 100644
--- a/pandas/core/arrays/base.py
+++ b/pandas/core/arrays/base.py
@@ -37,6 +37,7 @@
     ScalarIndexer,
     SequenceIndexer,
     Shape,
+    SortKind,
     TakeIndexer,
     npt,
 )
@@ -671,7 +672,7 @@ def _values_for_argsort(self) -> np.ndarray:
     def argsort(
         self,
         ascending: bool = True,
-        kind: str = "quicksort",
+        kind: SortKind = "quicksort",
         na_position: str = "last",
         *args,
         **kwargs,
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index f2dace75906ad..ee995a0f9d0b7 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -44,6 +44,7 @@
     NpDtype,
     Ordered,
     Shape,
+    SortKind,
     npt,
     type_t,
 )
@@ -1827,7 +1828,7 @@ def check_for_ordered(self, op) -> None:
     # error: Signature of "argsort" incompatible with supertype "ExtensionArray"
     @deprecate_nonkeyword_arguments(version=None, allowed_args=["self"])
     def argsort(  # type: ignore[override]
-        self, ascending: bool = True, kind="quicksort", **kwargs
+        self, ascending: bool = True, kind: SortKind = "quicksort", **kwargs
     ):
         """
         Return the indices that would sort the Categorical.
@@ -2200,7 +2201,9 @@ def _repr_footer(self) -> str:
         info = self._repr_categories_info()
         return f"Length: {len(self)}\n{info}"
 
-    def _get_repr(self, length: bool = True, na_rep="NaN", footer: bool = True) -> str:
+    def _get_repr(
+        self, length: bool = True, na_rep: str = "NaN", footer: bool = True
+    ) -> str:
         from pandas.io.formats import format as fmt
 
         formatter = fmt.CategoricalFormatter(
@@ -2716,7 +2719,7 @@ def _str_map(
         result = PandasArray(categories.to_numpy())._str_map(f, na_value, dtype)
         return take_nd(result, codes, fill_value=na_value)
 
-    def _str_get_dummies(self, sep="|"):
+    def _str_get_dummies(self, sep: str = "|"):
         # sep may not be in categories. Just bail on this.
         from pandas.core.arrays import PandasArray
 
diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py
index d28b9aeeb41d0..5a92cc3c8509c 100644
--- a/pandas/core/arrays/datetimelike.py
+++ b/pandas/core/arrays/datetimelike.py
@@ -63,6 +63,8 @@
     PositionalIndexerTuple,
     ScalarIndexer,
     SequenceIndexer,
+    TimeAmbiguous,
+    TimeNonexistent,
     npt,
 )
 from pandas.compat.numpy import function as nv
@@ -308,7 +310,7 @@ def asi8(self) -> npt.NDArray[np.int64]:
     # Rendering Methods
 
     def _format_native_types(
-        self, *, na_rep="NaT", date_format=None
+        self, *, na_rep: str | float = "NaT", date_format=None
     ) -> npt.NDArray[np.object_]:
         """
         Helper method for astype when converting to strings.
@@ -556,7 +558,7 @@ def _concat_same_type(
         new_obj._freq = new_freq
         return new_obj
 
-    def copy(self: DatetimeLikeArrayT, order="C") -> DatetimeLikeArrayT:
+    def copy(self: DatetimeLikeArrayT, order: str = "C") -> DatetimeLikeArrayT:
         # error: Unexpected keyword argument "order" for "copy"
         new_obj = super().copy(order=order)  # type: ignore[call-arg]
         new_obj._freq = self.freq
@@ -2085,15 +2087,30 @@ def _round(self, freq, mode, ambiguous, nonexistent):
         return self._simple_new(result, dtype=self.dtype)
 
     @Appender((_round_doc + _round_example).format(op="round"))
-    def round(self, freq, ambiguous="raise", nonexistent="raise"):
+    def round(
+        self,
+        freq,
+        ambiguous: TimeAmbiguous = "raise",
+        nonexistent: TimeNonexistent = "raise",
+    ):
         return self._round(freq, RoundTo.NEAREST_HALF_EVEN, ambiguous, nonexistent)
 
     @Appender((_round_doc + _floor_example).format(op="floor"))
-    def floor(self, freq, ambiguous="raise", nonexistent="raise"):
+    def floor(
+        self,
+        freq,
+        ambiguous: TimeAmbiguous = "raise",
+        nonexistent: TimeNonexistent = "raise",
+    ):
         return self._round(freq, RoundTo.MINUS_INFTY, ambiguous, nonexistent)
 
     @Appender((_round_doc + _ceil_example).format(op="ceil"))
-    def ceil(self, freq, ambiguous="raise", nonexistent="raise"):
+    def ceil(
+        self,
+        freq,
+        ambiguous: TimeAmbiguous = "raise",
+        nonexistent: TimeNonexistent = "raise",
+    ):
         return self._round(freq, RoundTo.PLUS_INFTY, ambiguous, nonexistent)
 
     # --------------------------------------------------------------
diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 017ff5abdbe77..a9c1a7e3cdab0 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -41,7 +41,13 @@
     tz_convert_from_utc,
     tzconversion,
 )
-from pandas._typing import npt
+from pandas._typing import (
+    DateTimeErrorChoices,
+    IntervalClosedType,
+    TimeAmbiguous,
+    TimeNonexistent,
+    npt,
+)
 from pandas.errors import (
     OutOfBoundsDatetime,
     PerformanceWarning,
@@ -298,7 +304,7 @@ def _from_sequence_not_strict(
         freq: str | BaseOffset | lib.NoDefault | None = lib.no_default,
         dayfirst: bool = False,
         yearfirst: bool = False,
-        ambiguous="raise",
+        ambiguous: TimeAmbiguous = "raise",
     ):
         explicit_none = freq is None
         freq = freq if freq is not lib.no_default else None
@@ -344,9 +350,9 @@ def _generate_range(  # type: ignore[override]
         freq,
         tz=None,
         normalize: bool = False,
-        ambiguous="raise",
-        nonexistent="raise",
-        inclusive="both",
+        ambiguous: TimeAmbiguous = "raise",
+        nonexistent: TimeNonexistent = "raise",
+        inclusive: IntervalClosedType = "both",
     ) -> DatetimeArray:
 
         periods = dtl.validate_periods(periods)
@@ -658,7 +664,7 @@ def astype(self, dtype, copy: bool = True):
     # Rendering Methods
 
     def _format_native_types(
-        self, *, na_rep="NaT", date_format=None, **kwargs
+        self, *, na_rep: str | float = "NaT", date_format=None, **kwargs
     ) -> npt.NDArray[np.object_]:
         from pandas.io.formats.format import get_format_datetime64_from_values
 
@@ -830,7 +836,12 @@ def tz_convert(self, tz) -> DatetimeArray:
         return self._simple_new(self._ndarray, dtype=dtype, freq=self.freq)
 
     @dtl.ravel_compat
-    def tz_localize(self, tz, ambiguous="raise", nonexistent="raise") -> DatetimeArray:
+    def tz_localize(
+        self,
+        tz,
+        ambiguous: TimeAmbiguous = "raise",
+        nonexistent: TimeNonexistent = "raise",
+    ) -> DatetimeArray:
         """
         Localize tz-naive Datetime Array/Index to tz-aware Datetime Array/Index.
 
@@ -1989,7 +2000,7 @@ def _sequence_to_dt64ns(
     tz=lib.no_default,
     dayfirst: bool = False,
     yearfirst: bool = False,
-    ambiguous="raise",
+    ambiguous: TimeAmbiguous = "raise",
     *,
     allow_mixed: bool = False,
     require_iso8601: bool = False,
@@ -2144,7 +2155,7 @@ def objects_to_datetime64ns(
     dayfirst,
     yearfirst,
     utc: bool = False,
-    errors="raise",
+    errors: DateTimeErrorChoices = "raise",
     require_iso8601: bool = False,
     allow_object: bool = False,
     allow_mixed: bool = False,
diff --git a/pandas/core/arrays/interval.py b/pandas/core/arrays/interval.py
index 57ef236eb6d5f..f2afc4762e6a8 100644
--- a/pandas/core/arrays/interval.py
+++ b/pandas/core/arrays/interval.py
@@ -38,6 +38,7 @@
     PositionalIndexer,
     ScalarIndexer,
     SequenceIndexer,
+    SortKind,
     npt,
 )
 from pandas.compat.numpy import function as nv
@@ -564,7 +565,7 @@ def from_arrays(
     def from_tuples(
         cls: type[IntervalArrayT],
         data,
-        closed="right",
+        closed: IntervalClosedType | None = "right",
         copy: bool = False,
         dtype: Dtype | None = None,
     ) -> IntervalArrayT:
@@ -799,7 +800,7 @@ def __le__(self, other):
     def argsort(
         self,
         ascending: bool = True,
-        kind: str = "quicksort",
+        kind: SortKind = "quicksort",
         na_position: str = "last",
         *args,
         **kwargs,
diff --git a/pandas/core/arrays/period.py b/pandas/core/arrays/period.py
index 91eeee936cba1..c0d476c2452b8 100644
--- a/pandas/core/arrays/period.py
+++ b/pandas/core/arrays/period.py
@@ -642,7 +642,7 @@ def _formatter(self, boxed: bool = False):
 
