Gh1318 defaults p3

pandas-stubs/core/arrays/boolean.pyi

@@ -22,13 +22,13 @@ class BooleanDtype(ExtensionDtype):
 
 class BooleanArray(BaseMaskedArray):
     def __init__(
-        self, values: np_ndarray_bool, mask: np_ndarray_bool, copy: bool = ...
+        self, values: np_ndarray_bool, mask: np_ndarray_bool, copy: bool = False
     ) -> None: ...
     @property
     def dtype(self): ...
     def __setitem__(self, key, value) -> None: ...
-    def any(self, *, skipna: bool = ..., **kwargs: Any): ...
-    def all(self, *, skipna: bool = ..., **kwargs: Any): ...
+    def any(self, *, skipna: bool = True, **kwargs: Any): ...
+    def all(self, *, skipna: bool = True, **kwargs: Any): ...
     def __and__(
         self,
         other: (

pandas-stubs/core/arrays/masked.pyi

@@ -27,11 +27,11 @@ class BaseMaskedArray(ExtensionArray, ExtensionOpsMixin):
     def __invert__(self): ...
     def to_numpy(
         self,
-        dtype: npt.DTypeLike | None = ...,
+        dtype: npt.DTypeLike | None = None,
         copy: bool = False,
         na_value: Scalar = ...,
     ) -> np_1darray: ...
-    __array_priority__: int = ...
+    __array_priority__: int = 1000
     def __array__(
         self, dtype: NpDtype | None = None, copy: bool | None = None
     ) -> np_1darray: ...

pandas-stubs/core/arrays/sparse/array.pyi

@@ -12,6 +12,8 @@ from pandas.core.arrays import (
 from typing_extensions import Self
 
 from pandas._typing import (
+    AxisInt,
+    DtypeArg,
     NpDtype,
     ScalarIndexer,
     SequenceIndexer,
@@ -28,9 +30,9 @@ class SparseArray(ExtensionArray, ExtensionOpsMixin):
         data,
         sparse_index=...,
         fill_value=...,
-        kind: str = ...,
-        dtype=...,
-        copy: bool = ...,
+        kind: str = "integer",
+        dtype: DtypeArg | None = None,
+        copy: bool = False,
     ) -> None: ...
     @classmethod
     def from_spmatrix(cls, data) -> Self: ...
@@ -73,10 +75,10 @@ class SparseArray(ExtensionArray, ExtensionOpsMixin):
     def to_dense(self): ...
     def nonzero(self): ...
     def all(self, axis=..., *args: Any, **kwargs: Any): ...
-    def any(self, axis: int = ..., *args: Any, **kwargs: Any): ...
-    def sum(self, axis: int = 0, *args: Any, **kwargs: Any): ...
-    def cumsum(self, axis: int = ..., *args: Any, **kwargs: Any): ...
-    def mean(self, axis: int = ..., *args: Any, **kwargs: Any): ...
+    def any(self, axis: AxisInt = 0, *args: Any, **kwargs: Any): ...
+    def sum(self, axis: AxisInt = 0, *args: Any, **kwargs: Any): ...
+    def cumsum(self, axis: AxisInt = 0, *args: Any, **kwargs: Any): ...
+    def mean(self, axis: AxisInt = 0, *args: Any, **kwargs: Any): ...
     @property
     def T(self): ...
     def __abs__(self): ...

pandas-stubs/core/arrays/sparse/dtype.pyi

@@ -11,7 +11,9 @@ from pandas.core.dtypes.dtypes import (
 
 class SparseDtype(ExtensionDtype):
     def __init__(
-        self, dtype: Dtype | npt.DTypeLike = ..., fill_value: Scalar | None = ...
+        self,
+        dtype: Dtype | npt.DTypeLike = ...,
+        fill_value: Scalar | None = None,
     ) -> None: ...
     @property
     def fill_value(self) -> Scalar | None: ...

