BUG: groupby.agg doesn't include grouping columns in result when selected

doc/source/whatsnew/v2.0.0.rst

@@ -1362,7 +1362,7 @@ Groupby/resample/rolling
 - Bug in :meth:`.DataFrameGroupBy.describe` produced incorrect results when data had duplicate columns (:issue:`50806`)
 - Bug in :meth:`.DataFrameGroupBy.agg` with ``engine="numba"`` failing to respect ``as_index=False`` (:issue:`51228`)
 - Bug in :meth:`DataFrameGroupBy.agg`, :meth:`SeriesGroupBy.agg`, and :meth:`Resampler.agg` would ignore arguments when passed a list of functions (:issue:`50863`)
--
+- Bug in :meth:`DataFrameGroupBy.agg` with multiple groupings would not include groupings in the result when they occurred in the selected columns (:issue:`51186`)
 
 Reshaping
 ^^^^^^^^^

pandas/core/groupby/generic.py

@@ -1320,21 +1320,15 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
     agg = aggregate
 
     def _iterate_slices(self) -> Iterable[Series]:
-        obj = self._selected_obj
+        obj = self._obj_with_exclusions
         if self.axis == 1:
             obj = obj.T
 
-        if isinstance(obj, Series) and obj.name not in self.exclusions:
+        if isinstance(obj, Series):
             # Occurs when doing DataFrameGroupBy(...)["X"]
             yield obj
         else:
             for label, values in obj.items():
-                if label in self.exclusions:
-                    # Note: if we tried to just iterate over _obj_with_exclusions,
-                    #  we would break test_wrap_agg_out by yielding a column
-                    #  that is skipped here but not dropped from obj_with_exclusions
-                    continue
-
                 yield values
 
     def _aggregate_frame(self, func, *args, **kwargs) -> DataFrame:

pandas/tests/groupby/aggregate/test_aggregate.py

@@ -321,8 +321,9 @@ def func(ser):
 
     with pytest.raises(TypeError, match="Test error message"):
         grouped.aggregate(func)
-    result = grouped[[c for c in three_group if c != "C"]].aggregate(func)
-    exp_grouped = three_group.loc[:, three_group.columns != "C"]
+    columns = ["D", "E", "F"]
+    result = grouped[columns].aggregate(func)
+    exp_grouped = three_group.loc[:, columns]
     expected = exp_grouped.groupby(["A", "B"]).aggregate(func)
     tm.assert_frame_equal(result, expected)
 
@@ -1515,3 +1516,16 @@ def foo2(x, b=2, c=0):
         [[8, 8], [9, 9], [10, 10]], index=Index([1, 2, 3]), columns=["foo1", "foo2"]
     )
     tm.assert_frame_equal(result, expected)
+
+
+def test_agg_groupings_selection():
+    # GH#51186 - a selected grouping should be in the output of agg
+    df = DataFrame({"a": [1, 1, 2], "b": [3, 3, 4], "c": [5, 6, 7]})
+    gb = df.groupby(["a", "b"])
+    selected_gb = gb[["b", "c"]]
+    result = selected_gb.agg(lambda x: x.sum())
+    index = MultiIndex(
+        levels=[[1, 2], [3, 4]], codes=[[0, 1], [0, 1]], names=["a", "b"]
+    )
+    expected = DataFrame({"b": [6, 4], "c": [11, 7]}, index=index)
+    tm.assert_frame_equal(result, expected)