BUG: Groupby head/tail with axis=1 fails

doc/source/whatsnew/v1.2.0.rst

@@ -543,6 +543,8 @@ Groupby/resample/rolling
 - Bug in :meth:`df.groupby(..).quantile() <pandas.core.groupby.DataFrameGroupBy.quantile>` and :meth:`df.resample(..).quantile() <pandas.core.resample.Resampler.quantile>` raised ``TypeError`` when values were of type ``Timedelta`` (:issue:`29485`)
 - Bug in :meth:`Rolling.median` and :meth:`Rolling.quantile` returned wrong values for :class:`BaseIndexer` subclasses with non-monotonic starting or ending points for windows (:issue:`37153`)
 - Bug in :meth:`DataFrame.groupby` dropped ``nan`` groups from result with ``dropna=False`` when grouping over a single column (:issue:`35646`, :issue:`35542`)
+- Bug in :meth:`DataFrameGroupBy.head`, :meth:`DataFrameGroupBy.tail`, :meth:`SeriesGroupBy.head`, and :meth:`SeriesGroupBy.tail` would raise when used with ``axis=1`` (:issue:`9772`)
+
 
 Reshaping
 ^^^^^^^^^

pandas/core/groupby/groupby.py

@@ -2742,7 +2742,10 @@ def head(self, n=5):
         """
         self._reset_group_selection()
         mask = self._cumcount_array() < n
-        return self._selected_obj[mask]
+        if self.axis == 0:
+            return self._selected_obj[mask]
+        else:
+            return self._selected_obj.iloc[:, mask]
 
     @Substitution(name="groupby")
     @Substitution(see_also=_common_see_also)
@@ -2776,7 +2779,10 @@ def tail(self, n=5):
         """
         self._reset_group_selection()
         mask = self._cumcount_array(ascending=False) < n
-        return self._selected_obj[mask]
+        if self.axis == 0:
+            return self._selected_obj[mask]
+        else:
+            return self._selected_obj.iloc[:, mask]
 
     def _reindex_output(
         self, output: OutputFrameOrSeries, fill_value: Scalar = np.NaN

pandas/tests/groupby/test_nth.py

@@ -513,6 +513,30 @@ def test_groupby_head_tail(op, n, expected_rows, columns, as_index):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.parametrize(
+    "op, n, expected_cols",
+    [
+        ("head", -1, []),
+        ("head", 0, []),
+        ("head", 1, [0, 2]),
+        ("head", 7, [0, 1, 2]),
+        ("tail", -1, []),
+        ("tail", 0, []),
+        ("tail", 1, [1, 2]),
+        ("tail", 7, [0, 1, 2]),
+    ],
+)
+def test_groupby_head_tail_axis_1(op, n, expected_cols):
+    # GH 9772
+    df = DataFrame(
+        [[1, 2, 3], [1, 4, 5], [2, 6, 7], [3, 8, 9]], columns=["A", "B", "C"]
+    )
+    g = df.groupby([0, 0, 1], axis=1)
+    expected = df.iloc[:, expected_cols]
+    result = getattr(g, op)(n)
+    tm.assert_frame_equal(result, expected)
+
+
 def test_group_selection_cache():
     # GH 12839 nth, head, and tail should return same result consistently
     df = DataFrame([[1, 2], [1, 4], [5, 6]], columns=["A", "B"])