pandas-stubs/core/indexes/accessors.pyi

@@ -180,32 +180,32 @@ class _DatetimeRoundingMethods(Generic[_DTTimestampTimedeltaReturnType]):
     def round(
         self,
         freq: Frequency | None,
-        ambiguous: Literal["raise", "infer", "NaT"] | bool | np_ndarray_bool = ...,
+        ambiguous: Literal["raise", "infer", "NaT"] | bool | np_ndarray_bool = "raise",
         nonexistent: (
             Literal["shift_forward", "shift_backward", "NaT", "raise"]
             | timedelta
             | Timedelta
-        ) = ...,
+        ) = "raise",
     ) -> _DTTimestampTimedeltaReturnType: ...
     def floor(
         self,
         freq: Frequency | None,
-        ambiguous: Literal["raise", "infer", "NaT"] | bool | np_ndarray_bool = ...,
+        ambiguous: Literal["raise", "infer", "NaT"] | bool | np_ndarray_bool = "raise",
         nonexistent: (
             Literal["shift_forward", "shift_backward", "NaT", "raise"]
             | timedelta
             | Timedelta
-        ) = ...,
+        ) = "raise",
     ) -> _DTTimestampTimedeltaReturnType: ...
     def ceil(
         self,
         freq: Frequency | None,
-        ambiguous: Literal["raise", "infer", "NaT"] | bool | np_ndarray_bool = ...,
+        ambiguous: Literal["raise", "infer", "NaT"] | bool | np_ndarray_bool = "raise",
         nonexistent: (
             Literal["shift_forward", "shift_backward", "NaT", "raise"]
             | timedelta
             | Timedelta
-        ) = ...,
+        ) = "raise",
     ) -> _DTTimestampTimedeltaReturnType: ...
 
 _DTNormalizeReturnType = TypeVar(
@@ -231,14 +231,14 @@ class _DatetimeLikeNoTZMethods(
     def tz_localize(
         self,
         tz: TimeZones,
-        ambiguous: TimeAmbiguous = ...,
-        nonexistent: TimeNonexistent = ...,
+        ambiguous: TimeAmbiguous = "raise",
+        nonexistent: TimeNonexistent = "raise",
     ) -> _DTNormalizeReturnType: ...
     def tz_convert(self, tz: TimeZones) -> _DTNormalizeReturnType: ...
     def normalize(self) -> _DTNormalizeReturnType: ...
     def strftime(self, date_format: str) -> _DTStrKindReturnType: ...
-    def month_name(self, locale: str | None = ...) -> _DTStrKindReturnType: ...
-    def day_name(self, locale: str | None = ...) -> _DTStrKindReturnType: ...
+    def month_name(self, locale: str | None = None) -> _DTStrKindReturnType: ...
+    def day_name(self, locale: str | None = None) -> _DTStrKindReturnType: ...
 
 class _DatetimeNoTZProperties(
     _DatetimeLikeOps[
@@ -359,12 +359,12 @@ class _PeriodProperties(
     def to_timestamp(
         self,
         freq: PeriodFrequency | None = None,
-        how: TimestampConvention = ...,
+        how: TimestampConvention = "start",
     ) -> _PeriodDTAReturnTypes: ...
     def asfreq(
         self,
         freq: PeriodFrequency | None = None,
-        how: Literal["E", "END", "FINISH", "S", "START", "BEGIN"] = ...,
+        how: Literal["E", "END", "FINISH", "S", "START", "BEGIN"] = "E",
     ) -> _PeriodPAReturnTypes: ...
 
 class PeriodIndexFieldOps(
@@ -432,7 +432,7 @@ class DatetimeIndexProperties(
     def tzinfo(self) -> _tzinfo | None: ...
     def to_pydatetime(self) -> np_1darray_object: ...
     def std(
-        self, axis: int | None = ..., ddof: int = ..., skipna: bool = ...
+        self, axis: int | None = None, ddof: int = 1, skipna: bool = True
     ) -> Timedelta: ...
 
 class TimedeltaIndexProperties(