Update app.py

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 import pandas as pd
 import numpy as np
-import plotly.express as px
+import plotly.graph_objects as go
 
 def calculate_schedule(
     principal: float,
@@ -65,22 +65,38 @@ def calculate_schedule(
     df = pd.DataFrame(schedule).round(2)
     df["Interest Increment (RMB)"] = df["Interest Earned (RMB)"].diff().fillna(0).round(2)
 
-    # 绘图
-    fig = px.line(
-        df,
-        x=display_freq,
-        y="Future Value (RMB)",
+    # 绘制未来价值折线图
+    fig_line = go.Figure()
+    fig_line.add_trace(go.Scatter(
+        x=df[display_freq],
+        y=df["Future Value (RMB)"],
+        mode='lines+markers',
+        name='Future Value',
+        line=dict(color='blue')
+    ))
+    fig_line.update_layout(
         title=f"Compound Growth over Time ({display_freq})",
+        xaxis_title=display_freq,
+        yaxis_title="Future Value (RMB)",
         template="plotly_white"
     )
-    fig.update_traces(mode="lines+markers")
-    fig.update_layout(
-        title_font_size=20,
+
+    # 绘制利息增量柱状图
+    fig_bar = go.Figure()
+    fig_bar.add_trace(go.Bar(
+        x=df[display_freq],
+        y=df["Interest Increment (RMB)"],
+        name='Interest Increment',
+        marker_color='orange'
+    ))
+    fig_bar.update_layout(
+        title=f"Interest Increment per {display_freq}",
         xaxis_title=display_freq,
-        yaxis_title="Future Value (RMB)"
+        yaxis_title="Interest Increment (RMB)",
+        template="plotly_white"
     )
 
-    return df, fig
+    return df, fig_line, fig_bar
 
 with gr.Blocks() as demo:
     gr.Markdown("## 复利计算器\n填写参数后点击“计算”查看结果")
@@ -101,6 +117,7 @@ with gr.Blocks() as demo:
 
     result_table = gr.Dataframe(interactive=False)
     result_plot  = gr.Plot()
+    interest_plot = gr.Plot()
 
     compute_btn.click(
         fn=calculate_schedule,
@@ -109,7 +126,7 @@ with gr.Blocks() as demo:
             compounding, deposit_freq, display_freq,
             years, stop_deposit_year
         ],
-        outputs=[result_table, result_plot]
+        outputs=[result_table, result_plot, interest_plot]
     )
 
     demo.launch()