diff --git a/doc/source/whatsnew/v1.2.0.rst b/doc/source/whatsnew/v1.2.0.rst
index 55570341cf4e8..1617bf66c4f04 100644
--- a/doc/source/whatsnew/v1.2.0.rst
+++ b/doc/source/whatsnew/v1.2.0.rst
@@ -255,6 +255,8 @@ Groupby/resample/rolling
 - 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 in :meth:`DataFrameGroupby.apply` would drop a :class:`CategoricalIndex` when grouped on. (:issue:`35792`)
+- 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
 ^^^^^^^^^
diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index e39464628ccaa..7b45a114e548b 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1603,17 +1603,32 @@ 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")
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 8c51ebf89f5c0..c743058c988b4 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2069,3 +2069,45 @@ 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(
+    "klass, attr, value",
+    [
+        (DataFrame, "axis", 1),
+        (DataFrame, "level", "a"),
+        (DataFrame, "as_index", False),
+        (DataFrame, "sort", False),
+        (DataFrame, "group_keys", False),
+        (DataFrame, "squeeze", True),
+        (DataFrame, "observed", True),
+        (DataFrame, "dropna", False),
+        pytest.param(
+            Series,
+            "axis",
+            1,
+            marks=pytest.mark.xfail(
+                reason="GH 35443: Attribute currently not passed on to series"
+            ),
+        ),
+        (Series, "level", "a"),
+        (Series, "as_index", False),
+        (Series, "sort", False),
+        (Series, "group_keys", False),
+        (Series, "squeeze", True),
+        (Series, "observed", True),
+        (Series, "dropna", False),
+    ],
+)
+@pytest.mark.filterwarnings(
+    "ignore:The `squeeze` parameter is deprecated:FutureWarning"
+)
+def test_subsetting_columns_keeps_attrs(klass, 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"]] if klass is DataFrame else expected["b"]
+    assert getattr(result, attr) == getattr(expected, attr)