Update app.py

app.py

@@ -47,8 +47,8 @@ def analyze_stocks(stocks_filepath, index_symbol, years=5):
     start_date = end_date - timedelta(days=365 * years)
 
     stock_symbols_df = pd.read_csv(stocks_filepath)
-    # Filter out USD Cash and GBP Cash
-    stock_symbols_df = stock_symbols_df[~stock_symbols_df['Name'].isin(['USD Cash', 'GBP Cash'])]
+    # Filter out USD and GBP
+    stock_symbols_df = stock_symbols_df[~stock_symbols_df['Symbol'].isin(['USD', 'GBP'])]
     stock_symbols = stock_symbols_df['Symbol'].tolist()
 
     index_data = fetch_data(index_symbol, start_date, end_date)
@@ -118,9 +118,9 @@ def analyze_stocks(stocks_filepath, index_symbol, years=5):
         traces.append(trace)
 
     layout = go.Layout(title=f'S&P500 Index Stock Clustering based on Beta and R-Squared',
-                       xaxis=dict(title='β (Risk)', tickmode='linear', dtick=0.25),
+                       xaxis=dict(title='β (Risk)', tickmode='linear', dtick=0.25, range=[0, 3.5]),
                        yaxis=dict(title='R² (Market Dependency)'),
-                       width=1000,
+                       width=1200,
                        height=800)
 
     fig = go.Figure(data=traces, layout=layout)
@@ -131,7 +131,7 @@ def analyze_stocks(stocks_filepath, index_symbol, years=5):
                              mode="lines", line=dict(color="black", width=2), showlegend=False))
 
     latest_date = end_date.strftime('%d/%m/%Y')
-    fig.add_annotation(x=results_df['Beta'].max(), y=results_df['R-Squared'].max(),
+    fig.add_annotation(x=3.4, y=results_df['R-Squared'].max(),
                        text=f"Valid Stocks: {valid_stocks_count} | Date: {latest_date}",
                        showarrow=False, font=dict(size=14, color="black"))
 
@@ -164,7 +164,7 @@ with gr.Blocks() as iface:
     <style>
     #large-plot {
         height: 800px !important;
-        width: 100% !important;
+        width: 1200px !important;
     }
     </style>
     """)