     @dtl.ravel_compat
     def _format_native_types(
-        self, *, na_rep="NaT", date_format=None, **kwargs
+        self, *, na_rep: str | float = "NaT", date_format=None, **kwargs
     ) -> npt.NDArray[np.object_]:
         """
         actually format my specific types
diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
index 06ea661aca6c9..75e4ab6b37bf7 100644
--- a/pandas/core/arrays/timedeltas.py
+++ b/pandas/core/arrays/timedeltas.py
@@ -33,6 +33,7 @@
 )
 from pandas._typing import (
     AxisInt,
+    DateTimeErrorChoices,
     DtypeObj,
     NpDtype,
     npt,
@@ -373,7 +374,7 @@ def _formatter(self, boxed: bool = False):
         return get_format_timedelta64(self, box=True)
 
     def _format_native_types(
-        self, *, na_rep="NaT", date_format=None, **kwargs
+        self, *, na_rep: str | float = "NaT", date_format=None, **kwargs
     ) -> npt.NDArray[np.object_]:
         from pandas.io.formats.format import get_format_timedelta64
 
@@ -846,7 +847,10 @@ def f(x):
 
 
 def sequence_to_td64ns(
-    data, copy: bool = False, unit=None, errors="raise"
+    data,
+    copy: bool = False,
+    unit=None,
+    errors: DateTimeErrorChoices = "raise",
 ) -> tuple[np.ndarray, Tick | None]:
     """
     Parameters
@@ -932,7 +936,7 @@ def sequence_to_td64ns(
     return data, inferred_freq
 
 
-def ints_to_td64ns(data, unit="ns"):
+def ints_to_td64ns(data, unit: str = "ns"):
     """
     Convert an ndarray with integer-dtype to timedelta64[ns] dtype, treating
     the integers as multiples of the given timedelta unit.
@@ -972,7 +976,7 @@ def ints_to_td64ns(data, unit="ns"):
     return data, copy_made
 
 
-def _objects_to_td64ns(data, unit=None, errors="raise"):
+def _objects_to_td64ns(data, unit=None, errors: DateTimeErrorChoices = "raise"):
     """
     Convert a object-dtyped or string-dtyped array into an
     timedelta64[ns]-dtyped array.
diff --git a/pandas/core/base.py b/pandas/core/base.py
index 7f8db4182c71d..a1ca8b59dcffa 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -80,6 +80,7 @@
 if TYPE_CHECKING:
 
     from pandas._typing import (
+        DropKeep,
         NumpySorter,
         NumpyValueArrayLike,
     )
@@ -1308,15 +1309,13 @@ def searchsorted(
             sorter=sorter,
         )
 
-    def drop_duplicates(self, keep="first"):
+    def drop_duplicates(self, keep: DropKeep = "first"):
         duplicated = self._duplicated(keep=keep)
         # error: Value of type "IndexOpsMixin" is not indexable
         return self[~duplicated]  # type: ignore[index]
 
     @final
-    def _duplicated(
-        self, keep: Literal["first", "last", False] = "first"
-    ) -> npt.NDArray[np.bool_]:
+    def _duplicated(self, keep: DropKeep = "first") -> npt.NDArray[np.bool_]:
         return duplicated(self._values, keep=keep)
 
     def _arith_method(self, other, op):
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 0ec4caaabb6b5..7064848233581 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -50,6 +50,7 @@
 )
 from pandas._typing import (
     AggFuncType,
+    AlignJoin,
     AnyAll,
     AnyArrayLike,
     ArrayLike,
@@ -58,6 +59,8 @@
     AxisInt,
     ColspaceArgType,
     CompressionOptions,
+    CorrelationMethod,
+    DropKeep,
     Dtype,
     DtypeObj,
     FilePath,
@@ -5084,7 +5087,7 @@ def _reindex_multi(
     def align(
         self,
         other: DataFrame,
-        join: Literal["outer", "inner", "left", "right"] = "outer",
+        join: AlignJoin = "outer",
         axis: Axis | None = None,
         level: Level = None,
         copy: bool = True,
@@ -6594,7 +6597,7 @@ def dropna(
     def drop_duplicates(
         self,
         subset: Hashable | Sequence[Hashable] | None = None,
-        keep: Literal["first", "last", False] = "first",
+        keep: DropKeep = "first",
         inplace: bool = False,
         ignore_index: bool = False,
     ) -> DataFrame | None:
@@ -6693,7 +6696,7 @@ def drop_duplicates(
     def duplicated(
         self,
         subset: Hashable | Sequence[Hashable] | None = None,
-        keep: Literal["first", "last", False] = "first",
+        keep: DropKeep = "first",
     ) -> Series:
         """
         Return boolean Series denoting duplicate rows.
@@ -8727,11 +8730,11 @@ def pivot_table(
         values=None,
         index=None,
         columns=None,
-        aggfunc="mean",
+        aggfunc: AggFuncType = "mean",
         fill_value=None,
         margins: bool = False,
         dropna: bool = True,
-        margins_name="All",
+        margins_name: Level = "All",
         observed: bool = False,
         sort: bool = True,
     ) -> DataFrame:
@@ -9128,7 +9131,7 @@ def melt(
         id_vars=None,
         value_vars=None,
         var_name=None,
-        value_name="value",
+        value_name: Hashable = "value",
         col_level: Level = None,
         ignore_index: bool = True,
     ) -> DataFrame:
@@ -10242,7 +10245,7 @@ def _series_round(ser: Series, decimals: int):
 
     def corr(
         self,
-        method: str | Callable[[np.ndarray, np.ndarray], float] = "pearson",
+        method: CorrelationMethod = "pearson",
         min_periods: int = 1,
         numeric_only: bool | lib.NoDefault = lib.no_default,
     ) -> DataFrame:
@@ -10500,8 +10503,7 @@ def corrwith(
         other: DataFrame | Series,
         axis: Axis = 0,
         drop: bool = False,
-        method: Literal["pearson", "kendall", "spearman"]
-        | Callable[[np.ndarray, np.ndarray], float] = "pearson",
+        method: CorrelationMethod = "pearson",
         numeric_only: bool | lib.NoDefault = lib.no_default,
     ) -> Series:
         """
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index f023e5b6adf04..b520aab2cfa5b 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -41,6 +41,7 @@
     to_offset,
 )
 from pandas._typing import (
+    AlignJoin,
     AnyArrayLike,
     ArrayLike,
     Axis,
@@ -70,7 +71,9 @@
     StorageOptions,
     Suffixes,
     T,
+    TimeAmbiguous,
     TimedeltaConvertibleTypes,
+    TimeNonexistent,
     TimestampConvertibleTypes,
     ValueKeyFunc,
     WriteBuffer,
@@ -2823,7 +2826,7 @@ def to_sql(
         name: str,
         con,
         schema: str | None = None,
-        if_exists: str = "fail",
+        if_exists: Literal["fail", "replace", "append"] = "fail",
         index: bool_t = True,
         index_label: IndexLabel = None,
         chunksize: int | None = None,
@@ -4140,7 +4143,7 @@ def _check_is_chained_assignment_possible(self) -> bool_t:
         return False
 
     @final
-    def _check_setitem_copy(self, t="setting", force: bool_t = False):
+    def _check_setitem_copy(self, t: str = "setting", force: bool_t = False):
         """
 
