Added test coverage for observed=False with ops

pandas/tests/groupby/conftest.py

@@ -76,3 +76,10 @@ def three_group():
  'D': np.random.randn(11),
  'E': np.random.randn(11),
  'F': np.random.randn(11)})
+
+
+AGG_FUNCS = ['sum', 'prod', 'min', 'max', 'mean', 'median', 'var', 'first',
+ 'last', 'nth'] # TODO: ohlc?
+@pytest.fixture(params=AGG_FUNCS)
+def agg_func(request):
+ return request.param

pandas/tests/groupby/test_categorical.py

@@ -433,6 +433,35 @@ def test_observed_groups_with_nan(observed):
  tm.assert_dict_equal(result, expected)
 
 
+def test_observed_ops(agg_func):
+ cat = pd.Categorical(['a', np.nan, np.nan], categories=['a', 'b', 'c'])
+ ser = pd.Series([1., 2., 3.])
+ df = pd.DataFrame({'cat': cat, 'ser': ser})
+
+ grp = df.groupby('cat', observed=False)['ser']
+ func = getattr(grp, agg_func)
+
+ if agg_func == 'nth': # Need an argument
+ result = func(0)
+ else:
+ result = func()
+
+ if agg_func == 'sum': # TODO: maybe a bug?
+ expected_vals = [1., 0., 0.]
+ elif agg_func == 'prod': # TODO: Definitely seems like a bug
+ expected_vals = [1., 1., 1.]
+ elif agg_func == 'var':
+ expected_vals = [np.nan, np.nan, np.nan]
+ else:
+ expected_vals = [1., np.nan, np.nan]
+
+ index = pd.Categorical(['a', 'b', 'c'], categories=['a', 'b', 'c'])
+ expected = pd.Series(expected_vals, index=index, name='ser')
+ expected.index.name = 'cat'
+
+ tm.assert_series_equal(result, expected)
+
+
 def test_dataframe_categorical_with_nan(observed):
  # GH 21151
  s1 = pd.Categorical([np.nan, 'a', np.nan, 'a'],