move test to test time grouper

Author: ruiann

pandas/tests/groupby/test_timegrouper.py

@@ -623,3 +623,20 @@ def test_nunique_with_timegrouper_and_nat(self):
         result = test.groupby(grouper)['data'].nunique()
         expected = test[test.time.notnull()].groupby(grouper)['data'].nunique()
         tm.assert_series_equal(result, expected)
+
+    def test_scalar_call_versus_list_call(self):
+        # Issue: 17530
+        data_frame = {
+            'location': ['shanghai', 'beijing', 'shanghai'],
+            'time': pd.Series(['2017-08-09 13:32:23', '2017-08-11 23:23:15',
+                               '2017-08-11 22:23:15'],
+                              dtype='datetime64[ns]'),
+            'value': [1, 2, 3]
+        }
+        data_frame = pd.DataFrame(data_frame).set_index('time')
+        grouper = pd.TimeGrouper('D')
+        grouped = data_frame.groupby(grouper)
+        data1 = grouped.count()
+        grouped = data_frame.groupby([grouper])
+        data2 = grouped.count()
+        assert_frame_equal(data1, data2)

pandas/tests/test_resample.py

@@ -3380,20 +3380,3 @@ def test_aggregate_with_nat(self):
 
             # if NaT is included, 'var', 'std', 'mean', 'first','last'
             # and 'nth' doesn't work yet
-
-    # Issue: 17530
-    def test_scalar_call_versus_list_call(self):
-        data_frame = {
-            'location': ['shanghai', 'beijing', 'shanghai'],
-            'time': pd.Series(['2017-08-09 13:32:23', '2017-08-11 23:23:15',
-                               '2017-08-11 22:23:15'],
-                              dtype='datetime64[ns]'),
-            'value': [1, 2, 3]
-        }
-        data_frame = pd.DataFrame(data_frame).set_index('time')
-        grouper = TimeGrouper('D')
-        grouped = data_frame.groupby(grouper)
-        data1 = grouped.count()
-        grouped = data_frame.groupby([grouper])
-        data2 = grouped.count()
-        assert_frame_equal(data1, data2)