BUG: Fix inconsistent GroupBy.aggregate behavior with as_index=False when grouping by external Series with conflicting names #58337

pandas/core/groupby/generic.py

@@ -1577,6 +1577,28 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
         if not self.as_index:
             result = self._insert_inaxis_grouper(result)
             result.index = default_index(len(result))
+            group_keys = []
+
+            if isinstance(self.keys, Series):  # Ensure consistent namespace usage
+                group_keys.append(self.keys.name)
+                if self.keys.name not in result.columns:
+                    result.insert(0, self.keys.name, self.keys)
+            else:
+                group_keys.extend(key for key in self.keys if key in self.obj.columns)
+
+            if not result.index.equals(default_index(len(result))):
+                result.reset_index(drop=False, inplace=True)
+
+            if group_keys:
+                for key in group_keys:
+                    if key not in result.columns:
+                        result.insert(0, key, self.obj[key])
+
+        if not self.as_index and isinstance(
+            self.keys, Series
+        ):  # Ensure consistent namespace usage
+            # Remove any duplicate entries for series key
+            result = result.loc[:, ~result.columns.duplicated()]
 
         return result
 

pandas/tests/groupby/test_groupby_aggregate_as_index.py

@@ -0,0 +1,31 @@
+import pytest
+
+import pandas as pd
+import pandas.testing as pdt
+
+
+@pytest.fixture
+def sample_df():
+    return pd.DataFrame(
+        {
+            "A": ["foo", "bar", "foo", "bar", "foo", "bar", "foo", "foo"],
+            "B": ["one", "one", "two", "three", "two", "two", "one", "three"],
+            "C": [1, 2, 3, 4, 5, 6, 7, 8],
+            "D": [2.0, 5.0, 8.0, 1.0, 2.0, 9.0, 7.0, 8.0],
+        }
+    )
+
+
+def test_groupby_aggregate_as_index_false_with_column_key(sample_df):
+    grouped = sample_df.groupby("A", as_index=False)
+    result = grouped.aggregate({"C": "sum"})
+    expected = pd.DataFrame({"A": ["bar", "foo"], "C": [12, 24]})
+    pdt.assert_frame_equal(result, expected)
+
+
+def test_groupby_aggregate_as_index_false_with_no_grouping_keys(sample_df):
+    grouped = sample_df.groupby("A", as_index=False)
+    result = grouped.aggregate({"D": "sum"})
+    expected = pd.DataFrame({"A": ["bar", "foo"], "D": [15.0, 27.0]})
+    pdt.assert_frame_equal(result, expected)
+    assert result.index.equals(pd.RangeIndex(start=0, stop=len(result), step=1))