CLN: consistent EA._reduce signatures (#35308)

Author: simonjayhawkins

pandas/core/arrays/base.py

@@ -1120,7 +1120,7 @@ def _concat_same_type(
     # of objects
     _can_hold_na = True
 
-    def _reduce(self, name, skipna=True, **kwargs):
+    def _reduce(self, name: str, skipna: bool = True, **kwargs):
         """
         Return a scalar result of performing the reduction operation.
 

pandas/core/arrays/categorical.py

@@ -2076,11 +2076,11 @@ def _reverse_indexer(self) -> Dict[Hashable, np.ndarray]:
         return result
 
     # reduction ops #
-    def _reduce(self, name, axis=0, **kwargs):
+    def _reduce(self, name: str, skipna: bool = True, **kwargs):
         func = getattr(self, name, None)
         if func is None:
             raise TypeError(f"Categorical cannot perform the operation {name}")
-        return func(**kwargs)
+        return func(skipna=skipna, **kwargs)
 
     @deprecate_kwarg(old_arg_name="numeric_only", new_arg_name="skipna")
     def min(self, skipna=True, **kwargs):

pandas/core/arrays/datetimelike.py

@@ -1552,7 +1552,7 @@ def __isub__(self, other):
     # --------------------------------------------------------------
     # Reductions
 
-    def _reduce(self, name, axis=0, skipna=True, **kwargs):
+    def _reduce(self, name: str, skipna: bool = True, **kwargs):
         op = getattr(self, name, None)
         if op:
             return op(skipna=skipna, **kwargs)

pandas/core/arrays/sparse/array.py

@@ -1164,7 +1164,7 @@ def nonzero(self):
     # Reductions
     # ------------------------------------------------------------------------
 
-    def _reduce(self, name, skipna=True, **kwargs):
+    def _reduce(self, name: str, skipna: bool = True, **kwargs):
         method = getattr(self, name, None)
 
         if method is None:

pandas/core/arrays/string_.py

@@ -291,7 +291,7 @@ def astype(self, dtype, copy=True):
 
         return super().astype(dtype, copy)
 
-    def _reduce(self, name, skipna=True, **kwargs):
+    def _reduce(self, name: str, skipna: bool = True, **kwargs):
         if name in ["min", "max"]:
             return getattr(self, name)(skipna=skipna)
 

pandas/tests/extension/arrow/arrays.py

@@ -162,14 +162,14 @@ def _concat_same_type(cls, to_concat):
     def __invert__(self):
         return type(self).from_scalars(~self._data.to_pandas())
 
-    def _reduce(self, method, skipna=True, **kwargs):
+    def _reduce(self, name: str, skipna: bool = True, **kwargs):
         if skipna:
             arr = self[~self.isna()]
         else:
             arr = self
 
         try:
-            op = getattr(arr, method)
+            op = getattr(arr, name)
         except AttributeError as err:
             raise TypeError from err
         return op(**kwargs)

pandas/tests/extension/decimal/array.py

@@ -174,7 +174,7 @@ def _formatter(self, boxed=False):
     def _concat_same_type(cls, to_concat):
         return cls(np.concatenate([x._data for x in to_concat]))
 
-    def _reduce(self, name, skipna=True, **kwargs):
+    def _reduce(self, name: str, skipna: bool = True, **kwargs):
 
         if skipna:
             # If we don't have any NAs, we can ignore skipna