addressed Jeff's comments

Author: discort

doc/source/whatsnew/v0.24.0.txt

@@ -183,7 +183,7 @@ Other Enhancements
 - :class:`Series` and :class:`DataFrame` now support :class:`Iterable` in constructor (:issue:`2193`)
 - :class:`DatetimeIndex` gained :attr:`DatetimeIndex.timetz` attribute. Returns local time with timezone information. (:issue:`21358`)
 - :class:`Resampler` now is iterable like :class:`GroupBy` (:issue:`15314`).
-- Added :meth:`Resampler.quantile` (:issue:`15023`).
+- :ref:`Series.resample` and :ref:`DataFrame.resample` have gained the :meth:`Resampler.quantile` (:issue:`15023`).
 
 .. _whatsnew_0240.api_breaking:
 

pandas/core/groupby/groupby.py

@@ -1168,7 +1168,12 @@ def var(self, ddof=1, *args, **kwargs):
         """
         nv.validate_groupby_func('var', args, kwargs)
         if ddof == 1:
-            return self._cython_agg_general('var', **kwargs)
+            try:
+                return self._cython_agg_general('var', **kwargs)
+            except Exception:
+                f = lambda x: x.var(ddof=ddof, **kwargs)
+                with _group_selection_context(self):
+                    return self._python_agg_general(f)
         else:
             f = lambda x: x.var(ddof=ddof, **kwargs)
             with _group_selection_context(self):

pandas/core/resample.py

@@ -770,11 +770,17 @@ def quantile(self, q=0.5, **kwargs):
         """
         Return value at the given quantile.
 
+        .. versionadded:: 0.24.0
+
         Parameters
         ----------
         q : float or array-like, default 0.5 (50% quantile)
 
-        .. versionadded:: 0.24.0
+        See Also
+        --------
+        Series.quantile
+        DataFrame.quantile
+        DataFrameGroupBy.quantile
         """
         return self._downsample('quantile', q=q, **kwargs)
 
@@ -1072,7 +1078,8 @@ def _downsample(self, how, **kwargs):
 
         if is_subperiod(ax.freq, self.freq):
             # Downsampling
-            return self._groupby_and_aggregate(how, grouper=self.grouper)
+            return self._groupby_and_aggregate(how, grouper=self.grouper,
+                                               **kwargs)
         elif is_superperiod(ax.freq, self.freq):
             if how == 'ohlc':
                 # GH #13083

pandas/tests/test_resample.py

@@ -782,6 +782,15 @@ def test_resampler_is_iterable(self):
             assert rk == gk
             assert_series_equal(rv, gv)
 
+    def test_resample_quantile(self):
+        # GH 15023
+        s = self.create_series()
+        q = 0.75
+        freq = 'H'
+        result = s.resample(freq).quantile(q)
+        expected = s.resample(freq).agg(lambda x: x.quantile(q))
+        tm.assert_series_equal(result, expected)
+
 
 class TestDatetimeIndex(Base):
     _index_factory = lambda x: date_range
@@ -2176,13 +2185,6 @@ def test_resample_datetime_values(self):
         res = df['timestamp'].resample('2D').first()
         tm.assert_series_equal(res, exp)
 
-    def test_resample_quantile(self):
-        # GH 15023
-        s = pd.Series(range(20), index=date_range('2016-01-01', periods=20))
-        result = s.resample('W').quantile(0.75)
-        expected = s.resample('W').agg(lambda x: x.quantile(0.75))
-        tm.assert_series_equal(result, expected)
-
 
 class TestPeriodIndex(Base):
     _index_factory = lambda x: period_range