Update app.py

app.py

@@ -615,10 +615,6 @@ def output_results(start_date, end_date, tickers_string):
     ticker_string_balanced = gr.Textbox("AAPL,JPM,JNJ,PG,KO,MSFT,PFE,VZ,MMM,WMT")
     ticker_string_agressive = gr.Textbox("TSLA,AMZN,NVDA,GOOGL,SHOP,SQ,MRNA,ZM,SNOW,PTON")
     
-    fig_efficient_frontier = gr.Plot(label="Efficient Frontier")
-    fig_corr = gr.Plot(label="Correlation between Stocks")
-    fig_indiv_prices = gr.Plot(label="Price of Individual Stocks")
-    fig_cum_returns = gr.Plot(label="Cumulative Returns of Individual Stocks Starting with $100")
 
 
 
@@ -694,20 +690,20 @@ with gr.Blocks() as demo:
             '''
             
             btn1.click(fn=output_results, inputs=[start_date, end_date, ticker_string_conservative], 
-                      outputs=[fig_cum_returns_optimized, weights_df, fig_efficient_frontier, fig_corr,   \
-                    expected_annual_return, annual_volatility, sharpe_ratio, fig_indiv_prices, fig_cum_returns])
+                      outputs=[fig_cum_returns_optimized, weights_df,   \
+                    expected_annual_return, annual_volatility, sharpe_ratio])
 
             btn2.click(fn=output_results, inputs=[start_date, end_date, ticker_string_growth], 
-                      outputs=[fig_cum_returns_optimized, weights_df, fig_efficient_frontier, fig_corr,   \
-                    expected_annual_return, annual_volatility, sharpe_ratio, fig_indiv_prices, fig_cum_returns])
+                      outputs=[fig_cum_returns_optimized, weights_df,   \
+                    expected_annual_return, annual_volatility, sharpe_ratio])
 
             btn3.click(fn=output_results, inputs=[start_date, end_date, ticker_string_balanced], 
-                      outputs=[fig_cum_returns_optimized, weights_df, fig_efficient_frontier, fig_corr,   \
-                    expected_annual_return, annual_volatility, sharpe_ratio, fig_indiv_prices, fig_cum_returns])
+                      outputs=[fig_cum_returns_optimized, weights_df,   \
+                    expected_annual_return, annual_volatility, sharpe_ratio])
             
             btn4.click(fn=output_results, inputs=[start_date, end_date, ticker_string_agressive], 
-                      outputs=[fig_cum_returns_optimized, weights_df, fig_efficient_frontier, fig_corr,   \
-                    expected_annual_return, annual_volatility, sharpe_ratio, fig_indiv_prices, fig_cum_returns])            
+                      outputs=[fig_cum_returns_optimized, weights_df,   \
+                    expected_annual_return, annual_volatility, sharpe_ratio])            
            
 
     with gr.Tab("Step 3: Portfolio Analysis"):