feat: Trends landing page with directorate overview chart (Task E.3)

src/data_processing/pathway_queries.py

@@ -1591,18 +1591,19 @@ def get_trend_data(
     metric: str = "patients",
     directory: Optional[str] = None,
     drug: Optional[str] = None,
+    group_by: str = "drug",
 ) -> list[dict]:
     """
     Query pathway_trends table for time-series data.
 
     Returns list of dicts with: period_end, name (drug or directory), value.
-    Groups by drug (one line per drug) unless aggregating by directory.
 
     Args:
         db_path: Path to pathways.db
         metric: "patients", "total_cost", or "cost_pp_pa"
         directory: Optional directory filter
         drug: Optional drug filter
+        group_by: "drug" (one line per drug) or "directory" (one line per directory)
 
     Returns:
         List of dicts: [{period_end, name, value}, ...]
@@ -1612,7 +1613,6 @@ def get_trend_data(
     conn.row_factory = sqlite3.Row
 
     try:
-        # Check if the table exists
         cursor = conn.cursor()
         cursor.execute(
             "SELECT name FROM sqlite_master WHERE type='table' AND name='pathway_trends'"
@@ -1624,7 +1624,6 @@ def get_trend_data(
         if metric not in valid_metrics:
             metric = "patients"
 
-        # Build query — group by drug (one line per drug over time)
         where_clauses = []
         params = []
 
@@ -1637,16 +1636,10 @@ def get_trend_data(
 
         where_sql = " AND ".join(where_clauses) if where_clauses else "1=1"
 
-        # Aggregate across directories per drug per period (or per directory if filtering by drug)
-        if drug:
-            # One line per directory for a specific drug
-            group_col = "directory"
-        else:
-            # One line per drug (aggregate across directories)
-            group_col = "drug"
+        # Determine grouping column
+        group_col = "directory" if group_by == "directory" else "drug"
 
         if metric == "cost_pp_pa":
-            # Weighted average for cost_pp_pa
             agg = "SUM(cost_pp_pa * patients) / NULLIF(SUM(patients), 0)"
         elif metric == "total_cost":
             agg = "SUM(total_cost)"