Enhance date filtering in init_team_data function of app.py. Updated date range queries to convert date objects to formatted datetime strings, ensuring accurate filtering of game logs. This change improves data consistency and reliability in analysis.

app.py

@@ -86,8 +86,12 @@ with st.sidebar:
 @st.cache_data(ttl = 60)
 def init_team_data(team, win_loss, kill_prediction, death_prediction, start_date, end_date):  
         
+        # Convert date objects to datetime strings in the correct format
+        start_datetime = datetime.combine(start_date, datetime.min.time()).strftime("%Y-%m-%d %H:%M:%S")
+        end_datetime = datetime.combine(end_date, datetime.max.time()).strftime("%Y-%m-%d %H:%M:%S")
+
         collection = db["gamelogs"] 
-        cursor = collection.find({"teamname": team, "date": {"$gte": start_date, "$lte": end_date}})
+        cursor = collection.find({"teamname": team, "date": {"$gte": start_datetime, "$lte": end_datetime}})
     
         raw_display = pd.DataFrame(list(cursor))
         raw_display = raw_display[['playername', 'teamname', 'playername_avg_kill_share_win', 'playername_avg_death_share_win', 'playername_avg_assist_share_win', 'playername_avg_total_cs_win', 'playername_avg_kill_share_loss', 'playername_avg_death_share_loss', 'playername_avg_assist_share_loss', 'playername_avg_total_cs_loss']]