diff --git a/doc/source/whatsnew/v1.1.0.rst b/doc/source/whatsnew/v1.1.0.rst
index b9ef1aae9a801..52b19fd4ebf2e 100644
--- a/doc/source/whatsnew/v1.1.0.rst
+++ b/doc/source/whatsnew/v1.1.0.rst
@@ -1117,6 +1117,7 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrame.ewm.cov` was throwing ``AssertionError`` for :class:`MultiIndex` inputs (:issue:`34440`)
 - Bug in :meth:`core.groupby.DataFrameGroupBy.quantile` raises ``TypeError`` for non-numeric types rather than dropping columns (:issue:`27892`)
 - Bug in :meth:`core.groupby.DataFrameGroupBy.transform` when ``func='nunique'`` and columns are of type ``datetime64``, the result would also be of type ``datetime64`` instead of ``int64`` (:issue:`35109`)
+- Bug in :meth:`DataFrame.groupby` raising an ``AttributeError`` when selecting a column and aggregating with ``as_index=False`` (:issue:`35246`).
 - Bug in :meth:'DataFrameGroupBy.first' and :meth:'DataFrameGroupBy.last' that would raise an unnecessary ``ValueError`` when grouping on multiple ``Categoricals`` (:issue:`34951`)
 
 Reshaping
diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 1d14361757e4a..ec7b14f27c5a1 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -963,18 +963,23 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
                 # try to treat as if we are passing a list
                 try:
                     result = self._aggregate_multiple_funcs([func], _axis=self.axis)
-                except ValueError as err:
-                    if "no results" not in str(err):
-                        # raised directly by _aggregate_multiple_funcs
-                        raise
-                    result = self._aggregate_frame(func)
-                else:
+
                     # select everything except for the last level, which is the one
                     # containing the name of the function(s), see GH 32040
                     result.columns = result.columns.rename(
                         [self._selected_obj.columns.name] * result.columns.nlevels
                     ).droplevel(-1)
 
+                except ValueError as err:
+                    if "no results" not in str(err):
+                        # raised directly by _aggregate_multiple_funcs
+                        raise
+                    result = self._aggregate_frame(func)
+                except AttributeError:
+                    # catch exception from line 969
+                    # (Series does not have attribute "columns"), see GH 35246
+                    result = self._aggregate_frame(func)
+
         if relabeling:
 
             # used reordered index of columns
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 0d040b8e6955a..ebce5b0ef0a66 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -605,6 +605,14 @@ def test_as_index_select_column():
     tm.assert_series_equal(result, expected)
 
 
+def test_groupby_as_index_select_column_sum_empty_df():
+    # GH 35246
+    df = DataFrame(columns=["A", "B", "C"])
+    left = df.groupby(by="A", as_index=False)["B"].sum()
+    assert type(left) is DataFrame
+    assert left.to_dict() == {"A": {}, "B": {}}
+
+
 def test_groupby_as_index_agg(df):
     grouped = df.groupby("A", as_index=False)