Update app.py

app.py

@@ -62,18 +62,14 @@ col1, col2 = st.columns([1, 3])
 
 with col1:
     st.subheader("Stock Overview")
-    # Adjust styling approach here
+    # Make sure to convert 'Combined Score' to numeric if it's not already
+    scores_df_sorted['Combined Score'] = pd.to_numeric(scores_df_sorted['Combined Score'], errors='coerce')
+    # Apply color based on 'Combined Score' value
     def color_combined_score(value):
-        """Colors the combined score cell based on its value."""
-        if value > 0:
-            color = 'green'
-        elif value < 0:
-            color = 'red'
-        else:
-            color = 'none'
+        color = 'green' if value > 0 else 'red' if value < 0 else 'none'
         return f'background-color: {color};'
 
-    # Apply the styling function to the 'Combined Score' column only
+    # Use 'Styler' to apply the style function to the 'Combined Score' column
     styled_scores_df = scores_df_sorted.style.applymap(color_combined_score, subset=['Combined Score'])
     st.dataframe(styled_scores_df)
 
@@ -85,15 +81,12 @@ with col2:
             stock_data, info = fetch_stock_data(ticker_symbol)
             comparison, _ = compare_to_index(stock_data, sp500_averages)
             
-            # Display the company name and its ticker symbol
-            st.markdown(f"**{info.get('longName', 'N/A')}** ({ticker_symbol})")
-            
-            # Display the company's business summary
-            st.write(info.get('longBusinessSummary', 'Description not available.'))
+            # Display the company name and ticker symbol
+            st.write(f"**{info.get('longName')}** ({ticker_symbol})")
+            st.write(info.get('longBusinessSummary'))
             
             # Display each financial ratio and its comparison result
             for ratio, status in comparison.items():
-                st.text(f"{ratio}: {status}")
-
+                st.write(f"{ratio}: {status}")