Fixes groupby.apply() error when no returns pandas-dev#9684

Author: Nick Eubank

doc/source/whatsnew/v0.16.1.txt

@@ -99,11 +99,10 @@ Bug Fixes
 
 
 - Bug in ``transform`` causing length mismatch when null entries were present and a fast aggregator was being used (:issue:`9697`)
-
 - Bug in ``equals`` causing false negatives when block order differed (:issue:`9330`)
-
 - Bug in ``DataFrame`` slicing may not retain metadata (:issue:`9776`)
 - Bug where ``TimdeltaIndex`` were not properly serialized in fixed ``HDFStore`` (:issue:`9635`)
+- Fixed bug in ``groupby.apply()`` that would raise an error the user passed function either returned nothing or only returned values of ``None``. (:issue:`9685`)
 
 - Bug in plotting continuously using ``secondary_y`` may not show legend properly. (:issue:`9610`, :issue:`9779`)
 

pandas/core/groupby.py

@@ -2808,7 +2808,12 @@ def _wrap_applied_output(self, keys, values, not_indexed_same=False):
 
             # make Nones an empty object
             if com._count_not_none(*values) != len(values):
-                v = next(v for v in values if v is not None)
+                try:
+                    v = next(v for v in values if v is not None)
+                except StopIteration:
+                    # If all values are None, then this will throw an error.
+                    # We'd prefer it return an empty dataframe. 
+                    return DataFrame()
                 if v is None:
                     return DataFrame()
                 elif isinstance(v, NDFrame):

pandas/tests/test_groupby.py

@@ -5053,6 +5053,17 @@ def test_groupby_categorical_two_columns(self):
                          "C3":[nan,nan,nan,nan, 10,100,nan,nan, nan,nan,200,34]}, index=idx)
         tm.assert_frame_equal(res, exp)
 
+    def test_groupby_apply_all_none(self):
+        # Tests to make sure no errors if apply function returns all None 
+        # values. Issue 9684.
+        test_df = DataFrame({'groups': [0,0,1,1], 'random_vars': [8,7,4,5]})
+        
+        def test_func(x):
+            pass
+        result = test_df.groupby('groups').apply(test_func)
+        expected = DataFrame()
+        tm.assert_frame_equal(result, expected)
+
 
 def assert_fp_equal(a, b):
     assert (np.abs(a - b) < 1e-12).all()