Update app.py

app.py

@@ -16,6 +16,7 @@ from matplotlib.ticker import MaxNLocator
 import matplotlib.font_manager as font_manager
 import numpy as np
 
+
 # team_games_df = pd.read_csv('data/team_games_all.csv',index_col=[0])
 # player_games_df = pd.read_csv('data/player_games_cards.csv',index_col=[0]).sort_values(by='date').reset_index(drop=True)
 team_abv_nst = pd.read_csv('data/team_abv_nst.csv')
@@ -24,6 +25,7 @@ team_abv_nst = pd.read_csv('data/team_abv_nst.csv')
 #team_games_df = team_games_df.merge(right=team_abv,left_on='team',right_on='team_name',how='left').drop(columns='team_name')
 team_abv = pd.read_csv('data/team_abv.csv')
 
+ 
 import pickle
 from datetime import timedelta
 
@@ -31,33 +33,42 @@ from datetime import timedelta
 # r = requests.get('https://statsapi.web.nhl.com/api/v1/schedule?startDate=2022-10-01&endDate=2023-06-01')
 # schedule = r.json()
 
-schedule = json.loads(urlopen('https://statsapi.web.nhl.com/api/v1/schedule?startDate=2023-10-07&endDate=2024-04-19').read())
-
-def flatten(t):
-    return [item for sublist in t for item in sublist]
-
-game_id = flatten([[x['gamePk'] for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
-game_type = flatten([[x['gameType'] for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
-game_date = flatten([[(pd.to_datetime(x['gameDate']) - timedelta(hours=8)) for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
-game_final = flatten([[x['status']['detailedState'] for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
-game_home = flatten([[x['teams']['home']['team']['name'] for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
-game_away = flatten([[x['teams']['away']['team']['name'] for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
-
-schedule_df = pd.DataFrame(data={'game_id': game_id, 'game_type':game_type,'game_date' : game_date, 'game_home' : game_home, 'game_away' : game_away,'status' : game_final})
-schedule_df = schedule_df[schedule_df.game_type == 'R'].reset_index(drop=True)
-schedule_df = schedule_df[schedule_df.status != 'Postponed']
-schedule_df = schedule_df.replace('Montréal Canadiens','Montreal Canadiens')
-
-
-
+# schedule = json.loads(urlopen('https://statsapi.web.nhl.com/api/v1/schedule?startDate=2023-10-07&endDate=2024-04-19').read())
+
+# def flatten(t):
+#     return [item for sublist in t for item in sublist]
+ 
+# game_id = flatten([[x['gamePk'] for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
+# game_type = flatten([[x['gameType'] for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
+# game_date = flatten([[(pd.to_datetime(x['gameDate']) - timedelta(hours=8)) for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
+# game_final = flatten([[x['status']['detailedState'] for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
+# game_home = flatten([[x['teams']['home']['team']['name'] for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
+# game_away = flatten([[x['teams']['away']['team']['name'] for x in schedule['dates'][y]['games']] for y in range(0,len(schedule['dates']))])
+ 
+# schedule_df = pd.DataFrame(data={'game_id': game_id, 'game_type':game_type,'game_date' : game_date, 'game_home' : game_home, 'game_away' : game_away,'status' : game_final})
+# schedule_df = schedule_df[schedule_df.game_type == 'R'].reset_index(drop=True)
+# schedule_df = schedule_df[schedule_df.status != 'Postponed']
+# schedule_df = schedule_df.replace('Montréal Canadiens','Montreal Canadiens')
+schedule = pd.read_csv('2024_schedule_href.csv')
+#schedule = pd.read_html('https://www.hockey-reference.com/leagues/NHL_2024_games.html')[0]
+   #schedule.to_csv('schedule/schedule_'+str(date.today())+'.csv')
+#schedule = pd.read_csv('schedule/schedule_'+str(date.today())+'.csv')
+schedule = schedule.replace('St Louis Blues','St. Louis Blues')
+
+ 
+schedule_df = schedule.merge(right=team_abv,left_on='Visitor',right_on='team_name',how='inner',suffixes=['','_away']) 
+schedule_df = schedule_df.merge(right=team_abv,left_on='Home',right_on='team_name',how='inner',suffixes=['','_home']) 
+
+schedule_df = schedule_df.rename(columns={'Visitor':'game_away','Home':'game_home','Date':'game_date'}) 
+
+ 
 schedule_df_merge = schedule_df.merge(right=team_abv,left_on='game_home',right_on='team_name',how='left')
 schedule_df_merge = schedule_df_merge.merge(right=team_abv,left_on='game_away',right_on='team_name',how='left')
 schedule_df_merge = schedule_df_merge.drop(columns={'team_name_x','team_name_y'})
 schedule_df_merge = schedule_df_merge.rename(columns={'team_abv_x' : 'team_abv_home','team_abv_y' : 'team_abv_away'})
 
