Update app.py

app.py

@@ -179,30 +179,6 @@ def plot_combined_signals(df, ticker):
 
     return fig
 
-# %%
-def stock_analysis(ticker, start_date, end_date):
-    # Download stock data from Yahoo Finance
-    df = yf.download(ticker, start=start_date, end=end_date)
-
-    # If the DataFrame has a MultiIndex for columns, drop the 'Ticker' level
-    if isinstance(df.columns, pd.MultiIndex):
-        df.columns = df.columns.droplevel(level=1)  # Drop the 'Ticker' level
-
-    # Explicitly set column names (optional)
-    df.columns = ['Close', 'High', 'Low', 'Open', 'Volume']
-
-    
-    # Generate signals
-    generate_trading_signals(df)
-    
-    # Last 60 days
-    df_last_60 = df.tail(360)
-    
-    # Plot signals
-    fig_signals = plot_combined_signals(df_last_60, ticker)
-    
-    return fig_signals
-
 
 
 
@@ -229,7 +205,7 @@ def plot_individual_signals(df, ticker):
         fig.add_trace(go.Scatter(
             x=buy_signals.index, y=buy_signals['Close'], 
             mode='markers', 
-            marker=dict(symbol='triangle-up', size=10, color='darkblue'), 
+            marker=dict(symbol='triangle-up', size=10, color='blackblue'), 
             name=f'{signal} Buy Signal'
         ))
 
@@ -269,46 +245,45 @@ def display_signals(df):
 
     return signals_df
 
+# Define the stock analysis function (keep only one version)
 def stock_analysis(ticker, start_date, end_date):
     # Download stock data from Yahoo Finance
     df = yf.download(ticker, start=start_date, end=end_date)
 
-    # If the DataFrame has a MultiIndex for columns, drop the 'Ticker' level
+    # If the DataFrame has a MultiIndex for columns, handle it
     if isinstance(df.columns, pd.MultiIndex):
-        df.columns = df.columns.droplevel(level=1)  # Drop the 'Ticker' level
-
-    # Explicitly set column names (optional)
-    df.columns = ['Close', 'High', 'Low', 'Open', 'Volume']
-
+        df.columns = df.columns.droplevel(1)
+    
     # Generate signals
     df = generate_trading_signals(df)
     
-    # Last 60 days for plotting
-    df_last_60 = df.tail(360)
+    # Last 360 days for plotting
+    df_last_360 = df.tail(360)
 
     # Plot combined signals
-    # fig_signals = plot_combined_signals(df_last_60, ticker)
-
+    fig_signals = plot_combined_signals(df_last_360, ticker)
+    
     # Plot individual signals
-    fig_individual_signals = plot_individual_signals(df_last_60, ticker)
-
-    # Display signals DataFrame
-    signals_df = df_last_60[['Close', 'SMA_Signal', 'MACD_Signal', 'RSI_Signal', 'BB_Signal', 
-                              'Stochastic_Signal','CMF_Signal', 
-                              'CCI_Signal']]
-
-    return fig_individual_signals
+    fig_individual_signals = plot_individual_signals(df_last_360, ticker)
 
+    # Create signals DataFrame for display
+    signals_df = df_last_360[['Close', 'SMA_Signal', 'MACD_Signal', 'RSI_Signal', 
+                             'BB_Signal', 'Stochastic_Signal', 'CMF_Signal', 
+                             'CCI_Signal']].copy()
+    
+    # Format signals for display
+    for column in signals_df.columns[1:]:  # Skip 'Close'
+        signals_df[column] = signals_df[column].replace({1: 'Buy', -1: 'Sell', 0: 'Hold'})
 
+    return fig_individual_signals, signals_df
 
-# %%
 # Define Gradio interface
 with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
     gr.Markdown("## 360 Stock Market Analysis")
 
     ticker_input = gr.Textbox(label="Enter Stock Ticker (e.g., AAPL, NVDA)", value="NVDA")
     start_date_input = gr.Textbox(label="Start Date (YYYY-MM-DD)", value="2022-01-01")
-    end_date_input = gr.Textbox(label="End Date (YYYY-MM-DD)", value="2026-01-01")
+    end_date_input = gr.Textbox(label="End Date (YYYY-MM-DD)", value="2023-01-01")  # Fixed end date
 
     # Create a submit button that runs the stock analysis function
     button = gr.Button("Analyze Stock")
@@ -317,10 +292,10 @@ with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
     individual_signals_output = gr.Plot(label="Trading Signals")
     signals_df_output = gr.Dataframe(label="Buy/Sell Signals")
 
-    # Link button to function
-    button.click(stock_analysis, inputs=[ticker_input, start_date_input, end_date_input], 
-                  outputs=[individual_signals_output,signals_df_output])
+    # Link button to function with both outputs
+    button.click(stock_analysis, 
+                inputs=[ticker_input, start_date_input, end_date_input], 
+                outputs=[individual_signals_output,signals_df_output])
 
 # Launch the interface
 demo.launch()
-