BUG: Attributes are lost when subsetting columns in groupby

doc/source/whatsnew/v1.2.0.rst

@@ -251,6 +251,8 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrameGroupBy.apply` that would some times throw an erroneous ``ValueError`` if the grouping axis had duplicate entries (:issue:`16646`)
 - Bug when combining methods :meth:`DataFrame.groupby` with :meth:`DataFrame.resample` and :meth:`DataFrame.interpolate` raising an ``TypeError`` (:issue:`35325`)
 - Bug in :meth:`DataFrameGroupBy.apply` where a non-nuisance grouping column would be dropped from the output columns if another groupby method was called before ``.apply()`` (:issue:`34656`)
+- Bug when subsetting columns on a :class:`~pandas.core.groupby.DataFrameGroupBy` (e.g. ``df.groupby('a')[['b']])``) would reset the attributes ``axis``, ``dropna``, ``group_keys``, ``level``, ``mutated``, ``sort``, and ``squeeze`` to their default values. (:issue:`9959`)
+-
 
 Reshaping
 ^^^^^^^^^

pandas/core/groupby/generic.py

@@ -1650,17 +1650,32 @@ def _gotitem(self, key, ndim: int, subset=None):
             return DataFrameGroupBy(
                 subset,
                 self.grouper,
-                selection=key,
+                axis=self.axis,
+                level=self.level,
                 grouper=self.grouper,
                 exclusions=self.exclusions,
+                selection=key,
                 as_index=self.as_index,
+                sort=self.sort,
+                group_keys=self.group_keys,
+                squeeze=self.squeeze,
                 observed=self.observed,
+                mutated=self.mutated,
+                dropna=self.dropna,
             )
         elif ndim == 1:
             if subset is None:
                 subset = self.obj[key]
             return SeriesGroupBy(
-                subset, selection=key, grouper=self.grouper, observed=self.observed
+                subset,
+                level=self.level,
+                grouper=self.grouper,
+                selection=key,
+                sort=self.sort,
+                group_keys=self.group_keys,
+                squeeze=self.squeeze,
+                observed=self.observed,
+                dropna=self.dropna,
             )
 
         raise AssertionError("invalid ndim for _gotitem")

pandas/tests/groupby/test_groupby.py

@@ -2069,3 +2069,36 @@ def test_group_on_two_row_multiindex_returns_one_tuple_key():
     assert len(result) == 1
     key = (1, 2)
     assert (result[key] == expected[key]).all()
+
+
+@pytest.mark.parametrize(
+    "attr, value",
+    [
+        ("axis", 1),
+        ("level", "a"),
+        ("as_index", False),
+        ("sort", False),
+        ("group_keys", False),
+        ("squeeze", True),
+        ("observed", True),
+        ("dropna", False),
+    ],
+)
+@pytest.mark.filterwarnings(
+    "ignore:The `squeeze` parameter is deprecated:FutureWarning"
+)
+def test_subsetting_columns_keeps_attrs(attr, value):
+    # GH 9959 - When subsetting columns, don't drop attributes
+    df = pd.DataFrame({"a": [1], "b": [2], "c": [3]})
+    if attr != "axis":
+        df = df.set_index("a")
+
+    expected = df.groupby("a", **{attr: value})
+
+    result = expected[["b"]]
+    assert getattr(result, attr) == getattr(expected, attr)
+
+    if attr in ("axis", "as_index"):
+        pytest.xfail("GH 35443: Attribute currently not passed on to series")
+    result = expected["b"]
+    assert getattr(result, attr) == getattr(expected, attr)