Refactor app.py to streamline player data processing by utilizing session state for game data and cleaning player names. This change enhances data management and ensures consistent access to player statistics, improving overall performance during simulations.

app.py

@@ -614,20 +614,20 @@ if st.button("Run"):
     st.session_state.player_summary = pd.DataFrame()
     
     for game_num in range(game_count):
-        game_df = st.session_state.results_dict[f'game {game_num + 1}']  # Use correct dictionary key format
+        st.session_state.game_df = st.session_state.results_dict[f'game {game_num + 1}']  # Use correct dictionary key format
         # Remove 'game X' from playernames if present
-        clean_df = game_df.copy()
-        clean_df['playername'] = clean_df['playername'].str.split(' game ').str[0]
+        st.session_state.clean_df = st.session_state.game_df.copy()
+        st.session_state.clean_df['playername'] = st.session_state.clean_df['playername'].str.split(' game ').str[0]
         
         if st.session_state.player_summary.empty:
-            st.session_state.player_summary = clean_df
+            st.session_state.player_summary = st.session_state.clean_df
         else:
             # Add the stats to existing players
             for col in ['Kill_Proj', 'Death_Proj', 'Assist_Proj', 'CS_Proj']:
-                st.session_state.player_summary[col] += clean_df[col]
+                st.session_state.player_summary[col] += st.session_state.clean_df[col]
             # Update teamname and position if needed
-            st.session_state.player_summary['teamname'].update(clean_df['teamname'])
-            st.session_state.player_summary['position'].update(clean_df['position'])
+            st.session_state.player_summary['teamname'].update(st.session_state.clean_df['teamname'])
+            st.session_state.player_summary['position'].update(st.session_state.clean_df['position'])
     
     st.session_state.player_summary = st.session_state.player_summary.set_index('playername')