         Parameters
@@ -4331,7 +4334,7 @@ def _is_view(self) -> bool_t:
     def reindex_like(
         self: NDFrameT,
         other,
-        method: str | None = None,
+        method: Literal["backfill", "bfill", "pad", "ffill", "nearest"] | None = None,
         copy: bool_t = True,
         limit=None,
         tolerance=None,
@@ -9312,7 +9315,7 @@ def compare(
     def align(
         self: NDFrameT,
         other: NDFrameT,
-        join: Literal["outer", "inner", "left", "right"] = "outer",
+        join: AlignJoin = "outer",
         axis: Axis | None = None,
         level: Level = None,
         copy: bool_t = True,
@@ -9505,7 +9508,7 @@ def align(
     def _align_frame(
         self,
         other,
-        join="outer",
+        join: AlignJoin = "outer",
         axis: Axis | None = None,
         level=None,
         copy: bool_t = True,
@@ -9569,7 +9572,7 @@ def _align_frame(
     def _align_series(
         self,
         other,
-        join="outer",
+        join: AlignJoin = "outer",
         axis: Axis | None = None,
         level=None,
         copy: bool_t = True,
@@ -10567,8 +10570,8 @@ def tz_localize(
         axis=0,
         level=None,
         copy: bool_t = True,
-        ambiguous="raise",
-        nonexistent: str = "raise",
+        ambiguous: TimeAmbiguous = "raise",
+        nonexistent: TimeNonexistent = "raise",
     ) -> NDFrameT:
         """
         Localize tz-naive index of a Series or DataFrame to target time zone.
@@ -10993,7 +10996,7 @@ def describe(
     def pct_change(
         self: NDFrameT,
         periods=1,
-        fill_method="pad",
+        fill_method: Literal["backfill", "bfill", "pad", "ffill"] = "pad",
         limit=None,
         freq=None,
         **kwargs,
diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 6a2070eb4f46f..4e17276a4eb1b 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -38,6 +38,7 @@
     ArrayLike,
     Axis,
     AxisInt,
+    CorrelationMethod,
     FillnaOptions,
     IndexLabel,
     Level,
@@ -857,8 +858,7 @@ def idxmax(self, axis: Axis = 0, skipna: bool = True) -> Series:
     def corr(
         self,
         other: Series,
-        method: Literal["pearson", "kendall", "spearman"]
-        | Callable[[np.ndarray, np.ndarray], float] = "pearson",
+        method: CorrelationMethod = "pearson",
         min_periods: int | None = None,
     ) -> Series:
         result = self._op_via_apply(
@@ -2220,8 +2220,7 @@ def corrwith(
         other: DataFrame | Series,
         axis: Axis = 0,
         drop: bool = False,
-        method: Literal["pearson", "kendall", "spearman"]
-        | Callable[[np.ndarray, np.ndarray], float] = "pearson",
+        method: CorrelationMethod = "pearson",
         numeric_only: bool | lib.NoDefault = lib.no_default,
     ) -> DataFrame:
         result = self._op_via_apply(
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 3e7fc1458c188..d5151d84e20bb 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -44,9 +44,11 @@ class providing the base-class of operations.
 )
 import pandas._libs.groupby as libgroupby
 from pandas._typing import (
+    AnyArrayLike,
     ArrayLike,
     AxisInt,
     Dtype,
+    FillnaOptions,
     IndexLabel,
     NDFrameT,
     PositionalIndexer,
@@ -3215,7 +3217,7 @@ def nth(
     @final
     def quantile(
         self,
-        q=0.5,
+        q: float | AnyArrayLike = 0.5,
         interpolation: str = "linear",
         numeric_only: bool | lib.NoDefault = lib.no_default,
     ):
@@ -3336,7 +3338,11 @@ def post_processor(
 
         orig_scalar = is_scalar(q)
         if orig_scalar:
-            q = [q]
+            # error: Incompatible types in assignment (expression has type "List[
+            # Union[float, ExtensionArray, ndarray[Any, Any], Index, Series]]",
+            # variable has type "Union[float, Union[Union[ExtensionArray, ndarray[
+            # Any, Any]], Index, Series]]")
+            q = [q]  # type: ignore[assignment]
 
         qs = np.array(q, dtype=np.float64)
         ids, _, ngroups = self.grouper.group_info
@@ -3991,7 +3997,14 @@ def diff(self, periods: int = 1, axis: AxisInt = 0) -> NDFrameT:
     @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
-    def pct_change(self, periods=1, fill_method="ffill", limit=None, freq=None, axis=0):
+    def pct_change(
+        self,
+        periods=1,
+        fill_method: FillnaOptions = "ffill",
+        limit=None,
+        freq=None,
+        axis=0,
+    ):
         """
         Calculate pct_change of each value to previous entry in group.
 
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 6a7f08d38024b..aaa840ef19650 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -50,6 +50,7 @@
     ArrayLike,
     Axes,
     AxisInt,
+    DropKeep,
     Dtype,
     DtypeObj,
     F,
@@ -1001,7 +1002,7 @@ def dtype(self) -> DtypeObj:
         return self._data.dtype
 
     @final
-    def ravel(self, order="C"):
+    def ravel(self, order: str_t = "C"):
         """
         Return an ndarray of the flattened values of the underlying data.
 
@@ -1538,7 +1539,7 @@ def to_native_types(self, slicer=None, **kwargs) -> np.ndarray:
         return values._format_native_types(**kwargs)
 
     def _format_native_types(
-        self, *, na_rep="", quoting=None, **kwargs
+        self, *, na_rep: str_t = "", quoting=None, **kwargs
     ) -> npt.NDArray[np.object_]:
         """
         Actually format specific types of the index.
@@ -3067,7 +3068,7 @@ def unique(self: _IndexT, level: Hashable | None = None) -> _IndexT:
         return self._shallow_copy(result)
 
     @deprecate_nonkeyword_arguments(version=None, allowed_args=["self"])
-    def drop_duplicates(self: _IndexT, keep: str_t | bool = "first") -> _IndexT:
+    def drop_duplicates(self: _IndexT, keep: DropKeep = "first") -> _IndexT:
         """
         Return Index with duplicate values removed.
 
@@ -3118,9 +3119,7 @@ def drop_duplicates(self: _IndexT, keep: str_t | bool = "first") -> _IndexT:
 
         return super().drop_duplicates(keep=keep)
 
-    def duplicated(
-        self, keep: Literal["first", "last", False] = "first"
-    ) -> npt.NDArray[np.bool_]:
+    def duplicated(self, keep: DropKeep = "first") -> npt.NDArray[np.bool_]:
         """
         Indicate duplicate index values.
 
diff --git a/pandas/core/indexes/datetimes.py b/pandas/core/indexes/datetimes.py
index 8a3b9b410cb16..bccbc2f861bdd 100644
--- a/pandas/core/indexes/datetimes.py
+++ b/pandas/core/indexes/datetimes.py
@@ -26,7 +26,6 @@
     lib,
 )
 from pandas._libs.tslibs import (
-    BaseOffset,
     Resolution,
     periods_per_day,
     timezones,
@@ -37,8 +36,11 @@
 from pandas._typing import (
     Dtype,
     DtypeObj,
+    Frequency,
     IntervalClosedType,
     IntervalLeftRight,
+    TimeAmbiguous,
+    TimeNonexistent,
     npt,
 )
 from pandas.util._decorators import (
@@ -278,7 +280,12 @@ def tz_convert(self, tz) -> DatetimeIndex:
         return type(self)._simple_new(arr, name=self.name)
 
     @doc(DatetimeArray.tz_localize)
-    def tz_localize(self, tz, ambiguous="raise", nonexistent="raise") -> DatetimeIndex:
+    def tz_localize(
+        self,
+        tz,
+        ambiguous: TimeAmbiguous = "raise",
+        nonexistent: TimeNonexistent = "raise",
+    ) -> DatetimeIndex:
         arr = self._data.tz_localize(tz, ambiguous, nonexistent)
         return type(self)._simple_new(arr, name=self.name)
 
@@ -314,11 +321,11 @@ def isocalendar(self) -> DataFrame:
     def __new__(
         cls,
         data=None,
-        freq: str | BaseOffset | lib.NoDefault = lib.no_default,
+        freq: Frequency | lib.NoDefault = lib.no_default,
         tz=lib.no_default,
         normalize: bool = False,
         closed=None,
-        ambiguous="raise",
+        ambiguous: TimeAmbiguous = "raise",
         dayfirst: bool = False,
         yearfirst: bool = False,
         dtype: Dtype | None = None,
@@ -590,7 +597,7 @@ def to_series(self, keep_tz=lib.no_default, index=None, name=None):
 
         return Series(values, index=index, name=name)
 
-    def snap(self, freq="S") -> DatetimeIndex:
+    def snap(self, freq: Frequency = "S") -> DatetimeIndex:
         """
         Snap time stamps to nearest occurring frequency.
 
@@ -1142,7 +1149,7 @@ def bdate_range(
     start=None,
     end=None,
     periods: int | None = None,
-    freq="B",
+    freq: Frequency = "B",
     tz=None,
     normalize: bool = True,
     name: Hashable = None,
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index 0076edb04f665..c8cb2cfa28640 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -311,7 +311,7 @@ def from_arrays(
     def from_tuples(
         cls,
         data,
-        closed: str = "right",
+        closed: IntervalClosedType = "right",
         name: Hashable = None,
         copy: bool = False,
         dtype: Dtype | None = None,
@@ -823,7 +823,7 @@ def _format_with_header(self, header: list[str], na_rep: str) -> list[str]:
         return header + list(self._format_native_types(na_rep=na_rep))
 
     def _format_native_types(
-        self, *, na_rep="NaN", quoting=None, **kwargs
+        self, *, na_rep: str = "NaN", quoting=None, **kwargs
     ) -> npt.NDArray[np.object_]:
         # GH 28210: use base method but with different default na_rep
         return super()._format_native_types(na_rep=na_rep, quoting=quoting, **kwargs)
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index 06021dfa93325..6e795bc4d13be 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -33,8 +33,10 @@
     AnyAll,
     AnyArrayLike,
     AxisInt,
+    DropKeep,
     DtypeObj,
     F,
+    IgnoreRaise,
     Scalar,
     Shape,
     npt,
@@ -1328,7 +1330,7 @@ def _formatter_func(self, tup):
         return tuple(func(val) for func, val in zip(formatter_funcs, tup))
 
     def _format_native_types(
-        self, *, na_rep="nan", **kwargs
+        self, *, na_rep: str = "nan", **kwargs
     ) -> npt.NDArray[np.object_]:
         new_levels = []
         new_codes = []
@@ -1626,7 +1628,7 @@ def _inferred_type_levels(self) -> list[str]:
         return [i.inferred_type for i in self.levels]
 
