BUG: Fix Series.groupby raising OutOfBoundsDatetime with DatetimeIndex and month name (#54306)

Fix Series.groupby raising OutOfBoundsDatetime with DatetimeIndex and month name

Author: yuanx749

doc/source/whatsnew/v2.1.0.rst

@@ -723,6 +723,7 @@ Groupby/resample/rolling
 - Bug in :meth:`GroupBy.var` failing to raise ``TypeError`` when called with datetime64, timedelta64 or :class:`PeriodDtype` values (:issue:`52128`, :issue:`53045`)
 - Bug in :meth:`DataFrameGroupby.resample` with ``kind="period"`` raising ``AttributeError`` (:issue:`24103`)
 - Bug in :meth:`Resampler.ohlc` with empty object returning a :class:`Series` instead of empty :class:`DataFrame` (:issue:`42902`)
+- Bug in :meth:`Series.groupby` raising an error when grouped :class:`Series` has a :class:`DatetimeIndex` index and a :class:`Series` with a name that is a month is given to the ``by`` argument (:issue:`48509`)
 - Bug in :meth:`SeriesGroupBy.count` and :meth:`DataFrameGroupBy.count` where the dtype would be ``np.int64`` for data with :class:`ArrowDtype` or masked dtypes (e.g. ``Int64``) (:issue:`53831`)
 - Bug in :meth:`SeriesGroupBy.nth` and :meth:`DataFrameGroupBy.nth` after performing column selection when using ``dropna="any"`` or ``dropna="all"`` would not subset columns (:issue:`53518`)
 - Bug in :meth:`SeriesGroupBy.nth` and :meth:`DataFrameGroupBy.nth` raised after performing column selection when using ``dropna="any"`` or ``dropna="all"`` resulted in rows being dropped (:issue:`53518`)

pandas/core/groupby/grouper.py

@@ -15,6 +15,7 @@
 from pandas._config import using_copy_on_write
 
 from pandas._libs import lib
+from pandas._libs.tslibs import OutOfBoundsDatetime
 from pandas.errors import InvalidIndexError
 from pandas.util._decorators import cache_readonly
 from pandas.util._exceptions import find_stack_level
@@ -969,7 +970,7 @@ def is_in_obj(gpr) -> bool:
             # series is part of the object
             try:
                 obj_gpr_column = obj[gpr.name]
-            except (KeyError, IndexError, InvalidIndexError):
+            except (KeyError, IndexError, InvalidIndexError, OutOfBoundsDatetime):
                 return False
             if isinstance(gpr, Series) and isinstance(obj_gpr_column, Series):
                 return gpr._mgr.references_same_values(  # type: ignore[union-attr]
@@ -978,11 +979,13 @@ def is_in_obj(gpr) -> bool:
             return False
         try:
             return gpr is obj[gpr.name]
-        except (KeyError, IndexError, InvalidIndexError):
+        except (KeyError, IndexError, InvalidIndexError, OutOfBoundsDatetime):
             # IndexError reached in e.g. test_skip_group_keys when we pass
             #  lambda here
             # InvalidIndexError raised on key-types inappropriate for index,
             #  e.g. DatetimeIndex.get_loc(tuple())
+            # OutOfBoundsDatetime raised when obj is a Series with DatetimeIndex
+            # and gpr.name is month str
             return False
 
     for gpr, level in zip(keys, levels):

pandas/tests/groupby/test_groupby.py

@@ -3124,3 +3124,12 @@ def test_groupby_with_Time_Grouper():
     df = test_data.groupby(Grouper(key="time2", freq="1T")).count().reset_index()
 
     tm.assert_frame_equal(df, expected_output)
+
+
+def test_groupby_series_with_datetimeindex_month_name():
+    # GH 48509
+    s = Series([0, 1, 0], index=date_range("2022-01-01", periods=3), name="jan")
+    result = s.groupby(s).count()
+    expected = Series([2, 1], name="jan")
+    expected.index.name = "jan"
+    tm.assert_series_equal(result, expected)