Refactor init_team_data function in app.py to enhance clarity and streamline table handling. Replaced count_var with a loop to iterate through data tables, improving readability and organization of statistical calculations for team performance metrics. This change contributes to better structure and understanding of kills, deaths, assists, and total CS analysis.

app.py

@@ -116,8 +116,10 @@ def init_team_data(team, opponent, win_loss, kill_prediction, death_prediction,
         cursor = collection.find({"Opponent": opponent, "date": {"$gte": start_datetime, "$lte": end_datetime}})
         raw_opponent = pd.DataFrame(list(cursor))
 
-        for tables in [raw_display, raw_opponent]:
-            count_var = 'raw_display' if tables == raw_display else 'raw_opponent'
+        tables_to_loop = [raw_display, raw_opponent]
+
+        for loop in range(len(tables_to_loop)):
+            tables = tables_to_loop[loop]
             calc_columns = ['kills', 'deaths', 'assists', 'total_cs']
             league_win_stats = {}
             league_loss_stats = {}
@@ -264,7 +266,7 @@ def init_team_data(team, opponent, win_loss, kill_prediction, death_prediction,
             tables['playername_avg_assist_share_loss'] = tables['playername_avg_assists_loss'] / tables['teamname_avg_kills_loss']
             tables['playername_avg_cs_share_loss'] = tables['playername_avg_total_cs_loss'] / tables['teamname_avg_total_cs_loss']
 
-            if count_var == 'raw_display':
+            if loop == 0:
                 player_tables = tables
             else:
                 opp_tables = tables