Fixed Issue Preventing Agg on RollingGroupBy Objects

doc/source/whatsnew/v0.24.0.txt

@@ -161,7 +161,7 @@ Plotting
 Groupby/Resample/Rolling
 ^^^^^^^^^^^^^^^^^^^^^^^^
 
--
+- :func:`RollingGroupby.agg` and :func:`ExpandingGroupby.agg` now support multiple aggregation functions as parameters (:issue:`15072`)
 -
 -
 

pandas/core/base.py

@@ -684,8 +684,14 @@ def _gotitem(self, key, ndim, subset=None):
         # with the same groupby
         kwargs = dict([(attr, getattr(self, attr))
                        for attr in self._attributes])
+
+        try:
+            groupby = self._groupby[key]  # get slice of frame
+        except Exception:
+            groupby = self._groupby  # working with a Series
+
         self = self.__class__(subset,
-                              groupby=self._groupby[key],
+                              groupby=groupby,
                               parent=self,
                               **kwargs)
         self._reset_cache()

pandas/tests/test_window.py

@@ -308,6 +308,53 @@ def test_preserve_metadata(self):
         assert s2.name == 'foo'
         assert s3.name == 'foo'
 
+    @pytest.mark.parametrize("func,window_size,expected_vals", [
+        ('rolling', 2, [[np.nan, np.nan, np.nan, np.nan],
+                        [15., 20., 25., 20.],
+                        [25., 30., 35., 30.],
+                        [np.nan, np.nan, np.nan, np.nan],
+                        [20., 30., 35., 30.],
+                        [35., 40., 60., 40.],
+                        [60., 80., 85., 80]]),
+        ('expanding', None, [[10., 10., 20., 20.],
+                             [15., 20., 25., 20.],
+                             [20., 30., 30., 20.],
+                             [10., 10., 30., 30.],
+                             [20., 30., 35., 30.],
+                             [26.666667, 40., 50., 30.],
+                             [40., 80., 60., 30.]])])
+    def test_multiple_agg_funcs(self, func, window_size, expected_vals):
+        # GH 15072
+        df = pd.DataFrame([
+            ['A', 10, 20],
+            ['A', 20, 30],
+            ['A', 30, 40],
+            ['B', 10, 30],
+            ['B', 30, 40],
+            ['B', 40, 80],
+            ['B', 80, 90]], columns=['stock', 'low', 'high'])
+
+        f = getattr(df.groupby('stock'), func)
+        if window_size:
+            window = f(window_size)
+        else:
+            window = f()
+
+        index = pd.MultiIndex.from_tuples([
+            ('A', 0), ('A', 1), ('A', 2),
+            ('B', 3), ('B', 4), ('B', 5), ('B', 6)], names=['stock', None])
+        columns = pd.MultiIndex.from_tuples([
+            ('low', 'mean'), ('low', 'max'), ('high', 'mean'),
+            ('high', 'min')])
+        expected = pd.DataFrame(expected_vals, index=index, columns=columns)
+
+        result = window.agg({
+            'low': ['mean', 'max'],
+            'high': ['mean', 'min']
+        })
+
+        tm.assert_frame_equal(result, expected)
+
 
 class TestWindow(Base):