Use skipna instead of numeric_only

Author: Arno Veenstra

pandas/core/arrays/categorical.py

@@ -2172,14 +2172,14 @@ def _reverse_indexer(self):
         return result
 
     # reduction ops #
-    def _reduce(self, name, axis=0, skipna=True, **kwargs):
+    def _reduce(self, name, axis=0, **kwargs):
         func = getattr(self, name, None)
         if func is None:
             msg = 'Categorical cannot perform the operation {op}'
             raise TypeError(msg.format(op=name))
         return func(**kwargs)
 
-    def min(self, numeric_only=None, **kwargs):
+    def min(self, skipna=None, **kwargs):
         """
         The minimum value of the object.
 
@@ -2195,7 +2195,7 @@ def min(self, numeric_only=None, **kwargs):
         min : the minimum of this `Categorical`
         """
         self.check_for_ordered('min')
-        if numeric_only:
+        if skipna:
             good = self._codes != -1
             pointer = self._codes[good].min(**kwargs)
         else:
@@ -2205,7 +2205,7 @@ def min(self, numeric_only=None, **kwargs):
         else:
             return self.categories[pointer]
 
-    def max(self, numeric_only=None, **kwargs):
+    def max(self, skipna=None, **kwargs):
         """
         The maximum value of the object.
 
@@ -2221,7 +2221,7 @@ def max(self, numeric_only=None, **kwargs):
         max : the maximum of this `Categorical`
         """
         self.check_for_ordered('max')
-        if numeric_only:
+        if skipna:
             good = self._codes != -1
             pointer = self._codes[good].max(**kwargs)
         else:

pandas/core/series.py

@@ -3676,8 +3676,7 @@ def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
 
         # dispatch to ExtensionArray interface
         if isinstance(delegate, ExtensionArray):
-            return delegate._reduce(name, skipna=skipna,
-                                    numeric_only=numeric_only, **kwds)
+            return delegate._reduce(name, skipna=skipna, **kwds)
         elif is_datetime64_dtype(delegate):
             # use DatetimeIndex implementation to handle skipna correctly
             delegate = DatetimeIndex(delegate)

pandas/tests/series/test_analytics.py

@@ -1498,10 +1498,10 @@ def test_drop_duplicates_categorical_bool(self, is_ordered):
         sc.drop_duplicates(keep=False, inplace=True)
         tm.assert_series_equal(sc, tc[~expected])
 
-    def test_min_numeric_only(self):
+    def test_min_skipna(self):
         raw_cat = pd.Categorical(["a", "b", "c", "a"],
                                  categories=["b", "c", "d"],
                                  ordered=True)
         s = pd.Series(raw_cat)
-        result = s.min(numeric_only=True)
+        result = s.min(skipna=True)
         assert result == 'b'