Added tests to mix group entries; fixed sort bug

Author: WillAyd

pandas/_libs/groupby_helper.pxi.in

@@ -662,7 +662,7 @@ def group_fillna_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,
 
     sorted_labels = np.argsort(labels)
     if method == 'bfill':
-        sorted_labels[::-1].sort()
+        sorted_labels = sorted_labels[::-1]
 
     {{if name == 'object'}}
     if True:  # make templating happy

pandas/tests/groupby/test_groupby.py

@@ -2061,30 +2061,59 @@ def test_rank_object_raises(self, ties_method, ascending, na_option,
                                    ascending=ascending,
                                    na_option=na_option, pct=pct)
 
+    @pytest.mark.parametrize("mix_groupings", [True, False])
     @pytest.mark.parametrize("as_series", [True, False])
+    @pytest.mark.parametrize("val1,val2", [
+        ('foo', 'bar'), (1, 2), (1., 2.)])
     @pytest.mark.parametrize("fill_method,limit,exp_vals", [
         ("ffill", None,
-         [np.nan, np.nan, 'foo', 'foo', 'foo', 'bar', 'bar', 'bar']),
+         [np.nan, np.nan, 'val1', 'val1', 'val1', 'val2', 'val2', 'val2']),
         ("ffill", 1,
-         [np.nan, np.nan, 'foo', 'foo', np.nan, 'bar', 'bar', np.nan]),
+         [np.nan, np.nan, 'val1', 'val1', np.nan, 'val2', 'val2', np.nan]),
         ("bfill", None,
-         ['foo', 'foo', 'foo', 'bar', 'bar', 'bar', np.nan, np.nan]),
+         ['val1', 'val1', 'val1', 'val2', 'val2', 'val2', np.nan, np.nan]),
         ("bfill", 1,
-         [np.nan, 'foo', 'foo', np.nan, 'bar', 'bar', np.nan, np.nan])
+         [np.nan, 'val1', 'val1', np.nan, 'val2', 'val2', np.nan, np.nan])
     ])
-    def test_group_fill_methods(self, as_series, fill_method, limit, exp_vals):
-        vals = [np.nan, np.nan, 'foo', np.nan, np.nan, 'bar', np.nan, np.nan]
-        keys = ['a'] * len(vals) + ['b'] * len(vals)
-        df = DataFrame({'key': keys, 'val': vals * 2})
-
+    def test_group_fill_methods(self, mix_groupings, as_series, val1, val2,
+                                fill_method, limit, exp_vals):
+        vals = [np.nan, np.nan, val1, np.nan, np.nan, val2, np.nan, np.nan]
+        _exp_vals = list(exp_vals)
+        # Overwrite placeholder values
+        for index, exp_val in enumerate(_exp_vals):
+            if exp_val == 'val1':
+                _exp_vals[index] = val1
+            elif exp_val == 'val2':
+                _exp_vals[index] = val2
+
+        # Need to modify values and expectations depending on the
+        # Series / DataFrame that we ultimately want to generate
+        if mix_groupings:  # ['a', 'b', 'a, 'b', ...]
+            keys = ['a', 'b'] * len(vals)
+
+            def interweave(list_obj):
+                temp = list()
+                for x in list_obj:
+                    temp.extend([x, x])
+
+                return temp
+
+            _exp_vals = interweave(_exp_vals)
+            vals = interweave(vals)
+        else:  # ['a', 'a', 'a', ... 'b', 'b', 'b']
+            keys = ['a'] * len(vals) + ['b'] * len(vals)
+            _exp_vals = _exp_vals * 2
+            vals = vals * 2
+
+        df = DataFrame({'key': keys, 'val': vals})
         if as_series:
             result = getattr(
                 df.groupby('key')['val'], fill_method)(limit=limit)
-            exp = Series(exp_vals * 2, name='val')
+            exp = Series(_exp_vals, name='val')
             assert_series_equal(result, exp)
         else:
             result = getattr(df.groupby('key'), fill_method)(limit=limit)
-            exp = DataFrame({'key': keys, 'val': exp_vals * 2})
+            exp = DataFrame({'key': keys, 'val': _exp_vals})
             assert_frame_equal(result, exp)
 
     def test_dont_clobber_name_column(self):