fix: count/nunique aggregates yield 0, not NaN, for parents without children

src/auto_bayesian/materialize.py

@@ -54,6 +54,18 @@ def materialize_project(
                 left_on=relation.parent_key,
                 right_on=relation.parent_key,
             )
+            count_columns = [
+                aggregate.output_name(relation.child)
+                for aggregate in relation.aggregations
+                if aggregate.op in ("count", "nunique")
+            ]
+            if count_columns:
+                # A parent with no child rows has a count of 0, not a missing
+                # value. Left NaN, these zeros would later be binned as
+                # "__missing__" and become indistinguishable from genuinely
+                # absent data. Other ops (mean, latest, ...) stay NaN, since
+                # they are truly undefined over an empty set.
+                parent[count_columns] = parent[count_columns].fillna(0)
         if relation.sequence_features:
             seq = _compute_sequence_features(child, relation, project.tables[relation.child])
             parent = parent.merge(
@@ -257,4 +269,4 @@ def _compute_acceleration(gaps: pd.Series) -> float:
     if older_mean == 0 and recent_mean == 0:
         return 0.0
     denom = older_mean if older_mean != 0 else 1.0
-    return float((older_mean - recent_mean) / denom)
+    return float((older_mean - recent_mean) / denom)

tests/test_materialize.py

@@ -22,3 +22,53 @@ def test_materialize_project_joins_and_aggregates() -> None:
     assert lead_2["interaction_count"] == 2
     assert lead_2["channel_count"] == 2
     assert lead_2["latest_channel"] == "meeting"
+
+
+def test_one_to_many_count_is_zero_for_parents_without_children(tmp_path: Path) -> None:
+    import pandas as pd
+
+    from auto_bayesian import build_project
+
+    parents = pd.DataFrame(
+        {"tender_id": ["T1", "T2", "T3"], "won": ["1", "0", "0"]}
+    )
+    children = pd.DataFrame(
+        {
+            "bid_id": ["B1", "B2", "B3"],
+            "tender_id": ["T1", "T1", "T2"],
+            "bidder": ["a", "b", "a"],
+            "price": [0.9, 1.1, 0.95],
+        }
+    )
+    project = build_project(
+        root=tmp_path,
+        root_table="tenders",
+        target_column="won",
+        positive_label="1",
+        output_dir=tmp_path / "artifacts",
+        tables=[
+            {"name": "tenders", "primary_key": "tender_id"},
+            {"name": "bids", "primary_key": "bid_id"},
+        ],
+        relations=[
+            {
+                "parent": "tenders",
+                "child": "bids",
+                "parent_key": "tender_id",
+                "child_key": "tender_id",
+                "kind": "one_to_many",
+                "aggregations": [
+                    {"op": "count", "name": "bid_count"},
+                    {"column": "bidder", "op": "nunique", "name": "bidder_count"},
+                    {"column": "price", "op": "mean", "name": "mean_price"},
+                ],
+            }
+        ],
+    )
+    frame = materialize_project(project, tables={"tenders": parents, "bids": children})
+    childless = frame.loc[frame["tender_id"] == "T3"].iloc[0]
+
+    assert childless["bid_count"] == 0
+    assert childless["bidder_count"] == 0
+    assert pd.isna(childless["mean_price"])
+    assert frame.loc[frame["tender_id"] == "T1"].iloc[0]["bid_count"] == 2