Update app.py

app.py

@@ -223,8 +223,9 @@ def get_normal_and_bible(
 
 
 # -------------------- Plotting ---
+import plotly.graph_objects as go
+
 def plot_name_trends_plotly(df, names, start_year=None, end_year=None, logscale=False):
-    # Filter for selected names
     name_df = df[df["name"].isin(names)]
     if start_year is not None:
         name_df = name_df[name_df["year"] >= start_year]
@@ -234,26 +235,45 @@ def plot_name_trends_plotly(df, names, start_year=None, end_year=None, logscale=
     if name_df.empty:
         raise gr.Error("No data for selected names and year range.")
 
-    # Aggregate by year and name
     agg_df = (
         name_df.groupby(["year", "name"])["count"]
         .sum()
         .reset_index()
     )
 
-    fig = px.line(
-        agg_df,
-        x="year",
-        y="count",
-        color="name",
+    # Build figure manually for better control
+    fig = go.Figure()
+    for name in sorted(agg_df["name"].unique()):
+        sub_df = agg_df[agg_df["name"] == name]
+        if len(sub_df) > 1:
+            fig.add_trace(go.Scatter(
+                x=sub_df["year"],
+                y=sub_df["count"],
+                mode="lines+markers",
+                name=name
+            ))
+        else:
+            # Jessca
+            fig.add_trace(go.Scatter(
+                x=sub_df["year"],
+                y=sub_df["count"],
+                mode="markers",
+                name=name,
+                marker=dict(size=10, symbol="circle"),
+            ))
+
+    fig.update_layout(
         title="Name Usage Over Time",
-        labels={"count": "Count", "year": "Year"},
-        log_y=logscale,
+        xaxis_title="Year",
+        yaxis_title="Count",
+        height=500,
+        yaxis_type="log" if logscale else "linear",
     )
-    fig.update_layout(height=500)
+
     return fig, agg_df
 
 
+
 def plot_from_inputs(name_text, start_year, end_year, logscale):
     names = [n.strip() for n in name_text.split(",") if n.strip()]
     if not names: