BUG: fix subclass metadata preservation in groupby column selection (#56761)

Author: jorisvandenbossche

doc/source/whatsnew/v2.2.0.rst

@@ -873,6 +873,7 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrame.asfreq` and :meth:`Series.asfreq` with a :class:`DatetimeIndex` with non-nanosecond resolution incorrectly converting to nanosecond resolution (:issue:`55958`)
 - Bug in :meth:`DataFrame.ewm` when passed ``times`` with non-nanosecond ``datetime64`` or :class:`DatetimeTZDtype` dtype (:issue:`56262`)
 - Bug in :meth:`DataFrame.groupby` and :meth:`Series.groupby` where grouping by a combination of ``Decimal`` and NA values would fail when ``sort=True`` (:issue:`54847`)
+- Bug in :meth:`DataFrame.groupby` for DataFrame subclasses when selecting a subset of columns to apply the function to (:issue:`56761`)
 - Bug in :meth:`DataFrame.resample` not respecting ``closed`` and ``label`` arguments for :class:`~pandas.tseries.offsets.BusinessDay` (:issue:`55282`)
 - Bug in :meth:`DataFrame.resample` when resampling on a :class:`ArrowDtype` of ``pyarrow.timestamp`` or ``pyarrow.duration`` type (:issue:`55989`)
 - Bug in :meth:`DataFrame.resample` where bin edges were not correct for :class:`~pandas.tseries.offsets.BusinessDay` (:issue:`55281`)

pandas/core/frame.py

@@ -4016,7 +4016,9 @@ def _getitem_nocopy(self, key: list):
             copy=False,
             only_slice=True,
         )
-        return self._constructor_from_mgr(new_mgr, axes=new_mgr.axes)
+        result = self._constructor_from_mgr(new_mgr, axes=new_mgr.axes)
+        result = result.__finalize__(self)
+        return result
 
     def __getitem__(self, key):
         check_dict_or_set_indexers(key)

pandas/tests/groupby/test_groupby_subclass.py

@@ -69,6 +69,7 @@ def test_groupby_preserves_metadata():
     def func(group):
         assert isinstance(group, tm.SubclassedDataFrame)
         assert hasattr(group, "testattr")
+        assert group.testattr == "hello"
         return group.testattr
 
     msg = "DataFrameGroupBy.apply operated on the grouping columns"
@@ -79,6 +80,13 @@ def func(group):
     expected = tm.SubclassedSeries(["hello"] * 3, index=Index([7, 8, 9], name="c"))
     tm.assert_series_equal(result, expected)
 
+    result = custom_df.groupby("c").apply(func, include_groups=False)
+    tm.assert_series_equal(result, expected)
+
+    # https://github.com/pandas-dev/pandas/pull/56761
+    result = custom_df.groupby("c")[["a", "b"]].apply(func)
+    tm.assert_series_equal(result, expected)
+
     def func2(group):
         assert isinstance(group, tm.SubclassedSeries)
         assert hasattr(group, "testattr")