feat: pathway depth distribution chart tab (Task C.2)

Horizontal bar chart showing patients who stopped at each treatment
line depth (exclusive counts, not cumulative like the funnel).

IMPLEMENTATION_PLAN.md

@@ -146,15 +146,17 @@ Comprehensive review and improvement of all Plotly charts in the Dash dashboard.
 - **Checkpoint**: Funnel tab shows retention by treatment line depth, responds to filters
 
 ### C.2 Pathway depth distribution chart
-- [ ] Create `get_pathway_depth_distribution()` in `src/data_processing/pathway_queries.py`:
+- [x] Create `get_pathway_depth_distribution()` in `src/data_processing/pathway_queries.py`:
   - Aggregate patient counts at level 3 (1-drug), level 4 (2-drug), etc.
   - Subtract child counts to get patients who STOPPED at each depth
-  - Return: `[{depth: 1, label: "1 drug only", patients: N}, ...]`
-- [ ] Add thin wrapper in `dash_app/data/queries.py`
-- [ ] Create `create_pathway_depth_figure(data, title)` in `src/visualization/plotly_generator.py`:
+  - Return: `[{depth: 1, label: "1 drug only", patients: N, pct: 80.2}, ...]`
+- [x] Add thin wrapper in `dash_app/data/queries.py`
+- [x] Create `create_pathway_depth_figure(data, title)` in `src/visualization/plotly_generator.py`:
   - Horizontal bar chart with NHS blue gradient by depth
-- [ ] Add "Depth" tab to `TAB_DEFINITIONS` in `chart_card.py`
-- [ ] Add `_render_depth()` helper and tab dispatch in `dash_app/callbacks/chart.py`
+  - Text shows "N (pct%)" inside bars
+  - Uses `_base_layout()` for consistent styling
+- [x] Add "Depth" tab to `TAB_DEFINITIONS` in `chart_card.py` (5 tabs: Icicle, Sankey, Heatmap, Funnel, Depth)
+- [x] Add `_render_depth()` helper and tab dispatch in `dash_app/callbacks/chart.py`
 - **Checkpoint**: Depth tab shows patient distribution by treatment line count
 
 ### C.3 Duration vs Cost scatter plot

dash_app/callbacks/chart.py

@@ -292,6 +292,31 @@ def _render_funnel(app_state, title):
     return create_retention_funnel_figure(data, title)
 
 
+def _render_depth(app_state, title):
+    """Build the pathway depth distribution figure from current filter state."""
+    from dash_app.data.queries import get_pathway_depth_distribution
+    from visualization.plotly_generator import create_pathway_depth_figure
+
+    filter_id = (app_state or {}).get("date_filter_id", "all_6mo")
+    chart_type = (app_state or {}).get("chart_type", "directory")
+
+    selected_dirs = (app_state or {}).get("selected_directorates") or []
+    selected_trusts = (app_state or {}).get("selected_trusts") or []
+    directory = selected_dirs[0] if len(selected_dirs) == 1 else None
+    trust = selected_trusts[0] if len(selected_trusts) == 1 else None
+
+    try:
+        data = get_pathway_depth_distribution(filter_id, chart_type, directory, trust)
+    except Exception:
+        log.exception("Failed to load pathway depth data")
+        return _empty_figure("Failed to load pathway depth data.")
+
+    if not data:
+        return _empty_figure("No pathway depth data available.\nTry adjusting your filters.")
+
+    return create_pathway_depth_figure(data, title)
+
+
 def register_chart_callbacks(app):
     """Register tab switching, pathway data loading, and chart rendering callbacks."""
 
@@ -435,6 +460,9 @@ def register_chart_callbacks(app):
         elif active_tab == "funnel":
             fig = _render_funnel(app_state, title)
 
+        elif active_tab == "depth":
+            fig = _render_depth(app_state, title)
+
         else:
             # Placeholder for charts not yet implemented
             tab_label = dict(TAB_DEFINITIONS).get(active_tab, active_tab)

dash_app/components/chart_card.py

@@ -9,6 +9,7 @@ TAB_DEFINITIONS = [
     ("sankey", "Sankey"),
     ("heatmap", "Heatmap"),
     ("funnel", "Funnel"),
+    ("depth", "Depth"),
 ]
 
 # Full set retained for Trust Comparison dashboard (Phase 10.8)

dash_app/data/queries.py

@@ -25,6 +25,7 @@ from data_processing.pathway_queries import (
     get_trust_durations as _get_trust_durations,
     get_directorate_summary as _get_directorate_summary,
     get_retention_funnel as _get_retention_funnel,
+    get_pathway_depth_distribution as _get_pathway_depth_distribution,
 )
 
