Enhance player data display in app.py by pivoting statistics for improved clarity. Introduced a pivot table to reorganize player metrics, ensuring percentiles are displayed in the correct order. Updated the background gradient direction for better visual representation, enhancing user experience in analyzing player performance.

app.py

@@ -358,8 +358,14 @@ if st.button("Run"):
     for player, tab in zip(unique_players, player_tabs):
         with tab:
             player_data = sim_df[sim_df['Player'] == player]
+            # Pivot the table to make Stats the columns
+            pivoted_data = player_data.pivot(columns='Stat', values=['10%', '25%', '50%', '75%', '90%'])
+            # Reorder the index to match the original percentile order
+            pivoted_data = pivoted_data.reindex(['10%', '25%', '50%', '75%', '90%'])
             st.dataframe(
-                player_data[['Stat', '10%', '25%', '50%', '75%', '90%']]
-                .style.background_gradient(axis=1).background_gradient(cmap='RdYlGn').format(precision=2),
+                pivoted_data
+                .style.background_gradient(axis=0)
+                .background_gradient(cmap='RdYlGn')
+                .format(precision=2),
                 use_container_width=True
             )