Update app.py

app.py

@@ -4,6 +4,7 @@ from prophet import Prophet
 import pandas as pd
 from datetime import datetime
 import plotly.graph_objects as go
+import plotly.express as px
 
 def download_data(ticker, start_date='2010-01-01'):
     """ 주식 데이터를 다운로드하고 포맷을 조정하는 함수 """
@@ -22,7 +23,7 @@ def predict_future_prices(ticker, periods=1825):
     data = download_data(ticker)
     
     # Prophet 모델 생성 및 학습
-    model = Prophet(daily_seasonality=False, weekly_seasonality=False, yearly_seasonality=True)
+    model = Prophet(daily_seasonality=False, weekly_seasonality=True, yearly_seasonality=True)
     model.fit(data)
     
     # 미래 데이터 프레임 생성 및 예측
@@ -31,11 +32,16 @@ def predict_future_prices(ticker, periods=1825):
     
     # 예측 결과 그래프 생성
     forecast['ds'] = forecast['ds'].dt.strftime('%Y-%m-%d')
-    fig = go.Figure()
-    fig.add_trace(go.Scatter(x=forecast['ds'], y=forecast['yhat'], mode='lines', name='Forecast (Blue)'))
-    fig.add_trace(go.Scatter(x=data['ds'], y=data['y'], mode='lines', name='Actual (Black)', line=dict(color='black')))
+    fig_main = go.Figure()
+    fig_main.add_trace(go.Scatter(x=forecast['ds'], y=forecast['yhat'], mode='lines', name='Forecast (Blue)'))
+    fig_main.add_trace(go.Scatter(x=data['ds'], y=data['y'], mode='lines', name='Actual (Black)', line=dict(color='black')))
     
-    return fig, forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']]
+    # 연간 및 주간 계절성 그래프 생성
+    fig_seasonal = model.plot_components(forecast)
+    fig_yearly = px.line(x=pd.to_datetime(fig_seasonal[0]['ds']), y=fig_seasonal[0]['yearly'], labels={'x': 'Date', 'y': 'Yearly Trend'})
+    fig_weekly = px.line(x=fig_seasonal[1]['day'], y=fig_seasonal[1]['weekly'], labels={'x': 'Day of Week', 'y': 'Weekly Trend'})
+    
+    return fig_main, forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']], fig_yearly, fig_weekly
 
 # Gradio 인터페이스 설정 및 실행
 with gr.Blocks() as app:
@@ -46,11 +52,13 @@ with gr.Blocks() as app:
         
     forecast_chart = gr.Plot(label="Forecast Chart")
     forecast_data = gr.Dataframe(label="Forecast Data")
+    yearly_chart = gr.Plot(label="Yearly (Monthly) Trend Chart")
+    weekly_chart = gr.Plot(label="Weekly Trend Chart")
     
     forecast_button.click(
         fn=predict_future_prices,
         inputs=[ticker_input, periods_input],
-        outputs=[forecast_chart, forecast_data]
+        outputs=[forecast_chart, forecast_data, yearly_chart, weekly_chart]
     )
 
 app.launch()