BUG: groupby with column selection not returning tuple when grouping by list of a single element (pandas-dev#53517)

Author: Charlie-XIAO

doc/source/whatsnew/v2.1.0.rst

@@ -439,6 +439,7 @@ Groupby/resample/rolling
   grouped :class:`Series` or :class:`DataFrame` was a :class:`DatetimeIndex`, :class:`TimedeltaIndex`
   or :class:`PeriodIndex`, and the ``groupby`` method was given a function as its first argument,
   the function operated on the whole index rather than each element of the index. (:issue:`51979`)
+- Bug in :meth:`DataFrame.groupby` with column selection on the resulting groupby object not returning names as tuples when grouping by a list of a single element. (:issue:`53500`)
 - Bug in :meth:`DataFrameGroupBy.agg` with lists not respecting ``as_index=False`` (:issue:`52849`)
 - Bug in :meth:`DataFrameGroupBy.apply` causing an error to be raised when the input :class:`DataFrame` was subset as a :class:`DataFrame` after groupby (``[['a']]`` and not ``['a']``) and the given callable returned :class:`Series` that were not all indexed the same. (:issue:`52444`)
 - Bug in :meth:`DataFrameGroupBy.apply` raising a ``TypeError`` when selecting multiple columns and providing a function that returns ``np.ndarray`` results (:issue:`18930`)

pandas/core/groupby/generic.py

@@ -1935,7 +1935,7 @@ def _gotitem(self, key, ndim: int, subset=None):
                 subset = self.obj
             return DataFrameGroupBy(
                 subset,
-                self.grouper,
+                self.keys,
                 axis=self.axis,
                 level=self.level,
                 grouper=self.grouper,
@@ -1952,6 +1952,7 @@ def _gotitem(self, key, ndim: int, subset=None):
                 subset = self.obj[key]
             return SeriesGroupBy(
                 subset,
+                self.keys,
                 level=self.level,
                 grouper=self.grouper,
                 exclusions=self.exclusions,

pandas/tests/groupby/test_groupby.py

@@ -2722,10 +2722,13 @@ def test_groupby_none_column_name():
     tm.assert_frame_equal(result, expected)
 
 
-def test_single_element_list_grouping():
-    # GH 42795
+@pytest.mark.parametrize("selection", [None, "a", ["a"]])
+def test_single_element_list_grouping(selection):
+    # GH#42795, GH#53500
     df = DataFrame({"a": [1, 2], "b": [np.nan, 5], "c": [np.nan, 2]}, index=["x", "y"])
-    result = [key for key, _ in df.groupby(["a"])]
+    grouped = df.groupby(["a"]) if selection is None else df.groupby(["a"])[selection]
+    result = [key for key, _ in grouped]
+
     expected = [(1,), (2,)]
     assert result == expected