diff --git a/pandas/core/apply.py b/pandas/core/apply.py
index 1aa08356982d2..693b1832ed3c9 100644
--- a/pandas/core/apply.py
+++ b/pandas/core/apply.py
@@ -360,7 +360,10 @@ def agg_list_like(self) -> FrameOrSeriesUnion:
                         # raised directly in _aggregate_named
                         pass
                     elif "no results" in str(err):
-                        # raised directly in _aggregate_multiple_funcs
+                        # reached in test_frame_apply.test_nuiscance_columns
+                        #  where the colg.aggregate(arg) ends up going through
+                        #  the selected_obj.ndim == 1 branch above with arg == ["sum"]
+                        #  on a datetime64[ns] column
                         pass
                     else:
                         raise
diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index fd4b0cfa87950..27e07deb69e9c 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1110,6 +1110,7 @@ def _cython_agg_general(
         # Note: we never get here with how="ohlc"; that goes through SeriesGroupBy
 
         data: Manager2D = self._get_data_to_aggregate()
+        orig = data
 
         if numeric_only:
             data = data.get_numeric_data(copy=False)
@@ -1187,7 +1188,8 @@ def array_func(values: ArrayLike) -> ArrayLike:
         #  continue and exclude the block
         new_mgr = data.grouped_reduce(array_func, ignore_failures=True)
 
-        if not len(new_mgr):
+        if not len(new_mgr) and len(orig):
+            # If the original Manager was already empty, no need to raise
             raise DataError("No numeric types to aggregate")
 
         return self._wrap_agged_manager(new_mgr)