     @doc(Index.duplicated)
-    def duplicated(self, keep="first") -> npt.NDArray[np.bool_]:
+    def duplicated(self, keep: DropKeep = "first") -> npt.NDArray[np.bool_]:
         shape = tuple(len(lev) for lev in self.levels)
         ids = get_group_index(self.codes, shape, sort=False, xnull=False)
 
@@ -2256,7 +2258,13 @@ def repeat(self, repeats: int, axis=None) -> MultiIndex:
             verify_integrity=False,
         )
 
-    def drop(self, codes, level=None, errors="raise"):
+    # error: Signature of "drop" incompatible with supertype "Index"
+    def drop(  # type: ignore[override]
+        self,
+        codes,
+        level: Index | np.ndarray | Iterable[Hashable] | None = None,
+        errors: IgnoreRaise = "raise",
+    ) -> MultiIndex:
         """
         Make new MultiIndex with passed list of codes deleted
 
@@ -2310,7 +2318,9 @@ def drop(self, codes, level=None, errors="raise"):
 
         return self.delete(inds)
 
-    def _drop_from_level(self, codes, level, errors="raise") -> MultiIndex:
+    def _drop_from_level(
+        self, codes, level, errors: IgnoreRaise = "raise"
+    ) -> MultiIndex:
         codes = com.index_labels_to_array(codes)
         i = self._get_level_number(level)
         index = self.levels[i]
@@ -3917,7 +3927,7 @@ def _lexsort_depth(codes: list[np.ndarray], nlevels: int) -> int:
     return 0
 
 
-def sparsify_labels(label_list, start: int = 0, sentinel=""):
+def sparsify_labels(label_list, start: int = 0, sentinel: object = ""):
     pivoted = list(zip(*label_list))
     k = len(label_list)
 
diff --git a/pandas/core/indexes/numeric.py b/pandas/core/indexes/numeric.py
index 6dc100dde67a0..7838600f626de 100644
--- a/pandas/core/indexes/numeric.py
+++ b/pandas/core/indexes/numeric.py
@@ -281,7 +281,13 @@ def _assert_safe_casting(cls, data: np.ndarray, subarr: np.ndarray) -> None:
                 raise TypeError("Unsafe NumPy casting, you must explicitly cast")
 
     def _format_native_types(
-        self, *, na_rep="", float_format=None, decimal=".", quoting=None, **kwargs
+        self,
+        *,
+        na_rep: str = "",
+        float_format=None,
+        decimal: str = ".",
+        quoting=None,
+        **kwargs,
     ) -> npt.NDArray[np.object_]:
         from pandas.io.formats.format import FloatArrayFormatter
 
diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index 37d211d4d3cf0..60b687167a7a3 100644
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -1660,7 +1660,7 @@ def _get_setitem_indexer(self, key):
 
     # -------------------------------------------------------------------
 
-    def _setitem_with_indexer(self, indexer, value, name="iloc"):
+    def _setitem_with_indexer(self, indexer, value, name: str = "iloc"):
         """
         _setitem_with_indexer is for setting values on a Series/DataFrame
         using positional indexers.
diff --git a/pandas/core/internals/array_manager.py b/pandas/core/internals/array_manager.py
index d2c626a9cf247..4aa16257b0802 100644
--- a/pandas/core/internals/array_manager.py
+++ b/pandas/core/internals/array_manager.py
@@ -23,6 +23,7 @@
     ArrayLike,
     AxisInt,
     DtypeObj,
+    QuantileInterpolation,
     npt,
 )
 from pandas.util._validators import validate_bool_kwarg
@@ -1057,7 +1058,7 @@ def quantile(
         qs: Float64Index,
         axis: AxisInt = 0,
         transposed: bool = False,
-        interpolation="linear",
+        interpolation: QuantileInterpolation = "linear",
     ) -> ArrayManager:
 
         arrs = [ensure_block_shape(x, 2) for x in self.arrays]
diff --git a/pandas/core/internals/blocks.py b/pandas/core/internals/blocks.py
index 432431c89b334..62d8d7e504b4a 100644
--- a/pandas/core/internals/blocks.py
+++ b/pandas/core/internals/blocks.py
@@ -31,6 +31,7 @@
     F,
     FillnaOptions,
     IgnoreRaise,
+    QuantileInterpolation,
     Shape,
     npt,
 )
@@ -539,7 +540,7 @@ def astype(
         return newb
 
     @final
-    def to_native_types(self, na_rep="nan", quoting=None, **kwargs) -> Block:
+    def to_native_types(self, na_rep: str = "nan", quoting=None, **kwargs) -> Block:
         """convert to our native types format"""
         result = to_native_types(self.values, na_rep=na_rep, quoting=quoting, **kwargs)
         return self.make_block(result)
@@ -1055,7 +1056,7 @@ def putmask(self, mask, new) -> list[Block]:
                     res_blocks.extend(rbs)
                 return res_blocks
 
-    def where(self, other, cond, _downcast="infer") -> list[Block]:
+    def where(self, other, cond, _downcast: str | bool = "infer") -> list[Block]:
         """
         evaluate the block; return result block(s) from the result
 
@@ -1214,7 +1215,7 @@ def fillna(
 
     def interpolate(
         self,
-        method: str = "pad",
+        method: FillnaOptions = "pad",
         axis: AxisInt = 0,
         index: Index | None = None,
         inplace: bool = False,
@@ -1318,7 +1319,10 @@ def shift(
 
     @final
     def quantile(
-        self, qs: Float64Index, interpolation="linear", axis: AxisInt = 0
+        self,
+        qs: Float64Index,
+        interpolation: QuantileInterpolation = "linear",
+        axis: AxisInt = 0,
     ) -> Block:
         """
         compute the quantiles of the
@@ -1442,7 +1446,7 @@ def setitem(self, indexer, value):
         else:
             return self
 
-    def where(self, other, cond, _downcast="infer") -> list[Block]:
+    def where(self, other, cond, _downcast: str | bool = "infer") -> list[Block]:
         # _downcast private bc we only specify it when calling from fillna
         arr = self.values.T
 
@@ -2267,10 +2271,10 @@ def ensure_block_shape(values: ArrayLike, ndim: int = 1) -> ArrayLike:
 def to_native_types(
     values: ArrayLike,
     *,
-    na_rep="nan",
+    na_rep: str = "nan",
     quoting=None,
     float_format=None,
-    decimal=".",
+    decimal: str = ".",
     **kwargs,
 ) -> np.ndarray:
     """convert to our native types format"""
diff --git a/pandas/core/internals/managers.py b/pandas/core/internals/managers.py
index c6762b72f82d7..5a398533e1510 100644
--- a/pandas/core/internals/managers.py
+++ b/pandas/core/internals/managers.py
@@ -28,6 +28,7 @@
     ArrayLike,
     AxisInt,
     DtypeObj,
+    QuantileInterpolation,
     Shape,
     npt,
     type_t,
@@ -1582,7 +1583,7 @@ def quantile(
         *,
         qs: Float64Index,
         axis: AxisInt = 0,
-        interpolation="linear",
+        interpolation: QuantileInterpolation = "linear",
     ) -> T:
         """
         Iterate over blocks applying quantile reduction.
diff --git a/pandas/core/missing.py b/pandas/core/missing.py
index 242ee43b32393..9a55076c71f5f 100644
--- a/pandas/core/missing.py
+++ b/pandas/core/missing.py
@@ -629,7 +629,9 @@ def _akima_interpolate(xi, yi, x, der=0, axis=0):
     return P(x, nu=der)
 
 
-def _cubicspline_interpolate(xi, yi, x, axis=0, bc_type="not-a-knot", extrapolate=None):
+def _cubicspline_interpolate(
+    xi, yi, x, axis=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 e61970b1d7dcb..8e162a8249fd9 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -23,6 +23,7 @@
 from pandas._typing import (
     ArrayLike,
     AxisInt,
+    CorrelationMethod,
     Dtype,
     DtypeObj,
     F,
@@ -1536,7 +1537,11 @@ def _zero_out_fperr(arg):
 
 @disallow("M8", "m8")
 def nancorr(
-    a: np.ndarray, b: np.ndarray, *, method="pearson", min_periods: int | None = None
+    a: np.ndarray,
+    b: np.ndarray,
+    *,
+    method: CorrelationMethod = "pearson",
+    min_periods: int | None = None,
 ) -> float:
     """
     a, b: ndarrays
@@ -1559,7 +1564,9 @@ def nancorr(
     return f(a, b)
 
