Deploy Space: update src

src/utils.py

@@ -602,3 +602,73 @@ def make_rank_trend_plot(history_df: pd.DataFrame, metrics: list[str] | None = N
         yaxis=dict(gridcolor="rgba(0,0,0,0.08)"),
     )
     return fig
+
+
+DOMAIN_COLORS = {
+    "Finance": "#f97316",
+    "Climate": "#60a5fa",
+    "Ocean": "#34d399",
+    "Hydrology": "#818cf8",
+    "Transport": "#fbbf24",
+    "Hazards": "#fb7185",
+    "Web": "#a78bfa",
+    "Other": "#94a3b8",
+}
+
+
+def make_domain_pie_chart(root_dir: str = "results") -> object | None:
+    """Build a plotly Pie chart showing dataset count per domain.
+
+    Uses dataset_properties.csv for domain info, with display_domain mapping.
+    Returns None if plotly is unavailable or no data.
+    """
+    go = _get_plotly()
+    if go is None:
+        return None
+
+    props_path = Path(root_dir) / "dataset_properties.csv"
+    if not props_path.exists():
+        return None
+
+    try:
+        df = pd.read_csv(props_path)
+    except Exception:
+        return None
+
+    if df.empty or "domain" not in df.columns:
+        return None
+
+    df["display_domain"] = df["domain"].map(lambda d: display_domain(d))
+
+    # Build per-domain dataset list for hover text
+    domain_datasets: dict[str, list[str]] = {}
+    for _, row in df.iterrows():
+        dd = row["display_domain"]
+        ds_name = dataset_short_name(str(row.get("dataset", "")))
+        domain_datasets.setdefault(dd, []).append(ds_name)
+
+    labels = list(domain_datasets.keys())
+    values = [len(v) for v in domain_datasets.values()]
+    hover = [", ".join(ds_list) for ds_list in domain_datasets.values()]
+    colors = [DOMAIN_COLORS.get(label, "#94a3b8") for label in labels]
+
+    fig = go.Figure(data=[go.Pie(
+        labels=labels,
+        values=values,
+        hovertext=hover,
+        hoverinfo="label+percent+text",
+        textinfo="label+value",
+        marker=dict(colors=colors),
+        hole=0.35,
+    )])
+    fig.update_layout(
+        title=dict(text="Dataset coverage by domain", font=dict(size=14)),
+        margin=dict(l=20, r=20, t=50, b=20),
+        height=320,
+        paper_bgcolor="rgba(0,0,0,0)",
+        plot_bgcolor="rgba(0,0,0,0)",
+        font=dict(color="black"),
+        legend=dict(orientation="h", yanchor="bottom", y=-0.15, xanchor="center", x=0.5),
+        showlegend=True,
+    )
+    return fig