TYP: pandas.core.series annotations from pandas-stubs (#47926)

* TYP: pandas.core.series annotations from pandas-stubs

* and DataFrame

* more compatibility with pandas-stub tests

* mypy address line-off-by-one (merge?) issue

pandas/_testing/asserters.py

@@ -866,7 +866,7 @@ def assert_series_equal(
     left,
     right,
     check_dtype: bool | Literal["equiv"] = True,
-    check_index_type="equiv",
+    check_index_type: bool | Literal["equiv"] = "equiv",
     check_series_type=True,
     check_less_precise: bool | int | NoDefault = no_default,
     check_names=True,
@@ -1134,7 +1134,7 @@ def assert_frame_equal(
     left,
     right,
     check_dtype: bool | Literal["equiv"] = True,
-    check_index_type="equiv",
+    check_index_type: bool | Literal["equiv"] = "equiv",
     check_column_type="equiv",
     check_frame_type=True,
     check_less_precise=no_default,

pandas/_typing.py

@@ -39,6 +39,7 @@
         Timedelta,
         Timestamp,
     )
+    from pandas._libs.tslibs import BaseOffset
 
     from pandas.core.dtypes.dtypes import ExtensionDtype
 
@@ -63,7 +64,6 @@
     from pandas.core.window.rolling import BaseWindow
 
     from pandas.io.formats.format import EngFormatter
-    from pandas.tseries.offsets import DateOffset
 
     # numpy compatible types
     NumpyValueArrayLike = Union[npt._ScalarLike_co, npt.ArrayLike]
@@ -113,7 +113,7 @@
 Suffixes = Tuple[Optional[str], Optional[str]]
 Ordered = Optional[bool]
 JSONSerializable = Optional[Union[PythonScalar, List, Dict]]
-Frequency = Union[str, "DateOffset"]
+Frequency = Union[str, "BaseOffset"]
 Axes = Union[AnyArrayLike, List, range]
 
 RandomState = Union[

pandas/core/arrays/base.py

@@ -985,7 +985,7 @@ def equals(self, other: object) -> bool:
             equal_na = self.isna() & other.isna()  # type: ignore[operator]
             return bool((equal_values | equal_na).all())
 
-    def isin(self, values) -> np.ndarray:
+    def isin(self, values) -> npt.NDArray[np.bool_]:
         """
         Pointwise comparison for set containment in the given values.
 

pandas/core/arrays/interval.py

@@ -1738,7 +1738,7 @@ def contains(self, other):
             other < self._right if self.open_right else other <= self._right
         )
 
-    def isin(self, values) -> np.ndarray:
+    def isin(self, values) -> npt.NDArray[np.bool_]:
         if not hasattr(values, "dtype"):
             values = np.array(values)
         values = extract_array(values, extract_numpy=True)

pandas/core/arrays/string_arrow.py

@@ -202,7 +202,7 @@ def _maybe_convert_setitem_value(self, value):
                     raise ValueError("Scalar must be NA or str")
         return value
 
-    def isin(self, values):
+    def isin(self, values) -> npt.NDArray[np.bool_]:
         if pa_version_under2p0:
             fallback_performancewarning(version="2")
             return super().isin(values)