BUG: Fix for resampler for grouping kwarg bug

closes #13235
closes #13241

Author: roycoding

doc/source/whatsnew/v0.18.2.txt

@@ -224,9 +224,11 @@ Bug Fixes
 
 
 - Bug in ``PeriodIndex`` and ``Period`` subtraction raises ``AttributeError`` (:issue:`13071`)
-- Bug in ``.resample(..)`` with a ``PeriodIndex`` not changing its ``freq`` appropriately when empty (:issue:`13067`)
 - Bug in ``PeriodIndex`` construction returning a ``float64`` index in some circumstances (:issue:`13067`)
+- Bug in ``.resample(..)`` with a ``PeriodIndex`` not changing its ``freq`` appropriately when empty (:issue:`13067`)
 - Bug in ``.resample(..)`` with a ``PeriodIndex`` not retaining its type or name with an empty ``DataFrame``appropriately when empty (:issue:`13212`)
+- Bug in ``groupby(..).resample(..)`` where passing some keywords would raise an exception (:issue:`13235`)
+- Bug in ``pd.read_csv`` in which the ``nrows`` argument was not properly validated for both engines (:issue:`10476`)
 
 
 
@@ -251,5 +253,7 @@ Bug Fixes
 
 - Bug in ``groupby`` where ``apply`` returns different result depending on whether first result is ``None`` or not (:issue:`12824`)
 
+
+
+
 - Bug in ``Categorical.remove_unused_categories()`` changes ``.codes`` dtype to platform int (:issue:`13261`)
-- Bug in ``pd.read_csv`` in which the ``nrows`` argument was not properly validated for both engines (:issue:`10476`)

pandas/tseries/resample.py

@@ -912,8 +912,7 @@ def get_resampler_for_grouping(groupby, rule, how=None, fill_method=None,
     return _maybe_process_deprecations(r,
                                        how=how,
                                        fill_method=fill_method,
-                                       limit=limit,
-                                       **kwargs)
+                                       limit=limit)
 
 
 class TimeGrouper(Grouper):

pandas/tseries/tests/test_resample.py

@@ -2670,6 +2670,26 @@ def f(x):
         result = g.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)
+        df = DataFrame(index=index,
+                       data={'col0': [0, 0, 1, 1, 2], 'col1': [1, 1, 1, 1, 1]}
+                       )
+        result = df.groupby('col0').resample('1W', label='left').sum()
+
+        mi = [np.array([0, 0, 1, 2]),
+              pd.to_datetime(np.array(['1999-12-26', '2000-01-02',
+                                       '2000-01-02', '2000-01-02'])
+                             )
+              ]
+        mindex = pd.MultiIndex.from_arrays(mi, names=['col0', None])
+        expected = DataFrame(data={'col0': [0, 0, 2, 2], 'col1': [1, 1, 2, 1]},
+                             index=mindex
+                             )
+
+        assert_frame_equal(result, expected)
+
     def test_consistency_with_window(self):
 
         # consistent return values with window