Add ROI coloring function and update dataframe display in app.py

- Introduced a new function, color_roi, to apply conditional formatting to ROI values based on their performance (green for >100%, red for <100%, yellow for =100%).
- Updated the dataframe display in the Contest Analysis tab to utilize the new color_roi function for enhanced visualization of ROI metrics.

app.py

@@ -117,6 +117,17 @@ def get_payout_for_position(finish_pos, payout_df):
     else:
         return 0  # Default value if no match found
 
+def color_roi(val):
+    """Color ROI values: green if > 100%, red if < 100%"""
+    if pd.isna(val):
+        return ''
+    if val > 1.0:  # Greater than 100%
+        return 'background-color: lightgreen'
+    elif val < 1.0:  # Less than 100%
+        return 'background-color: lightcoral'
+    else:  # Exactly 100%
+        return 'background-color: lightyellow'
+
 db = init_conn()
 
 ## import global functions for usages
@@ -941,8 +952,9 @@ if selected_tab == 'Contest Analysis':
                     end_ROI_idx = min((st.session_state.ROI_page) * rows_per_page, total_rows)
 
                     st.dataframe(st.session_state['ROI_frame'].iloc[start_ROI_idx:end_ROI_idx].style.
-                            background_gradient(cmap='RdYlGn', subset=['ROI', 'Total Fees', 'Total Payout'], axis=0).
-                            background_gradient(cmap='RdYlGn', subset=['EntryCount', 'Total Fees'], axis=0).
+                            applymap(color_roi, subset=['ROI']).
+                            background_gradient(cmap='RdYlGn', subset=['Total Fees', 'Total Payout'], axis=0).
+                            background_gradient(cmap='RdYlGn', subset=['EntryCount'], axis=0).
                             format(roi_format, precision=2), hide_index=True)
                     st.download_button(label="Download ROI Info", data=st.session_state['ROI_frame'].to_csv(index=False), file_name="ROI_info.csv", mime="text/csv", key='ROI_exp_comp_download')
                 else: