Merge remote-tracking branch 'upstream/main' into move-to-1.5.0

Author: Kevin Sheppard

pandas-stubs/_libs/tslibs/timestamps.pyi

@@ -77,7 +77,7 @@ class Timestamp(datetime):
         cls: type[_DatetimeT], t: float, tz: _tzinfo | None = ...
     ) -> _DatetimeT: ...
     @classmethod
-    def utcfromtimestamp(cls: type[_DatetimeT], t: float) -> _DatetimeT: ...
+    def utcfromtimestamp(cls: type[_DatetimeT], ts: float) -> _DatetimeT: ...
     @classmethod
     def today(cls: type[_DatetimeT], tz: _tzinfo | str | None = ...) -> _DatetimeT: ...
     @classmethod

pandas-stubs/core/arrays/base.pyi

@@ -47,7 +47,7 @@ class ExtensionArray:
     ) -> tuple[np.ndarray, ABCExtensionArray]: ...
     def repeat(self, repeats, axis=...): ...
     def take(
-        self, indices: Sequence[int], allow_fill: bool = ..., fill_value=...
+        self, indices: Sequence[int], *, allow_fill: bool = ..., fill_value=...
     ) -> ABCExtensionArray: ...
     def copy(self) -> ABCExtensionArray: ...
     def view(self, dtype=...) -> ABCExtensionArray | np.ndarray: ...

pandas-stubs/core/arrays/interval.pyi

@@ -44,7 +44,7 @@ class IntervalArray(IntervalMixin, ExtensionArray):
         self, periods: int = ..., fill_value: object = ...
     ) -> ABCExtensionArray: ...
     def take(
-        self, indices, allow_fill: bool = ..., fill_value=..., axis=..., **kwargs
+        self, indices, *, allow_fill: bool = ..., fill_value=..., axis=..., **kwargs
     ): ...
     def value_counts(self, dropna: bool = ...): ...
     @property

pandas-stubs/core/arrays/numpy_.pyi

@@ -5,11 +5,6 @@ from pandas.core.arrays.base import (
     ExtensionOpsMixin,
 )
 
-from pandas._typing import (
-    Scalar,
-    npt,
-)
-
 from pandas.core.dtypes.dtypes import ExtensionDtype
 
 class PandasDtype(ExtensionDtype):
@@ -30,95 +25,4 @@ class PandasDtype(ExtensionDtype):
     def itemsize(self): ...
 
 class PandasArray(ExtensionArray, ExtensionOpsMixin, NDArrayOperatorsMixin):
-    __array_priority__: int = ...
-    def __init__(self, values: np.ndarray | PandasArray, copy: bool = ...) -> None: ...
-    @property
-    def dtype(self): ...
-    def __array__(self, dtype=...) -> np.ndarray: ...
     def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): ...
-    def __getitem__(self, item): ...
-    def __setitem__(self, key, value) -> None: ...
-    def __len__(self) -> int: ...
-    @property
-    def nbytes(self) -> int: ...
-    def isna(self): ...
-    def fillna(self, value=..., method=..., limit=...): ...
-    def take(self, indices, allow_fill: bool = ..., fill_value=...): ...
-    def copy(self): ...
-    def unique(self): ...
-    def any(self, axis=..., out=..., keepdims: bool = ..., skipna: bool = ...): ...
-    def all(self, axis=..., out=..., keepdims: bool = ..., skipna: bool = ...): ...
-    def min(self, axis=..., out=..., keepdims: bool = ..., skipna: bool = ...): ...
-    def max(self, axis=..., out=..., keepdims: bool = ..., skipna: bool = ...): ...
-    def sum(
-        self,
-        axis=...,
-        dtype=...,
-        out=...,
-        keepdims: bool = ...,
-        initial=...,
-        skipna: bool = ...,
-        min_count: int = ...,
-    ): ...
-    def prod(
-        self,
-        axis=...,
-        dtype=...,
-        out=...,
-        keepdims: bool = ...,
-        initial=...,
-        skipna: bool = ...,
-        min_count: int = ...,
-    ): ...
-    def mean(
-        self, axis=..., dtype=..., out=..., keepdims: bool = ..., skipna: bool = ...
-    ): ...
-    def median(
-        self,
-        axis=...,
-        out=...,
-        overwrite_input: bool = ...,
-        keepdims: bool = ...,
-        skipna: bool = ...,
-    ): ...
-    def std(
-        self,
-        axis=...,
-        dtype=...,
-        out=...,
-        ddof: int = ...,
-        keepdims: bool = ...,
-        skipna: bool = ...,
-    ): ...
-    def var(
-        self,
-        axis=...,
-        dtype=...,
-        out=...,
-        ddof: int = ...,
-        keepdims: bool = ...,
-        skipna: bool = ...,
-    ): ...
-    def sem(
-        self,
-        axis=...,
-        dtype=...,
-        out=...,
-        ddof: int = ...,
-        keepdims: bool = ...,
-        skipna: bool = ...,
-    ): ...
-    def kurt(
-        self, axis=..., dtype=..., out=..., keepdims: bool = ..., skipna: bool = ...
-    ): ...
-    def skew(
-        self, axis=..., dtype=..., out=..., keepdims: bool = ..., skipna: bool = ...
-    ): ...
-    def to_numpy(
-        self,
-        dtype: npt.DTypeLike | None = ...,
-        copy: bool = ...,
-        na_value: Scalar = ...,
-    ) -> np.ndarray: ...
-    def searchsorted(self, value, side: str = ..., sorter=...): ...
-    def __invert__(self): ...

