Backport PR pandas-dev#54882 on branch 2.1.x (REGR: get_group raising with axis=1) (pandas-dev#54956)

REGR: get_group raising with axis=1 (pandas-dev#54882)

(cherry picked from commit ab34dd6)

Author: phofl

doc/source/whatsnew/v2.1.1.rst

@@ -15,6 +15,7 @@ Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - Fixed regression in :func:`merge` when merging over a PyArrow string index (:issue:`54894`)
 - Fixed regression in :func:`read_csv` when ``usecols`` is given and ``dtypes`` is a dict for ``engine="python"`` (:issue:`54868`)
+- Fixed regression in :meth:`.GroupBy.get_group` raising for ``axis=1`` (:issue:`54858`)
 - Fixed regression in :meth:`DataFrame.__setitem__` raising ``AssertionError`` when setting a :class:`Series` with a partial :class:`MultiIndex` (:issue:`54875`)
 - Fixed regression in :meth:`Series.drop_duplicates` for PyArrow strings (:issue:`54904`)
 - Fixed regression in :meth:`Series.value_counts` raising for numeric data if ``bins`` was specified (:issue:`54857`)

pandas/core/groupby/groupby.py

@@ -1059,7 +1059,8 @@ def get_group(self, name, obj=None) -> DataFrame | Series:
             raise KeyError(name)
 
         if obj is None:
-            return self._selected_obj.iloc[inds]
+            indexer = inds if self.axis == 0 else (slice(None), inds)
+            return self._selected_obj.iloc[indexer]
         else:
             warnings.warn(
                 "obj is deprecated and will be removed in a future version. "

pandas/tests/groupby/test_groupby.py

@@ -3159,3 +3159,26 @@ def test_groupby_series_with_datetimeindex_month_name():
     expected = Series([2, 1], name="jan")
     expected.index.name = "jan"
     tm.assert_series_equal(result, expected)
+
+
+def test_get_group_axis_1():
+    # GH#54858
+    df = DataFrame(
+        {
+            "col1": [0, 3, 2, 3],
+            "col2": [4, 1, 6, 7],
+            "col3": [3, 8, 2, 10],
+            "col4": [1, 13, 6, 15],
+            "col5": [-4, 5, 6, -7],
+        }
+    )
+    with tm.assert_produces_warning(FutureWarning, match="deprecated"):
+        grouped = df.groupby(axis=1, by=[1, 2, 3, 2, 1])
+    result = grouped.get_group(1)
+    expected = DataFrame(
+        {
+            "col1": [0, 3, 2, 3],
+            "col5": [-4, 5, 6, -7],
+        }
+    )
+    tm.assert_frame_equal(result, expected)