Moved fixes into '_groupby_and_aggregate'.

Author: discort

pandas/core/resample.py

@@ -395,7 +395,11 @@ def _groupby_and_aggregate(self, how, grouper=None, *args, **kwargs):
             grouped = PanelGroupBy(obj, grouper=grouper, axis=self.axis)
 
         try:
-            result = self._try_aggregate(grouped, how, *args, **kwargs)
+            if isinstance(obj, ABCDataFrame) and compat.callable(how):
+                # Check if the function is reducing or not.
+                result = grouped._aggregate_item_by_item(how, *args, **kwargs)
+            else:
+                result = grouped.aggregate(how, *args, **kwargs)
         except Exception:
 
             # we have a non-reducing function
@@ -405,24 +409,6 @@ def _groupby_and_aggregate(self, how, grouper=None, *args, **kwargs):
         result = self._apply_loffset(result)
         return self._wrap_result(result)
 
-    def _try_aggregate(self, grouped, how, *args, **kwargs):
-        """
-        Tries to aggregate a 'grouped' object.
-        When 'how' param is a callable, we aggregate item by item
-        to check if the function is reducing or not.
-
-        Parameters
-        ----------
-        grouped : GroupBy object
-        how : string / cython mapped function
-        """
-        if not compat.callable(how) or isinstance(grouped, PanelGroupBy):
-            return grouped.aggregate(how, *args, **kwargs)
-
-        # Callables might change the count of columns (GH #15169)
-        result = grouped._aggregate_item_by_item(how, *args, **kwargs)
-        return result
-
     def _apply_loffset(self, result):
         """
         if loffset is set, offset the result index

pandas/tests/test_resample.py

@@ -3113,11 +3113,16 @@ def f(x):
             s = pd.Series([1, 2], index=['a', 'b'])
             return s
 
-        result = df.resample('M').apply(f)
         expected = df.groupby(pd.Grouper(freq='M')).apply(f)
 
+        result = df.resample('M').apply(f)
         assert_frame_equal(result, expected)
 
+        # A case for series
+        expected = df['col1'].groupby(pd.Grouper(freq='M')).apply(f)
+        result = df['col1'].resample('M').apply(f)
+        assert_series_equal(result, expected)
+
     def test_resample_groupby_with_label(self):
         # GH 13235
         index = date_range('2000-01-01', freq='2D', periods=5)