Update app.py

app.py

@@ -672,7 +672,7 @@ with gr.Blocks() as demo:
                 fig_cum_returns_optimized = gr.Plot(label="Cumulative Returns of Optimized Portfolio (Starting Price of $100)")
                 weights_df = gr.DataFrame(label="Optimized Weights of Each Ticker")
 
-            '''    
+           
             with gr.Row():
                 fig_efficient_frontier = gr.Plot(label="Efficient Frontier")
                 fig_corr = gr.Plot(label="Correlation between Stocks")
@@ -681,7 +681,7 @@ with gr.Blocks() as demo:
                 fig_indiv_prices = gr.Plot(label="Price of Individual Stocks")
                 fig_cum_returns = gr.Plot(label="Cumulative Returns of Individual Stocks Starting with $100")
 
-            '''
+           
 
             '''
             btn.click(fn=output_results, inputs=[start_date, end_date, ticker_string], 
@@ -690,20 +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,   \
-                    expected_annual_return, annual_volatility, sharpe_ratio])
+                   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])
 
             btn2.click(fn=output_results, inputs=[start_date, end_date, ticker_string_growth], 
-                      outputs=[fig_cum_returns_optimized, weights_df,   \
-                    expected_annual_return, annual_volatility, sharpe_ratio])
+                  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])
 
             btn3.click(fn=output_results, inputs=[start_date, end_date, ticker_string_balanced], 
-                      outputs=[fig_cum_returns_optimized, weights_df,   \
-                    expected_annual_return, annual_volatility, sharpe_ratio])
+                  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])
             
             btn4.click(fn=output_results, inputs=[start_date, end_date, ticker_string_agressive], 
-                      outputs=[fig_cum_returns_optimized, weights_df,   \
-                    expected_annual_return, annual_volatility, sharpe_ratio])            
+                  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])       
            
 
     with gr.Tab("Step 3: Portfolio Analysis"):