Deprecate numeric_only

pandas/core/arrays/categorical.py

@@ -2179,7 +2179,8 @@ def _reduce(self, name, axis=0, **kwargs):
             raise TypeError(msg.format(op=name))
         return func(**kwargs)
 
-    def min(self, skipna=True, **kwargs):
+    @deprecate_kwarg(old_arg_name='numeric_only', new_arg_name='skipna')
+    def min(self, skipna=True, numeric_only=None, **kwargs):
         """
         The minimum value of the object.
 
@@ -2205,7 +2206,8 @@ def min(self, skipna=True, **kwargs):
         else:
             return self.categories[pointer]
 
-    def max(self, skipna=True, **kwargs):
+    @deprecate_kwarg(old_arg_name='numeric_only', new_arg_name='skipna')
+    def max(self, skipna=True, numeric_only=None, **kwargs):
         """
         The maximum value of the object.
 

pandas/core/series.py

@@ -3674,8 +3674,17 @@ def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
         if axis is not None:
             self._get_axis_number(axis)
 
-        # dispatch to ExtensionArray interface
-        if isinstance(delegate, ExtensionArray):
+        if isinstance(delegate, Categorical):
+            # TODO: remove numeric_only argument and treat Categorical the same
+            # as all ExtensionArrays
+            # See https://github.com/pandas-dev/pandas/issues/25303
+            if numeric_only is not None:
+                return delegate._reduce(name, numeric_only=numeric_only,
+                                        **kwds)
+            else:
+                return delegate._reduce(name, skipna=skipna, **kwds)
+        elif isinstance(delegate, ExtensionArray):
+            # dispatch to ExtensionArray interface
             return delegate._reduce(name, skipna=skipna, **kwds)
         elif is_datetime64_dtype(delegate):
             # use DatetimeIndex implementation to handle skipna correctly

pandas/tests/reductions/test_reductions.py

@@ -967,6 +967,12 @@ def test_min_max(self):
         assert _min == "b"
         assert _max == "c"
 
+        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+            _min = cat.min(numeric_only=False)
+            _max = cat.max(numeric_only=False)
+        assert np.isnan(_min)
+        assert _max == "c"
+
 
 class TestSeriesMode(object):
     # Note: the name TestSeriesMode indicates these tests