pandas-stubs/core/arrays/string_.pyi

@@ -1,8 +1,8 @@
-from pandas.core.arrays import PandasArray as PandasArray
+from pandas.core.arrays import PandasArray
 
 from pandas._typing import type_t
 
-from pandas.core.dtypes.base import ExtensionDtype as ExtensionDtype
+from pandas.core.dtypes.base import ExtensionDtype
 
 class StringDtype(ExtensionDtype):
     name: str = ...

pandas-stubs/core/arrays/timedeltas.pyi

@@ -14,6 +14,7 @@ class TimedeltaArray(DatetimeLikeArrayMixin, TimelikeOps):
     def astype(self, dtype, copy: bool = ...): ...
     def sum(
         self,
+        *,
         axis=...,
         dtype=...,
         out=...,
@@ -24,6 +25,7 @@ class TimedeltaArray(DatetimeLikeArrayMixin, TimelikeOps):
     ): ...
     def std(
         self,
+        *,
         axis=...,
         dtype=...,
         out=...,
@@ -33,6 +35,7 @@ class TimedeltaArray(DatetimeLikeArrayMixin, TimelikeOps):
     ): ...
     def median(
         self,
+        *,
         axis=...,
         out=...,
         overwrite_input: bool = ...,

pandas-stubs/core/dtypes/missing.pyi

@@ -30,7 +30,7 @@ def isna(obj: Index | list | ArrayLike) -> npt.NDArray[np.bool_]: ...
 @overload
 def isna(obj: Scalar) -> bool: ...
 @overload
-def isna(obj: NaTType | NAType) -> Literal[True]: ...
+def isna(obj: NaTType | NAType | None) -> Literal[True]: ...
 
 isnull = isna
 
@@ -43,6 +43,6 @@ def notna(obj: Index | list | ArrayLike) -> npt.NDArray[np.bool_]: ...
 @overload
 def notna(obj: Scalar) -> bool: ...
 @overload
-def notna(obj: NaTType | NAType) -> Literal[False]: ...
+def notna(obj: NaTType | NAType | None) -> Literal[False]: ...
 
 notnull = notna

pandas-stubs/core/frame.pyi

@@ -1777,6 +1777,7 @@ class DataFrame(NDFrame, OpsMixin):
         min_periods: int | None = ...,
         center: _bool = ...,
         *,
+        win_type: None = ...,
         on: Hashable | None = ...,
         axis: AxisType = ...,
         closed: IntervalClosedType | None = ...,

pandas-stubs/core/indexes/datetimes.pyi

@@ -1,4 +1,7 @@
-from datetime import tzinfo
+from datetime import (
+    timedelta,
+    tzinfo,
+)
 from typing import overload
 
 import numpy as np
@@ -90,7 +93,7 @@ def date_range(
     start: str | DatetimeLike | None = ...,
     end: str | DatetimeLike | None = ...,
     periods: int | None = ...,
-    freq: str | BaseOffset = ...,
+    freq: str | timedelta | Timedelta | BaseOffset = ...,
     tz: str | tzinfo = ...,
     normalize: bool = ...,
     name: str | None = ...,
@@ -101,7 +104,7 @@ def bdate_range(
     start: str | DatetimeLike | None = ...,
     end: str | DatetimeLike | None = ...,
     periods: int | None = ...,
-    freq: str | BaseOffset = ...,
+    freq: str | timedelta | Timedelta | BaseOffset = ...,
     tz: str | tzinfo = ...,
     normalize: bool = ...,
     name: str | None = ...,

pandas-stubs/core/indexes/timedeltas.pyi

@@ -36,7 +36,6 @@ class TimedeltaIndex(DatetimeTimedeltaMixin, TimedeltaIndexProperties):
     def get_value(self, series, key): ...
     def get_loc(self, key, tolerance=...): ...
     def searchsorted(self, value, side: str = ..., sorter=...): ...
-    def is_type_compatible(self, typ) -> bool: ...
     @property
     def inferred_type(self) -> str: ...
     def insert(self, loc, item): ...