BUG: Fix groupby with MultiIndex Series corner case (#25704) (#25743)

Author: ArtificialQualia

doc/source/whatsnew/v0.25.0.rst

@@ -371,6 +371,7 @@ Groupby/Resample/Rolling
 - Bug in :meth:`pandas.core.groupby.DataFrameGroupBy.nunique` in which the names of column levels were lost (:issue:`23222`)
 - Bug in :func:`pandas.core.groupby.GroupBy.agg` when applying a aggregation function to timezone aware data (:issue:`23683`)
 - Bug in :func:`pandas.core.groupby.GroupBy.first` and :func:`pandas.core.groupby.GroupBy.last` where timezone information would be dropped (:issue:`21603`)
+- Bug in :func:`Series.groupby` where using ``groupby`` with a :class:`MultiIndex` Series with a list of labels equal to the length of the series caused incorrect grouping (:issue:`25704`)
 - Ensured that ordering of outputs in ``groupby`` aggregation functions is consistent across all versions of Python (:issue:`25692`)
 - Bug in :func:`idxmax` and :func:`idxmin` on :meth:`DataFrame.groupby` with datetime column would return incorrect dtype (:issue:`25444`, :issue:`15306`)
 

pandas/core/groupby/grouper.py

@@ -524,6 +524,8 @@ def _get_grouper(obj, key=None, axis=0, level=None, sort=True,
         if isinstance(obj, DataFrame):
             all_in_columns_index = all(g in obj.columns or g in obj.index.names
                                        for g in keys)
+        elif isinstance(obj, Series):
+            all_in_columns_index = all(g in obj.index.names for g in keys)
         else:
             all_in_columns_index = False
     except Exception:

pandas/tests/groupby/test_groupby.py

@@ -1719,3 +1719,23 @@ def test_groupby_empty_list_raises():
     msg = "Grouper and axis must be same length"
     with pytest.raises(ValueError, match=msg):
         df.groupby([[]])
+
+
+def test_groupby_multiindex_series_keys_len_equal_group_axis():
+    # GH 25704
+    index_array = [
+        ['x', 'x'],
+        ['a', 'b'],
+        ['k', 'k']
+    ]
+    index_names = ['first', 'second', 'third']
+    ri = pd.MultiIndex.from_arrays(index_array, names=index_names)
+    s = pd.Series(data=[1, 2], index=ri)
+    result = s.groupby(['first', 'third']).sum()
+
+    index_array = [['x'], ['k']]
+    index_names = ['first', 'third']
+    ei = pd.MultiIndex.from_arrays(index_array, names=index_names)
+    expected = pd.Series([3], index=ei)
+
+    assert_series_equal(result, expected)