 
-def get_corr_func(method) -> Callable[[np.ndarray, np.ndarray], float]:
+def get_corr_func(
+    method: CorrelationMethod,
+) -> Callable[[np.ndarray, np.ndarray], float]:
     if method == "kendall":
         from scipy.stats import kendalltau
 
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 827dde886a216..0e0aa9e272c89 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -27,11 +27,15 @@
     to_offset,
 )
 from pandas._typing import (
+    AnyArrayLike,
     AxisInt,
+    Frequency,
     IndexLabel,
     NDFrameT,
+    QuantileInterpolation,
     T,
     TimedeltaConvertibleTypes,
+    TimeGrouperOrigin,
     TimestampConvertibleTypes,
     npt,
 )
@@ -921,11 +925,11 @@ def fillna(self, method, limit=None):
     @doc(NDFrame.interpolate, **_shared_docs_kwargs)
     def interpolate(
         self,
-        method="linear",
+        method: QuantileInterpolation = "linear",
         axis=0,
         limit=None,
         inplace: bool = False,
-        limit_direction="forward",
+        limit_direction: Literal["forward", "backward", "both"] = "forward",
         limit_area=None,
         downcast=None,
         **kwargs,
@@ -1052,7 +1056,7 @@ def count(self):
 
         return result
 
-    def quantile(self, q=0.5, **kwargs):
+    def quantile(self, q: float | AnyArrayLike = 0.5, **kwargs):
         """
         Return value at the given quantile.
 
@@ -1585,12 +1589,14 @@ class TimeGrouper(Grouper):
         "offset",
     )
 
+    origin: TimeGrouperOrigin
+
     def __init__(
         self,
-        freq="Min",
+        freq: Frequency = "Min",
         closed: Literal["left", "right"] | None = None,
         label: Literal["left", "right"] | None = None,
-        how="mean",
+        how: str = "mean",
         axis=0,
         fill_method=None,
         limit=None,
@@ -1598,7 +1604,8 @@ def __init__(
         kind: str | None = None,
         convention: Literal["start", "end", "e", "s"] | None = None,
         base: int | None = None,
-        origin: str | TimestampConvertibleTypes = "start_day",
+        origin: Literal["epoch", "start", "start_day", "end", "end_day"]
+        | TimestampConvertibleTypes = "start_day",
         offset: TimedeltaConvertibleTypes | None = None,
         group_keys: bool | lib.NoDefault = True,
         **kwargs,
@@ -1649,7 +1656,12 @@ def __init__(
         self.group_keys = group_keys
 
         if origin in ("epoch", "start", "start_day", "end", "end_day"):
-            self.origin = origin
+            # error: Incompatible types in assignment (expression has type "Union[Union[
+            # Timestamp, datetime, datetime64, signedinteger[_64Bit], float, str],
+            # Literal['epoch', 'start', 'start_day', 'end', 'end_day']]", variable has
+            # type "Union[Timestamp, Literal['epoch', 'start', 'start_day', 'end',
+            # 'end_day']]")
+            self.origin = origin  # type: ignore[assignment]
         else:
             try:
                 self.origin = Timestamp(origin)
@@ -1975,7 +1987,7 @@ def _get_timestamp_range_edges(
     last: Timestamp,
     freq: BaseOffset,
     closed: Literal["right", "left"] = "left",
-    origin="start_day",
+    origin: TimeGrouperOrigin = "start_day",
     offset: Timedelta | None = None,
 ) -> tuple[Timestamp, Timestamp]:
     """
@@ -2053,7 +2065,7 @@ def _get_period_range_edges(
     last: Period,
     freq: BaseOffset,
     closed: Literal["right", "left"] = "left",
-    origin="start_day",
+    origin: TimeGrouperOrigin = "start_day",
     offset: Timedelta | None = None,
 ) -> tuple[Period, Period]:
     """
@@ -2127,7 +2139,7 @@ def _adjust_dates_anchored(
     last: Timestamp,
     freq: Tick,
     closed: Literal["right", "left"] = "right",
-    origin="start_day",
+    origin: TimeGrouperOrigin = "start_day",
     offset: Timedelta | None = None,
 ) -> tuple[Timestamp, Timestamp]:
     # First and last offsets should be calculated from the start day to fix an
@@ -2143,11 +2155,11 @@ def _adjust_dates_anchored(
     elif isinstance(origin, Timestamp):
         origin_nanos = origin.value
     elif origin in ["end", "end_day"]:
-        origin = last if origin == "end" else last.ceil("D")
-        sub_freq_times = (origin.value - first.value) // freq.nanos
+        origin_last = last if origin == "end" else last.ceil("D")
+        sub_freq_times = (origin_last.value - first.value) // freq.nanos
         if closed == "left":
             sub_freq_times += 1
-        first = origin - sub_freq_times * freq
+        first = origin_last - sub_freq_times * freq
         origin_nanos = first.value
     origin_nanos += offset.value if offset else 0
 
diff --git a/pandas/core/reshape/encoding.py b/pandas/core/reshape/encoding.py
index 9567a1053c9a6..6670633fcc587 100644
--- a/pandas/core/reshape/encoding.py
+++ b/pandas/core/reshape/encoding.py
@@ -2,7 +2,10 @@
 
 from collections import defaultdict
 import itertools
-from typing import Hashable
+from typing import (
+    Hashable,
+    Iterable,
+)
 
 import numpy as np
 
@@ -25,7 +28,7 @@
 def get_dummies(
     data,
     prefix=None,
-    prefix_sep="_",
+    prefix_sep: str | Iterable[str] | dict[str, str] = "_",
     dummy_na: bool = False,
     columns=None,
     sparse: bool = False,
@@ -221,7 +224,7 @@ def check_len(item, name):
 def _get_dummies_1d(
     data,
     prefix,
-    prefix_sep="_",
+    prefix_sep: str | Iterable[str] | dict[str, str] = "_",
     dummy_na: bool = False,
     sparse: bool = False,
     drop_first: bool = False,
diff --git a/pandas/core/reshape/melt.py b/pandas/core/reshape/melt.py
index 73f6aff82f330..f35430e37e964 100644
--- a/pandas/core/reshape/melt.py
+++ b/pandas/core/reshape/melt.py
@@ -2,7 +2,10 @@
 
 import inspect
 import re
-from typing import TYPE_CHECKING
+from typing import (
+    TYPE_CHECKING,
+    Hashable,
+)
 import warnings
 
 import numpy as np
@@ -42,7 +45,7 @@ def melt(
     id_vars=None,
     value_vars=None,
     var_name=None,
-    value_name="value",
+    value_name: Hashable = "value",
     col_level=None,
     ignore_index: bool = True,
 ) -> DataFrame:
diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index a55a84735699d..8d1c20d5507a8 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -64,7 +64,7 @@ def pivot_table(
     fill_value=None,
     margins: bool = False,
     dropna: bool = True,
-    margins_name: str = "All",
+    margins_name: Hashable = "All",
     observed: bool = False,
     sort: bool = True,
 ) -> DataFrame:
@@ -119,7 +119,7 @@ def __internal_pivot_table(
     fill_value,
     margins: bool,
     dropna: bool,
-    margins_name: str,
+    margins_name: Hashable,
     observed: bool,
     sort: bool,
 ) -> DataFrame:
@@ -262,7 +262,7 @@ def _add_margins(
     cols,
     aggfunc,
     observed=None,
-    margins_name: str = "All",
+    margins_name: Hashable = "All",
     fill_value=None,
 ):
     if not isinstance(margins_name, str):
@@ -334,7 +334,9 @@ def _add_margins(
     return result
 
 
-def _compute_grand_margin(data: DataFrame, values, aggfunc, margins_name: str = "All"):
+def _compute_grand_margin(
+    data: DataFrame, values, aggfunc, margins_name: Hashable = "All"
+):
 
     if values:
         grand_margin = {}
@@ -357,7 +359,7 @@ def _compute_grand_margin(data: DataFrame, values, aggfunc, margins_name: str =
 
 
 def _generate_marginal_results(
-    table, data, values, rows, cols, aggfunc, observed, margins_name: str = "All"
+    table, data, values, rows, cols, aggfunc, observed, margins_name: Hashable = "All"
 ):
     if len(cols) > 0:
         # need to "interleave" the margins
@@ -427,7 +429,13 @@ def _all_key(key):
 
 
 def _generate_marginal_results_without_values(
-    table: DataFrame, data, rows, cols, aggfunc, observed, margins_name: str = "All"
+    table: DataFrame,
+    data,
+    rows,
+    cols,
+    aggfunc,
+    observed,
+    margins_name: Hashable = "All",
 ):
     if len(cols) > 0:
         # need to "interleave" the margins
@@ -555,7 +563,7 @@ def crosstab(
     colnames=None,
     aggfunc=None,
     margins: bool = False,
-    margins_name: str = "All",
+    margins_name: Hashable = "All",
     dropna: bool = True,
     normalize: bool = False,
 ) -> DataFrame:
@@ -696,7 +704,7 @@ def crosstab(
         kwargs = {"aggfunc": aggfunc}
 
