BUG: Fix Grouper with a datetime key in conjunction with another key (pandas-dev#51414)

Author: juleek

doc/source/whatsnew/v2.1.0.rst

@@ -300,6 +300,7 @@ Groupby/resample/rolling
   grouped :class:`Series` or :class:`DataFrame` was a :class:`DatetimeIndex`, :class:`TimedeltaIndex`
   or :class:`PeriodIndex`, and the ``groupby`` method was given a function as its first argument,
   the function operated on the whole index rather than each element of the index. (:issue:`51979`)
+- Bug in :meth:`GroupBy.groups` with a datetime key in conjunction with another key produced incorrect number of group keys (:issue:`51158`)
 - Bug in :meth:`GroupBy.var` failing to raise ``TypeError`` when called with datetime64 or :class:`PeriodDtype` values (:issue:`52128`)
 - Bug in :meth:`DataFrameGroupBy.apply` causing an error to be raised when the input :class:`DataFrame` was subset as a :class:`DataFrame` after groupby (``[['a']]`` and not ``['a']``) and the given callable returned :class:`Series` that were not all indexed the same. (:issue:`52444`)
 -

pandas/core/groupby/ops.py

@@ -963,6 +963,9 @@ def groups(self):
         }
         return result
 
+    def __iter__(self) -> Iterator[Hashable]:
+        return iter(self.groupings[0].grouping_vector)
+
     @property
     def nkeys(self) -> int:
         # still matches len(self.groupings), but we can hard-code

pandas/tests/groupby/test_grouping.py

@@ -447,6 +447,29 @@ def test_groupby_grouper_f_sanity_checked(self):
         expected.index.freq = None
         tm.assert_series_equal(result, expected)
 
+    def test_groupby_with_datetime_key(self):
+        # GH 51158
+        df = DataFrame(
+            {
+                "id": ["a", "b"] * 3,
+                "b": date_range("2000-01-01", "2000-01-03", freq="9H"),
+            }
+        )
+        grouper = Grouper(key="b", freq="D")
+        gb = df.groupby([grouper, "id"])
+
+        # test number of groups
+        expected = {
+            (Timestamp("2000-01-01"), "a"): [0, 2],
+            (Timestamp("2000-01-01"), "b"): [1],
+            (Timestamp("2000-01-02"), "a"): [4],
+            (Timestamp("2000-01-02"), "b"): [3, 5],
+        }
+        tm.assert_dict_equal(gb.groups, expected)
+
+        # test number of group keys
+        assert len(gb.groups.keys()) == 4
+
     def test_grouping_error_on_multidim_input(self, df):
         msg = "Grouper for '<class 'pandas.core.frame.DataFrame'>' not 1-dimensional"
         with pytest.raises(ValueError, match=msg):