Update app.py

app.py

@@ -7,7 +7,7 @@ import contextlib
 import requests
 import random
 from functools import lru_cache
-import matplotlib.pyplot as plt
+import plotly.express as px
 
 FORBIDDEN_NAMES ={"Judas",
                   "Judas Iscariot"
@@ -52,29 +52,6 @@ FORBIDDEN_NAMES ={"Judas",
                   "Pontius Pilate"
                  }
 
-# ----------------------------- Plotting
-
-
-def plot_name_trends(df, names, start_year=None, end_year=None, logscale=False):
-    name_df = df[df["name"].isin(names)]
-    if start_year is not None:
-        name_df = name_df[name_df["year"] >= start_year]
-    if end_year is not None:
-        name_df = name_df[name_df["year"] <= end_year]
-
-    pivot = name_df.pivot_table(index="year", columns="name", values="count", aggfunc="sum", fill_value=0)
-
-    fig, ax = plt.subplots(figsize=(12, 6))
-    pivot.plot(ax=ax)
-    ax.set_title("Name Usage Over Time")
-    ax.set_xlabel("Year")
-    ax.set_ylabel("Count")
-    if logscale:
-        ax.set_yscale("log")
-    ax.grid(True)
-    ax.legend(title="Name")
-    fig.tight_layout()
-    return fig
 
 
 # --- File download & setup ---
@@ -243,6 +220,47 @@ def get_normal_and_bible(
 
     return ssa_name, bible_name
 
+
+
+# -------------------- Plotting ---
+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]
+    if end_year is not None:
+        name_df = name_df[name_df["year"] <= end_year]
+
+    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",
+        title="Name Usage Over Time",
+        labels={"count": "Count", "year": "Year"},
+        log_y=logscale,
+    )
+    fig.update_layout(height=500)
+    return fig
+
+
+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:
+        raise gr.Error("Please enter at least one name.")
+    full_df = load_all_ssa_names()
+    return plot_name_trends_plotly(full_df, names, start_year, end_year, logscale)    
+
 # --- Gradio app ---
 def generate_names(n, sex, ssa_min_len, ssa_max_len, 
                    ssa_min_year,
@@ -350,13 +368,6 @@ with gr.Blocks() as demo:
             plot_button = gr.Button("📊 Plot Trends")
             plot_output = gr.Plot(label="Trend Plot")
 
-            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:
-                    raise gr.Error("Please enter at least one name.")
-                full_df = load_all_ssa_names()
-                return plot_name_trends(full_df, names, start_year, end_year, logscale)
-
             plot_button.click(
                 fn=plot_from_inputs,
                 inputs=[trend_names_input, trend_start_year, trend_end_year, trend_logscale],