     # error: Argument 7 to "pivot_table" of "DataFrame" has incompatible type
-    # "**Dict[str, object]"; expected "bool"
+    # "**Dict[str, object]"; expected "Union[...]"
     table = df.pivot_table(
         "__dummy__",
         index=unique_rownames,
@@ -720,7 +728,7 @@ def crosstab(
 
 
 def _normalize(
-    table: DataFrame, normalize, margins: bool, margins_name="All"
+    table: DataFrame, normalize, margins: bool, margins_name: Hashable = "All"
 ) -> DataFrame:
 
     if not isinstance(normalize, (bool, str)):
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 77a978647be31..b91d5540335f1 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -35,11 +35,14 @@
 from pandas._libs.lib import no_default
 from pandas._typing import (
     AggFuncType,
+    AlignJoin,
     AnyAll,
     AnyArrayLike,
     ArrayLike,
     Axis,
     AxisInt,
+    CorrelationMethod,
+    DropKeep,
     Dtype,
     DtypeObj,
     FilePath,
@@ -2251,28 +2254,23 @@ def unique(self) -> ArrayLike:
 
     @overload
     def drop_duplicates(
-        self,
-        keep: Literal["first", "last", False] = ...,
-        *,
-        inplace: Literal[False] = ...,
+        self, keep: DropKeep = ..., *, inplace: Literal[False] = ...
     ) -> Series:
         ...
 
     @overload
-    def drop_duplicates(
-        self, keep: Literal["first", "last", False] = ..., *, inplace: Literal[True]
-    ) -> None:
+    def drop_duplicates(self, keep: DropKeep = ..., *, inplace: Literal[True]) -> None:
         ...
 
     @overload
     def drop_duplicates(
-        self, keep: Literal["first", "last", False] = ..., *, inplace: bool = ...
+        self, keep: DropKeep = ..., *, inplace: bool = ...
     ) -> Series | None:
         ...
 
     @deprecate_nonkeyword_arguments(version=None, allowed_args=["self"])
     def drop_duplicates(
-        self, keep: Literal["first", "last", False] = "first", inplace: bool = False
+        self, keep: DropKeep = "first", inplace: bool = False
     ) -> Series | None:
         """
         Return Series with duplicate values removed.
@@ -2357,7 +2355,7 @@ def drop_duplicates(
         else:
             return result
 
-    def duplicated(self, keep: Literal["first", "last", False] = "first") -> Series:
+    def duplicated(self, keep: DropKeep = "first") -> Series:
         """
         Indicate duplicate Series values.
 
@@ -2706,8 +2704,7 @@ def quantile(
     def corr(
         self,
         other: Series,
-        method: Literal["pearson", "kendall", "spearman"]
-        | Callable[[np.ndarray, np.ndarray], float] = "pearson",
+        method: CorrelationMethod = "pearson",
         min_periods: int | None = None,
     ) -> float:
         """
@@ -4860,7 +4857,7 @@ def _needs_reindex_multi(self, axes, method, level) -> bool:
     def align(
         self,
         other: Series,
-        join: Literal["outer", "inner", "left", "right"] = "outer",
+        join: AlignJoin = "outer",
         axis: Axis | None = None,
         level: Level = None,
         copy: bool = True,
diff --git a/pandas/core/strings/accessor.py b/pandas/core/strings/accessor.py
index ab5439188cd0e..3f1176f42e44c 100644
--- a/pandas/core/strings/accessor.py
+++ b/pandas/core/strings/accessor.py
@@ -9,6 +9,7 @@
     Callable,
     Hashable,
     Iterator,
+    Literal,
     cast,
 )
 import warnings
@@ -17,6 +18,7 @@
 
 import pandas._libs.lib as lib
 from pandas._typing import (
+    AlignJoin,
     DtypeObj,
     F,
     Scalar,
@@ -427,7 +429,11 @@ def _get_series_list(self, others):
 
     @forbid_nonstring_types(["bytes", "mixed", "mixed-integer"])
     def cat(
-        self, others=None, sep=None, na_rep=None, join="left"
+        self,
+        others=None,
+        sep=None,
+        na_rep=None,
+        join: AlignJoin = "left",
     ) -> str | Series | Index:
         """
         Concatenate strings in the Series/Index with given separator.
@@ -979,7 +985,7 @@ def rsplit(self, pat=None, n=-1, expand: bool = False):
         }
     )
     @forbid_nonstring_types(["bytes"])
-    def partition(self, sep=" ", expand: bool = True):
+    def partition(self, sep: str = " ", expand: bool = True):
         result = self._data.array._str_partition(sep, expand)
         return self._wrap_result(result, expand=expand, returns_string=expand)
 
@@ -993,7 +999,7 @@ def partition(self, sep=" ", expand: bool = True):
         }
     )
     @forbid_nonstring_types(["bytes"])
-    def rpartition(self, sep=" ", expand: bool = True):
+    def rpartition(self, sep: str = " ", expand: bool = True):
         result = self._data.array._str_rpartition(sep, expand)
         return self._wrap_result(result, expand=expand, returns_string=expand)
 
@@ -1553,7 +1559,12 @@ def repeat(self, repeats):
         return self._wrap_result(result)
 
     @forbid_nonstring_types(["bytes"])
-    def pad(self, width, side="left", fillchar=" "):
+    def pad(
+        self,
+        width,
+        side: Literal["left", "right", "both"] = "left",
+        fillchar: str = " ",
+    ):
         """
         Pad strings in the Series/Index up to width.
 
@@ -1642,17 +1653,17 @@ def pad(self, width, side="left", fillchar=" "):
 
     @Appender(_shared_docs["str_pad"] % {"side": "left and right", "method": "center"})
     @forbid_nonstring_types(["bytes"])
-    def center(self, width, fillchar=" "):
+    def center(self, width, fillchar: str = " "):
         return self.pad(width, side="both", fillchar=fillchar)
 
     @Appender(_shared_docs["str_pad"] % {"side": "right", "method": "ljust"})
     @forbid_nonstring_types(["bytes"])
-    def ljust(self, width, fillchar=" "):
+    def ljust(self, width, fillchar: str = " "):
         return self.pad(width, side="right", fillchar=fillchar)
 
     @Appender(_shared_docs["str_pad"] % {"side": "left", "method": "rjust"})
     @forbid_nonstring_types(["bytes"])
-    def rjust(self, width, fillchar=" "):
+    def rjust(self, width, fillchar: str = " "):
         return self.pad(width, side="left", fillchar=fillchar)
 
     @forbid_nonstring_types(["bytes"])
@@ -1874,7 +1885,7 @@ def slice_replace(self, start=None, stop=None, repl=None):
         result = self._data.array._str_slice_replace(start, stop, repl)
         return self._wrap_result(result)
 
-    def decode(self, encoding, errors="strict"):
+    def decode(self, encoding, errors: str = "strict"):
         """
         Decode character string in the Series/Index using indicated encoding.
 
@@ -1903,7 +1914,7 @@ def decode(self, encoding, errors="strict"):
         return self._wrap_result(result)
 
     @forbid_nonstring_types(["bytes"])
-    def encode(self, encoding, errors="strict"):
+    def encode(self, encoding, errors: str = "strict"):
         """
         Encode character string in the Series/Index using indicated encoding.
 
@@ -2152,7 +2163,7 @@ def wrap(self, width, **kwargs):
         return self._wrap_result(result)
 
     @forbid_nonstring_types(["bytes"])
-    def get_dummies(self, sep="|"):
+    def get_dummies(self, sep: str = "|"):
         """
         Return DataFrame of dummy/indicator variables for Series.
 
diff --git a/pandas/core/strings/base.py b/pandas/core/strings/base.py
index ae9a480ef73be..ae39526871d63 100644
--- a/pandas/core/strings/base.py
+++ b/pandas/core/strings/base.py
@@ -3,7 +3,10 @@
 import abc
 from collections.abc import Callable  # noqa: PDF001
 import re
-from typing import TYPE_CHECKING
+from typing import (
+    TYPE_CHECKING,
+    Literal,
+)
 
 import numpy as np
 
@@ -40,7 +43,12 @@ def _str_count(self, pat, flags=0):
         pass
 
     @abc.abstractmethod
-    def _str_pad(self, width, side="left", fillchar=" "):
+    def _str_pad(
+        self,
+        width,
+        side: Literal["left", "right", "both"] = "left",
+        fillchar: str = " ",
+    ):
         pass
 
     @abc.abstractmethod
@@ -90,7 +98,7 @@ def _str_fullmatch(
         pass
 
     @abc.abstractmethod
-    def _str_encode(self, encoding, errors="strict"):
+    def _str_encode(self, encoding, errors: str = "strict"):
         pass
 
     @abc.abstractmethod
@@ -150,7 +158,7 @@ def _str_wrap(self, width, **kwargs):
         pass
 
     @abc.abstractmethod
-    def _str_get_dummies(self, sep="|"):
+    def _str_get_dummies(self, sep: str = "|"):
         pass
 
     @abc.abstractmethod
diff --git a/pandas/core/strings/object_array.py b/pandas/core/strings/object_array.py
index 26843146b3633..e9b05f0d4e0e4 100644
--- a/pandas/core/strings/object_array.py
+++ b/pandas/core/strings/object_array.py
@@ -3,7 +3,10 @@
 from collections.abc import Callable  # noqa: PDF001
 import re
 import textwrap
-from typing import TYPE_CHECKING
+from typing import (
+    TYPE_CHECKING,
+    Literal,
+)
 import unicodedata
 
 import numpy as np
@@ -103,7 +106,12 @@ def _str_count(self, pat, flags=0):
         f = lambda x: len(regex.findall(x))
         return self._str_map(f, dtype="int64")
 
-    def _str_pad(self, width, side="left", fillchar=" "):
+    def _str_pad(
+        self,
+        width,
+        side: Literal["left", "right", "both"] = "left",
+        fillchar: str = " ",
+    ):
         if side == "left":
             f = lambda x: x.rjust(width, fillchar)
         elif side == "right":
@@ -220,7 +228,7 @@ def _str_fullmatch(
         f = lambda x: regex.fullmatch(x) is not None
         return self._str_map(f, na_value=na, dtype=np.dtype(bool))
 
-    def _str_encode(self, encoding, errors="strict"):
+    def _str_encode(self, encoding, errors: str = "strict"):
         f = lambda x: x.encode(encoding, errors=errors)
         return self._str_map(f, dtype=object)
 
@@ -356,7 +364,7 @@ def _str_wrap(self, width, **kwargs):
         tw = textwrap.TextWrapper(**kwargs)
         return self._str_map(lambda s: "\n".join(tw.wrap(s)))
 
-    def _str_get_dummies(self, sep="|"):
+    def _str_get_dummies(self, sep: str = "|"):
         from pandas import Series
 
         arr = Series(self).fillna("")
diff --git a/pandas/core/tools/datetimes.py b/pandas/core/tools/datetimes.py
index 565d2f2897514..dd4b21ade5cf8 100644
--- a/pandas/core/tools/datetimes.py
+++ b/pandas/core/tools/datetimes.py
@@ -329,7 +329,7 @@ def _convert_listlike_datetimes(
     name: Hashable = None,
     tz: Timezone | None = None,
     unit: str | None = None,
-    errors: str = "raise",
+    errors: DateTimeErrorChoices = "raise",
     infer_datetime_format: bool = False,
     dayfirst: bool | None = None,
     yearfirst: bool | None = None,
@@ -713,7 +713,7 @@ def to_datetime(
     exact: bool = True,
     unit: str | None = None,
     infer_datetime_format: bool = False,
-    origin="unix",
+    origin: str = "unix",
     cache: bool = True,
 ) -> DatetimeIndex | Series | DatetimeScalar | NaTType | None:
     """
@@ -1306,7 +1306,12 @@ def calc_with_mask(carg, mask):
     return None
 
 
-def to_time(arg, format=None, infer_time_format: bool = False, errors="raise"):
+def to_time(
+    arg,
+    format=None,
+    infer_time_format: bool = False,
+    errors: DateTimeErrorChoices = "raise",
+):
     # GH#34145
     warnings.warn(
         "`to_time` has been moved, should be imported from pandas.core.tools.times. "
diff --git a/pandas/core/tools/numeric.py b/pandas/core/tools/numeric.py
index ef7f4bc92e25b..9b158a6b5aed2 100644
--- a/pandas/core/tools/numeric.py
+++ b/pandas/core/tools/numeric.py
@@ -1,9 +1,14 @@
 from __future__ import annotations
 
+from typing import Literal
+
 import numpy as np
 
 from pandas._libs import lib
-from pandas._typing import npt
+from pandas._typing import (
+    DateTimeErrorChoices,
+    npt,
+)
 
 from pandas.core.dtypes.cast import maybe_downcast_numeric
 from pandas.core.dtypes.common import (
@@ -25,7 +30,11 @@
 from pandas.core.arrays.numeric import NumericArray
 
 
-def to_numeric(arg, errors="raise", downcast=None):
+def to_numeric(
+    arg,
+    errors: DateTimeErrorChoices = "raise",
+    downcast: Literal["integer", "signed", "unsigned", "float"] | None = None,
+):
     """
     Convert argument to a numeric type.
 
diff --git a/pandas/core/tools/timedeltas.py b/pandas/core/tools/timedeltas.py
index 5026c97c0b2b0..705c77090e168 100644
--- a/pandas/core/tools/timedeltas.py
+++ b/pandas/core/tools/timedeltas.py
@@ -211,7 +211,9 @@ def to_timedelta(
     return _coerce_scalar_to_timedelta_type(arg, unit=unit, errors=errors)
 
 
-def _coerce_scalar_to_timedelta_type(r, unit="ns", errors="raise"):
+def _coerce_scalar_to_timedelta_type(
+    r, unit: UnitChoices | None = "ns", errors: DateTimeErrorChoices = "raise"
+):
     """Convert string 'r' to a timedelta object."""
     result: Timedelta | NaTType
 
@@ -229,7 +231,9 @@ def _coerce_scalar_to_timedelta_type(r, unit="ns", errors="raise"):
     return result
 
 
-def _convert_listlike(arg, unit=None, errors="raise", name=None):
+def _convert_listlike(
+    arg, unit=None, errors: DateTimeErrorChoices = "raise", name=None
+):
     """Convert a list of objects to a timedelta index object."""
     if isinstance(arg, (list, tuple)) or not hasattr(arg, "dtype"):
         # This is needed only to ensure that in the case where we end up
diff --git a/pandas/core/tools/times.py b/pandas/core/tools/times.py
index bb100fab0ba8d..d0a4342254e16 100644
--- a/pandas/core/tools/times.py
+++ b/pandas/core/tools/times.py
@@ -8,6 +8,7 @@
 import numpy as np
 
 from pandas._libs.lib import is_list_like
+from pandas._typing import DateTimeErrorChoices
 
 from pandas.core.dtypes.generic import (
     ABCIndex,
@@ -16,7 +17,12 @@
 from pandas.core.dtypes.missing import notna
 
 
-def to_time(arg, format=None, infer_time_format: bool = False, errors="raise"):
+def to_time(
+    arg,
+    format=None,
+    infer_time_format: bool = False,
+    errors: DateTimeErrorChoices = "raise",
+):
     """
     Parse time strings to time objects using fixed strptime formats ("%H:%M",
     "%H%M", "%I:%M%p", "%I%M%p", "%H:%M:%S", "%H%M%S", "%I:%M:%S%p",
diff --git a/pandas/core/window/ewm.py b/pandas/core/window/ewm.py
index 32559d0d88bcf..6fae119bffdf1 100644
--- a/pandas/core/window/ewm.py
+++ b/pandas/core/window/ewm.py
@@ -447,7 +447,7 @@ def _get_window_indexer(self) -> BaseIndexer:
         return ExponentialMovingWindowIndexer()
 
     def online(
-        self, engine="numba", engine_kwargs=None
+        self, engine: str = "numba", engine_kwargs=None
     ) -> OnlineExponentialMovingWindow:
         """
         Return an ``OnlineExponentialMovingWindow`` object to calculate
diff --git a/pandas/io/formats/format.py b/pandas/io/formats/format.py
index 5045b351a9525..cdc21f04da43a 100644
--- a/pandas/io/formats/format.py
+++ b/pandas/io/formats/format.py
@@ -1857,7 +1857,7 @@ def _format_strings(self) -> list[str]:
 
 def get_format_timedelta64(
     values: np.ndarray | TimedeltaIndex | TimedeltaArray,
-    nat_rep: str = "NaT",
+    nat_rep: str | float = "NaT",
     box: bool = False,
 ) -> Callable:
     """
diff --git a/pandas/io/formats/style.py b/pandas/io/formats/style.py
index be8f0e22a5174..0d8c970c414f0 100644
--- a/pandas/io/formats/style.py
+++ b/pandas/io/formats/style.py
@@ -9,6 +9,7 @@
 import inspect
 import operator
 from typing import (
+    TYPE_CHECKING,
     Any,
     Callable,
     Generator,
@@ -71,6 +72,9 @@
     refactor_levels,
 )
 
