feat(db): aggregate_marches pour les requêtes GROUP BY (#78)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

tests/api/test_db_aggregate.py

@@ -0,0 +1,19 @@
+import polars as pl
+
+from src.db import aggregate_marches
+
+
+def test_aggregate_groupby_count_returns_named_columns():
+    df = aggregate_marches(
+        select_sql='"acheteur_departement_code", COUNT("uid") AS "uid__count"',
+        group_by='"acheteur_departement_code"',
+    )
+    assert isinstance(df, pl.DataFrame)
+    assert df.columns == ["acheteur_departement_code", "uid__count"]
+    assert df["uid__count"].sum() > 0
+
+
+def test_aggregate_global_without_groupby_returns_one_row():
+    df = aggregate_marches(select_sql='COUNT("uid") AS "uid__count"')
+    assert df.height == 1
+    assert df["uid__count"][0] > 0