BUG: Fix Grouper with a datetime key in conjunction with another key

doc/source/whatsnew/v2.1.0.rst

@@ -243,6 +243,7 @@ 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`)
 -
 

pandas/core/groupby/ops.py

@@ -1186,6 +1186,9 @@ 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):