 DB_PATH = Path(__file__).resolve().parents[2] / "data" / "pathways.db"
@@ -194,3 +195,13 @@ def get_retention_funnel(
 ) -> list[dict]:
     """Patient retention by treatment line depth."""
     return _get_retention_funnel(DB_PATH, date_filter_id, chart_type, directory, trust)
+
+
+def get_pathway_depth_distribution(
+    date_filter_id: str = "all_6mo",
+    chart_type: str = "directory",
+    directory: Optional[str] = None,
+    trust: Optional[str] = None,
+) -> list[dict]:
+    """Patients who stopped at each treatment line depth (exclusive counts)."""
+    return _get_pathway_depth_distribution(DB_PATH, date_filter_id, chart_type, directory, trust)

src/data_processing/pathway_queries.py

@@ -1139,6 +1139,76 @@ def get_retention_funnel(
         conn.close()
 
 
+def get_pathway_depth_distribution(
+    db_path: Path,
+    date_filter_id: str,
+    chart_type: str,
+    directory: Optional[str] = None,
+    trust: Optional[str] = None,
+) -> list[dict]:
+    """Count patients who STOPPED at each treatment line depth.
+
+    Unlike the retention funnel (cumulative), this shows exclusive counts:
+    patients at depth N minus patients at depth N+1 = stopped at depth N.
+
+    Returns list of dicts sorted by depth ascending:
+        [{depth: 1, label: "1 drug only", patients: N, pct: 45.2}, ...]
+    """
+    conn = sqlite3.connect(str(db_path))
+    conn.row_factory = sqlite3.Row
+    try:
+        where = ["date_filter_id = ?", "chart_type = ?", "level >= 3"]
+        params: list = [date_filter_id, chart_type]
+
+        if directory:
+            where.append("directory = ?")
+            params.append(directory)
+        if trust:
+            where.append("trust_name = ?")
+            params.append(trust)
+
+        query = f"""
+            SELECT level, SUM(value) AS patients
+            FROM pathway_nodes
+            WHERE {' AND '.join(where)}
+            GROUP BY level
+            ORDER BY level
+        """
+        rows = conn.execute(query, params).fetchall()
+
+        if not rows:
+            return []
+
+        # Build list of (depth, cumulative_patients)
+        levels = []
+        for r in rows:
+            depth = r["level"] - 2  # level 3 → depth 1
+            patients = r["patients"] or 0
+            levels.append((depth, patients))
+
+        # Subtract next level to get "stopped at this depth"
+        total_patients = levels[0][1] if levels else 0
+        result = []
+        for i, (depth, patients) in enumerate(levels):
+            next_patients = levels[i + 1][1] if i + 1 < len(levels) else 0
+            stopped = patients - next_patients
+
+            label = f"{depth} drug{'s' if depth > 1 else ''} only"
+            pct = round(stopped / total_patients * 100, 1) if total_patients else 0
+            result.append({
+                "depth": depth,
+                "label": label,
+                "patients": stopped,
+                "pct": pct,
+            })
+
+        return result
+    except sqlite3.Error:
+        return []
+    finally:
+        conn.close()
+
+
 def get_directorate_summary(
     db_path: Path,
     date_filter_id: str,

src/visualization/plotly_generator.py

@@ -1820,3 +1820,74 @@ def create_retention_funnel_figure(
     fig.update_layout(**layout)
 
     return fig
+
+
+def create_pathway_depth_figure(
+    data: list[dict],
+    title: str = "",
+) -> go.Figure:
+    """Create a horizontal bar chart showing patients who stopped at each treatment depth.
+
+    Args:
+        data: List of dicts with keys: depth, label, patients, pct
+        title: Chart title from filter state.
+
+    Returns:
+        Plotly Figure with horizontal bar trace.
+    """
+    if not data:
+        return go.Figure()
+
+    display_title = f"Pathway Depth Distribution — {title}" if title else "Pathway Depth Distribution"
+
+    labels = [d["label"] for d in data]
+    patients = [d["patients"] for d in data]
+    pcts = [d["pct"] for d in data]
+
+    # NHS blue gradient: darkest for depth 1 (most patients) → lightest
+    bar_colors = [
+        "#003087",
+        "#005EB8",
+        "#1E88E5",
+        "#42A5F5",
+        "#90CAF9",
+    ]
+    colors = bar_colors[: len(data)]
+    if len(colors) < len(data):
+        colors.extend(["#E3F2FD"] * (len(data) - len(colors)))
+
+    fig = go.Figure(
+        go.Bar(
+            y=labels,
+            x=patients,
+            orientation="h",
+            text=[f"{p:,} ({pct}%)" for p, pct in zip(patients, pcts)],
+            textposition="auto",
+            textfont=dict(family=CHART_FONT_FAMILY, size=13),
+            marker=dict(color=colors),
+            hovertemplate=(
+                "<b>%{y}</b><br>"
+                "Patients: %{x:,}<br>"
+                "<extra></extra>"
+            ),
+        )
+    )
+
+    layout = _base_layout(display_title)
+    layout.update(
+        margin=dict(t=60, l=8, r=24, b=40),
+        yaxis=dict(
+            automargin=True,
+            autorange="reversed",
+            title="",
+        ),
+        xaxis=dict(
+            title="Patients",
+            gridcolor=GRID_COLOR,
+        ),
+        height=max(300, len(data) * 70 + 120),
+        bargap=0.3,
+    )
+    fig.update_layout(**layout)
+
+    return fig