CLN: pandas.core.algorithms.value_counts is internal (#1525)

value_counts is internal

Author: cmp0xff

pandas-stubs/__init__.pyi

@@ -63,7 +63,6 @@ from pandas.core.api import (
     to_numeric as to_numeric,
     to_timedelta as to_timedelta,
     unique as unique,
-    value_counts as value_counts,
 )
 from pandas.core.arrays.sparse import SparseDtype as SparseDtype
 from pandas.core.computation.api import eval as eval

pandas-stubs/_libs/tslibs/timestamps.pyi

@@ -100,7 +100,7 @@ class Timestamp(datetime, SupportsIndex):
     def fold(self) -> int: ...
     if sys.version_info >= (3, 12):
         @classmethod
-        def fromtimestamp(  # pyright: ignore[reportIncompatibleMethodOverride]
+        def fromtimestamp(  # pyright: ignore[reportIncompatibleMethodOverride] # ty: ignore[invalid-method-override]
             cls, t: float, tz: _tzinfo | str | None = ...
         ) -> Self: ...
     else:

pandas-stubs/core/algorithms.pyi

@@ -19,7 +19,6 @@ from pandas.core.series import Series
 
 from pandas._typing import (
     T_EXTENSION_ARRAY,
-    AnyArrayLike,
     GenericT,
     IntervalT,
     TakeIndexer,
@@ -88,14 +87,6 @@ def factorize(
     use_na_sentinel: bool = ...,
     size_hint: int | None = ...,
 ) -> tuple[np_1darray_int64, Categorical]: ...
-def value_counts(
-    values: AnyArrayLike | list | tuple,
-    sort: bool = True,
-    ascending: bool = False,
-    normalize: bool = False,
-    bins: int | None = None,
-    dropna: bool = True,
-) -> Series: ...
 def take(
     arr: np_ndarray[Any] | ExtensionArray | Index | Series,
     indices: TakeIndexer,

pandas-stubs/core/api.pyi

@@ -1,7 +1,6 @@
 from pandas.core.algorithms import (
     factorize as factorize,
     unique as unique,
-    value_counts as value_counts,
 )
 from pandas.core.arrays import Categorical as Categorical
 from pandas.core.arrays.arrow.dtype import ArrowDtype as ArrowDtype

tests/extension/decimal/array.py

@@ -342,7 +342,9 @@ def convert_values(param: Any) -> ExtensionArray | list[Any]:
         return cast(np_1darray_bool, np.asarray(res, dtype=bool))
 
     def value_counts(self, dropna: bool = True) -> Series:
-        from pandas.core.algorithms import value_counts
+        from pandas.core.algorithms import (  # type: ignore[attr-defined] # isort: skip
+            value_counts,  # pyright: ignore[reportAttributeAccessIssue]
+        )
 
         return value_counts(self.to_numpy(), dropna=dropna)