Added applying of multiple columns to resample

Author: discort

doc/source/whatsnew/v0.21.0.txt

@@ -1023,6 +1023,7 @@ Groupby/Resample/Rolling
 - Bug in ``DataFrame.groupby`` where a single level selection from a ``MultiIndex`` unexpectedly sorts (:issue:`17537`)
 - Bug in ``DataFrame.groupby`` where spurious warning is raised when ``Grouper`` object is used to override ambiguous column name (:issue:`17383`)
 - Bug in ``TimeGrouper`` differs when passes as a list and as a scalar (:issue:`17530`)
+- Bug in ``DataFrame.resample(...).apply(...)`` when there is a callable that returns different columns (:issue:`15169`)
 
 Sparse
 ^^^^^^

pandas/core/resample.py

@@ -395,7 +395,7 @@ def _groupby_and_aggregate(self, how, grouper=None, *args, **kwargs):
             grouped = PanelGroupBy(obj, grouper=grouper, axis=self.axis)
 
         try:
-            result = grouped.aggregate(how, *args, **kwargs)
+            result = self._try_aggregate(grouped, how, *args, **kwargs)
         except Exception:
 
             # we have a non-reducing function
@@ -405,6 +405,15 @@ 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):
+        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

@@ -3103,6 +3103,21 @@ def f(x):
         result = g.apply(f)
         assert_frame_equal(result, expected)
 
+    def test_apply_with_mutated_index(self):
+        # GH 15169
+        index = pd.date_range('1-1-2015', '12-31-15', freq='D')
+        df = pd.DataFrame(data={'col1': np.random.rand(len(index))},
+                          index=index)
+
+        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)
+
+        assert_frame_equal(result, expected)
+
     def test_resample_groupby_with_label(self):
         # GH 13235
         index = date_range('2000-01-01', freq='2D', periods=5)