REF: Pre-empt ValueError in _aggregate_series_fast

pandas/_libs/reduction.pyx

@@ -325,6 +325,10 @@ cdef class SeriesGrouper:
         #  safer obj._get_values(slice(None, 0))
         assert dummy is not None
 
+        if len(series) == 0:
+            # get_result would never assign `result`
+            raise ValueError("SeriesGrouper requires non-empty `series`")
+
         self.labels = labels
         self.f = f
 
@@ -428,7 +432,9 @@ cdef class SeriesGrouper:
             vslider.reset()
 
         if result is None:
-            raise ValueError("No result.")
+            # This should no longer be reachable since we check for empty
+            #  series in the constructor.
+            raise AssertionError("`result` has not been assigned.")
 
         if result.dtype == np.object_:
             result = maybe_convert_objects(result)

pandas/core/groupby/ops.py

@@ -583,7 +583,12 @@ def _transform(
         return result
 
     def agg_series(self, obj: Series, func):
-        if is_extension_array_dtype(obj.dtype) and obj.dtype.kind != "M":
+        if len(obj) == 0:
+            # SeriesGrouper would raise if we were to call _aggregate_series_fast
+            # 2019-11-09: 3 tests get here with len(obj) == 0
+            return self._aggregate_series_pure_python(obj, func)
+
+        elif is_extension_array_dtype(obj.dtype) and obj.dtype.kind != "M":
             # _aggregate_series_fast would raise TypeError when
             #  calling libreduction.Slider
             # TODO: can we get a performant workaround for EAs backed by ndarray?
@@ -597,19 +602,18 @@ def agg_series(self, obj: Series, func):
         try:
             return self._aggregate_series_fast(obj, func)
         except ValueError as err:
-            if "No result." in str(err):
-                # raised in libreduction
-                pass
-            elif "Function does not reduce" in str(err):
+            if "Function does not reduce" in str(err):
                 # raised in libreduction
                 pass
             else:
                 raise
         return self._aggregate_series_pure_python(obj, func)
 
     def _aggregate_series_fast(self, obj, func):
-        # At this point we have already checked that obj.index is not a MultiIndex
-        #  and that obj is backed by an ndarray, not ExtensionArray
+        # At this point we have already checked that
+        #  - obj.index is not a MultiIndex
+        #  - obj is backed by an ndarray, not ExtensionArray
+        #  - len(obj) > 0
         func = self._is_builtin_func(func)
 
         group_index, _, ngroups = self.group_info
@@ -797,6 +801,7 @@ def groupings(self):
         ]
 
     def agg_series(self, obj: Series, func):
+        # 2019-11-09: 3 tests get here with len(obj) == 0
         if is_extension_array_dtype(obj.dtype):
             # pre-empty SeriesBinGrouper from raising TypeError
             # TODO: watch out, this can return None

pandas/tests/groupby/test_bin_groupby.py

@@ -25,6 +25,15 @@ def test_series_grouper():
     tm.assert_almost_equal(counts, exp_counts)
 
 
+def test_series_grouper_requires_nonempty():
+    obj = Series(np.random.randn(10))
+    dummy = obj[:0]
+    labels = np.array([-1, -1, -1, 0, 0, 0, 1, 1, 1, 1], dtype=np.int64)
+
+    with pytest.raises(ValueError, match="requires non-empty"):
+        libreduction.SeriesGrouper(dummy, np.mean, labels, 2, dummy)
+
+
 def test_series_bin_grouper():
     obj = Series(np.random.randn(10))
     dummy = obj[:0]