diff --git a/doc/source/whatsnew/v0.24.0.txt b/doc/source/whatsnew/v0.24.0.txt
index 7eb3ea303cc9d1..0e591e180e0781 100644
--- a/doc/source/whatsnew/v0.24.0.txt
+++ b/doc/source/whatsnew/v0.24.0.txt
@@ -785,6 +785,7 @@ Groupby/Resample/Rolling
 - Bug in :meth:`Series.resample` when passing ``numpy.timedelta64`` to ``loffset`` kwarg (:issue:`7687`).
 - Bug in :meth:`Resampler.asfreq` when frequency of ``TimedeltaIndex`` is a subperiod of a new frequency (:issue:`13022`).
 - Bug in :meth:`SeriesGroupBy.mean` when values were integral but could not fit inside of int64, overflowing instead. (:issue:`22487`)
+- :func:`RollingGroupby.agg` and :func:`ExpandingGroupby.agg` now support multiple aggregation functions as parameters (:issue:`15072`)
 
 Sparse
 ^^^^^^
diff --git a/pandas/core/base.py b/pandas/core/base.py
index 26fea89b45ae1f..7f14a68503973e 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -245,8 +245,8 @@ def _obj_with_exclusions(self):
 
     def __getitem__(self, key):
         if self._selection is not None:
-            raise Exception('Column(s) {selection} already selected'
-                            .format(selection=self._selection))
+            raise IndexError('Column(s) {selection} already selected'
+                             .format(selection=self._selection))
 
         if isinstance(key, (list, tuple, ABCSeries, ABCIndexClass,
                             np.ndarray)):
diff --git a/pandas/core/groupby/base.py b/pandas/core/groupby/base.py
index 96c74f7fd4d75a..ac84971de08d8c 100644
--- a/pandas/core/groupby/base.py
+++ b/pandas/core/groupby/base.py
@@ -44,8 +44,15 @@ def _gotitem(self, key, ndim, subset=None):
         # we need to make a shallow copy of ourselves
         # with the same groupby
         kwargs = {attr: getattr(self, attr) for attr in self._attributes}
+
+        # Try to select from a DataFrame, falling back to a Series
+        try:
+            groupby = self._groupby[key]
+        except IndexError:
+            groupby = self._groupby
+
         self = self.__class__(subset,
-                              groupby=self._groupby[key],
+                              groupby=groupby,
                               parent=self,
                               **kwargs)
         self._reset_cache()
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 483f814bc83835..3cdd0965ccfd0d 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -623,8 +623,14 @@ def test_as_index_series_return_frame(df):
     assert isinstance(result2, DataFrame)
     assert_frame_equal(result2, expected2)
 
-    # corner case
-    pytest.raises(Exception, grouped['C'].__getitem__, 'D')
+
+def test_as_index_series_column_slice_raises(df):
+    # GH15072
+    grouped = df.groupby('A', as_index=False)
+    msg = r"Column\(s\) C already selected"
+
+    with tm.assert_raises_regex(IndexError, msg):
+        grouped['C'].__getitem__('D')
 
 
 def test_groupby_as_index_cython(df):
diff --git a/pandas/tests/test_window.py b/pandas/tests/test_window.py
index 052bfd2b858fb2..cc663fc59cbf16 100644
--- a/pandas/tests/test_window.py
+++ b/pandas/tests/test_window.py
@@ -1,3 +1,4 @@
+from collections import OrderedDict
 from itertools import product
 import pytest
 import warnings
@@ -314,6 +315,53 @@ 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(OrderedDict((
+            ('low', ['mean', 'max']),
+            ('high', ['mean', 'min']),
+        )))
+
+        tm.assert_frame_equal(result, expected)
+
 
 @pytest.mark.filterwarnings("ignore:can't resolve package:ImportWarning")
 class TestWindow(Base):