Fix multi index problem

src/recx/rec.py

@@ -55,8 +55,8 @@ def clip_to_last_common_date(
         ``(a_clipped, b_clipped)`` with only rows whose ``date_col`` value is
         less than or equal to the shared maximum date.
     """
-    a_dates = get_col(a, date_col)
-    b_dates = get_col(b, date_col)
+    a_dates = get_col(a, date_col).to_numpy()
+    b_dates = get_col(b, date_col).to_numpy()
 
     latest_date = min(a_dates.max(), b_dates.max())
 

tests/fixtures/frames.py

@@ -63,3 +63,26 @@ def equal_nan_frames():
     baseline = pd.DataFrame({"A": [1.0, None]})
     candidate = pd.DataFrame({"A": [1.0, None]})
     return baseline, candidate
+
+
+@pytest.fixture
+def multi_index_frames():
+    baseline = pd.DataFrame(
+        {
+            "vintage_date": ["2024-01-01", "2024-01-02"],
+            "date": ["2024-01-01", "2024-01-02"],
+            "series_id": [1, 2],
+            "A": [1, 2],
+            "B": [3, 4],
+        }
+    ).set_index(["vintage_date", "date", "series_id"])
+    candidate = pd.DataFrame(
+        {
+            "vintage_date": ["2024-01-01", "2024-01-02", "2024-01-03"],
+            "date": ["2024-01-01", "2024-01-02", "2024-01-03"],
+            "series_id": [1, 2, 3],
+            "A": [1, 2, 3],
+            "B": [3, 4, 6],
+        }
+    ).set_index(["vintage_date", "date", "series_id"])
+    return baseline, candidate

tests/unit/test_utils.py

@@ -15,3 +15,14 @@ def test_clip_to_last_common_date_index(dated_frames):
     assert a_clip.equals(baseline)
     # Candidate should be clipped to remove trailing 2024-01-03, keeping first two rows
     assert list(b_clip.index) == ["2024-01-01", "2024-01-02"]
+
+
+def test_clip_to_last_common_date_index_on_multi_index(multi_index_frames):
+    b, c = multi_index_frames
+    a_clip, b_clip = clip_to_last_common_date(b, c, "vintage_date")
+    assert a_clip.equals(b)
+
+    assert b_clip.index.get_level_values("vintage_date").tolist() == [
+        "2024-01-01",
+        "2024-01-02",
+    ]