+if TYPE_CHECKING:
+    from matplotlib.colors import Colormap
+
 try:
     import matplotlib as mpl
     import matplotlib.pyplot as plt
@@ -2996,7 +3000,7 @@ def _get_numeric_subset_default(self):
     @Substitution(subset=subset)
     def background_gradient(
         self,
-        cmap="PuBu",
+        cmap: str | Colormap = "PuBu",
         low: float = 0,
         high: float = 0,
         axis: Axis | None = 0,
@@ -3151,7 +3155,7 @@ def background_gradient(
     )
     def text_gradient(
         self,
-        cmap="PuBu",
+        cmap: str | Colormap = "PuBu",
         low: float = 0,
         high: float = 0,
         axis: Axis | None = 0,
@@ -3907,7 +3911,7 @@ def _validate_apply_axis_arg(
 
 def _background_gradient(
     data,
-    cmap="PuBu",
+    cmap: str | Colormap = "PuBu",
     low: float = 0,
     high: float = 0,
     text_color_threshold: float = 0.408,
diff --git a/pandas/io/formats/style_render.py b/pandas/io/formats/style_render.py
index dd56928d3a496..b8ea0374c0288 100644
--- a/pandas/io/formats/style_render.py
+++ b/pandas/io/formats/style_render.py
@@ -621,12 +621,12 @@ def _translate_body(self, idx_lengths: dict, max_rows: int, max_cols: int):
 
     def _check_trim(
         self,
-        count,
-        max,
-        obj,
-        element,
-        css=None,
-        value="...",
+        count: int,
+        max: int,
+        obj: list,
+        element: str,
+        css: str | None = None,
+        value: str = "...",
     ) -> bool:
         """
         Indicates whether to break render loops and append a trimming indicator
@@ -1503,7 +1503,7 @@ def alias_(x, value):
 
 def _element(
     html_element: str,
-    html_class: str,
+    html_class: str | None,
     value: Any,
     is_visible: bool,
     **kwargs,
@@ -1528,7 +1528,7 @@ def _get_trimming_maximums(
     max_elements,
     max_rows=None,
     max_cols=None,
-    scaling_factor=0.8,
+    scaling_factor: float = 0.8,
 ) -> tuple[int, int]:
     """
     Recursively reduce the number of rows and columns to satisfy max elements.
diff --git a/pandas/io/parquet.py b/pandas/io/parquet.py
index b4abd6aea6b20..6f297457ced41 100644
--- a/pandas/io/parquet.py
+++ b/pandas/io/parquet.py
@@ -3,7 +3,10 @@
 
 import io
 import os
-from typing import Any
+from typing import (
+    Any,
+    Literal,
+)
 from warnings import catch_warnings
 
 from pandas._typing import (
@@ -270,7 +273,7 @@ def write(
         self,
         df: DataFrame,
         path,
-        compression="snappy",
+        compression: Literal["snappy", "gzip", "brotli"] | None = "snappy",
         index=None,
         partition_cols=None,
         storage_options: StorageOptions = None,
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index 75cbf57f82644..39273a28b6d0f 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -1531,7 +1531,7 @@ def get_storer(self, key: str) -> GenericFixed | Table:
     def copy(
         self,
         file,
-        mode="w",
+        mode: str = "w",
         propindexes: bool = True,
         keys=None,
         complib=None,
diff --git a/pandas/io/sql.py b/pandas/io/sql.py
index 4bc2de32a20d5..9beafb9032676 100644
--- a/pandas/io/sql.py
+++ b/pandas/io/sql.py
@@ -18,6 +18,7 @@
     TYPE_CHECKING,
     Any,
     Iterator,
+    Literal,
     cast,
     overload,
 )
@@ -603,7 +604,7 @@ def to_sql(
     name: str,
     con,
     schema: str | None = None,
-    if_exists: str = "fail",
+    if_exists: Literal["fail", "replace", "append"] = "fail",
     index: bool = True,
     index_label: IndexLabel = None,
     chunksize: int | None = None,
@@ -784,7 +785,7 @@ def __init__(
         pandas_sql_engine,
         frame=None,
         index: bool | str | list[str] | None = True,
-        if_exists: str = "fail",
+        if_exists: Literal["fail", "replace", "append"] = "fail",
         prefix: str = "pandas",
         index_label=None,
         schema=None,
@@ -1269,7 +1270,7 @@ def to_sql(
         self,
         frame,
         name,
-        if_exists: str = "fail",
+        if_exists: Literal["fail", "replace", "append"] = "fail",
         index: bool = True,
         index_label=None,
         schema=None,
@@ -1589,7 +1590,7 @@ def prep_table(
         self,
         frame,
         name,
-        if_exists="fail",
+        if_exists: Literal["fail", "replace", "append"] = "fail",
         index: bool | str | list[str] | None = True,
         index_label=None,
         schema=None,
@@ -1666,14 +1667,14 @@ def to_sql(
         self,
         frame,
         name,
-        if_exists: str = "fail",
+        if_exists: Literal["fail", "replace", "append"] = "fail",
         index: bool = True,
         index_label=None,
         schema=None,
         chunksize=None,
         dtype: DtypeArg | None = None,
         method=None,
-        engine="auto",
+        engine: str = "auto",
         **engine_kwargs,
     ) -> int | None:
         """
diff --git a/pandas/plotting/_matplotlib/boxplot.py b/pandas/plotting/_matplotlib/boxplot.py
index ae61a9743ca1d..6067f7e7fca84 100644
--- a/pandas/plotting/_matplotlib/boxplot.py
+++ b/pandas/plotting/_matplotlib/boxplot.py
@@ -3,6 +3,7 @@
 import inspect
 from typing import (
     TYPE_CHECKING,
+    Collection,
     Literal,
     NamedTuple,
 )
@@ -11,6 +12,7 @@
 from matplotlib.artist import setp
 import numpy as np
 
+from pandas._typing import MatplotlibColor
 from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import is_dict_like
@@ -68,8 +70,11 @@ def _args_adjust(self) -> None:
             else:
                 self.sharey = False
 
+    # error: Signature of "_plot" incompatible with supertype "MPLPlot"
     @classmethod
-    def _plot(cls, ax, y, column_num=None, return_type="axes", **kwds):
+    def _plot(  # type: ignore[override]
+        cls, ax, y, column_num=None, return_type: str = "axes", **kwds
+    ):
         if y.ndim == 2:
             y = [remove_na_arraylike(v) for v in y]
             # Boxplot fails with empty arrays, so need to add a NaN
@@ -118,7 +123,14 @@ def _validate_color_args(self):
         self._medians_c = colors[2]
         self._caps_c = colors[0]
 
-    def _get_colors(self, num_colors=None, color_kwds="color") -> None:
+    def _get_colors(
+        self,
+        num_colors=None,
+        color_kwds: dict[str, MatplotlibColor]
+        | MatplotlibColor
+        | Collection[MatplotlibColor]
+        | None = "color",
+    ) -> None:
         pass
 
     def maybe_color_bp(self, bp) -> None:
diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index a02e81935f696..9dcc858c6e589 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -987,7 +987,11 @@ def _apply_style_colors(self, colors, kwds, col_num, label):
                 kwds["color"] = colors[col_num % len(colors)]
         return style, kwds
 
-    def _get_colors(self, num_colors=None, color_kwds="color"):
+    def _get_colors(
+        self,
+        num_colors: int | None = None,
+        color_kwds: str = "color",
+    ):
         if num_colors is None:
             num_colors = self.nseries
 
diff --git a/pandas/plotting/_matplotlib/style.py b/pandas/plotting/_matplotlib/style.py
index d8823c7ec8d3d..c1b37eca2a76c 100644
--- a/pandas/plotting/_matplotlib/style.py
+++ b/pandas/plotting/_matplotlib/style.py
@@ -6,8 +6,6 @@
     TYPE_CHECKING,
     Collection,
     Iterator,
-    Sequence,
-    Union,
     cast,
 )
 import warnings
@@ -17,6 +15,7 @@
 import matplotlib.colors
 import numpy as np
 
+from pandas._typing import MatplotlibColor as Color
 from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import is_list_like
@@ -29,9 +28,6 @@
     from matplotlib.colors import Colormap
 
 
-Color = Union[str, Sequence[float]]
-
-
 def get_standard_colors(
     num_colors: int,
     colormap: Colormap | None = None,
diff --git a/pyright_reportGeneralTypeIssues.json b/pyright_reportGeneralTypeIssues.json
index 940364e580d12..761018c3ce496 100644
--- a/pyright_reportGeneralTypeIssues.json
+++ b/pyright_reportGeneralTypeIssues.json
@@ -17,6 +17,7 @@
         # and all files that currently don't pass
         "pandas/_testing/__init__.py",
         "pandas/_testing/_hypothesis.py",
+        "pandas/_testing/_io.py",
         "pandas/compat/pickle_compat.py",
         "pandas/core/algorithms.py",
         "pandas/core/apply.py",
@@ -80,6 +81,7 @@
         "pandas/core/sorting.py",
         "pandas/core/strings/accessor.py",
         "pandas/core/tools/datetimes.py",
+        "pandas/core/tools/numeric.py",
         "pandas/core/tools/timedeltas.py",
         "pandas/core/util/hashing.py",
         "pandas/core/window/ewm.py",