-
-
-
+ 
+schedule_df_merge = schedule_df_merge.loc[:,~schedule_df_merge.columns.duplicated()].copy()
 #schedule_df_merge.game_date = pd.to_datetime(schedule_df_merge['game_date']).dt.tz_convert(tz='US/Eastern').dt.date
 # schedule_df_merge = schedule_df_merge.set_index(pd.DatetimeIndex(schedule_df_merge.game_date).strftime('%Y-%m-%d'))
 schedule_df_merge.index = pd.to_datetime(schedule_df_merge.game_date)
@@ -67,16 +78,16 @@ schedule_df_merge.index = schedule_df_merge.index.date
 schedule_df_merge = schedule_df_merge.sort_index()
 schedule_df_merge = schedule_df_merge[schedule_df_merge.index <= date(2024,5,1)]
 
-schedule_df_merge_final = schedule_df_merge[schedule_df_merge['status']=='Final']
+schedule_df_merge_final = schedule_df_merge[schedule_df_merge.index<date.today()]
 schedule_ccount_df = pd.DataFrame(data={'date':list(schedule_df_merge_final.index)*2,'team':list(schedule_df_merge_final.team_abv_away)+list(schedule_df_merge_final.team_abv_home)}).sort_values(by='date').reset_index(drop=True)
 schedule_ccount_df['team_game'] = schedule_ccount_df.groupby('team').cumcount()+1
 schedule_ccount_df.date = pd.to_datetime(schedule_ccount_df.date)
-
+ 
 today = pd.to_datetime(datetime.now(pytz.timezone('US/Pacific')).strftime('%Y-%m-%d'))
 team_schdule = schedule_df_merge[(schedule_df_merge['team_abv_home']=='EDM')|(schedule_df_merge['team_abv_away']=='EDM')]
 team_schdule_live = team_schdule[team_schdule.index <= today]
 team_schdule_live.head()
-
+ 
 team_games_df = pd.read_csv('data/team_games_all.csv',index_col=[0])
 player_games_df = pd.read_csv('data/player_games_cards.csv',index_col=[0]).sort_values(by='date').reset_index(drop=True)
 team_abv_df = pd.read_csv('data/team_abv.csv')
@@ -86,34 +97,38 @@ team_games_df = team_games_df.merge(right=team_abv_df,left_on='team',right_on='t
 
 player_games_df = player_games_df.drop_duplicates(subset=['player_id','date'],keep='last').reset_index(drop=True)
 player_games_df.date = pd.to_datetime(player_games_df.date)
-team_games_df = team_games_df[team_games_df['date']=='Final']
-schedule_df_merge_final = schedule_df_merge[schedule_df_merge['status']=='Final']
+
+team_games_df['date'] = pd.to_datetime(team_games_df['date']).dt.date
+team_games_df = team_games_df[team_games_df['date']<date.today()]
+
+#schedule_df_merge_final = schedule_df_merge[schedule_df_merge['status']=='Final']
 schedule_ccount_df = pd.DataFrame(data={'date':list(schedule_df_merge_final.index)*2,'team':list(schedule_df_merge_final.team_abv_away)+list(schedule_df_merge_final.team_abv_home)}).sort_values(by='date').reset_index(drop=True)
 schedule_ccount_df['team_game'] = schedule_ccount_df.groupby('team').cumcount()+1
 schedule_ccount_df.date = pd.to_datetime(schedule_ccount_df.date)
 team_games_df['team_game'] = team_games_df.groupby('team').cumcount()+1
 player_games_df = player_games_df.merge(right=schedule_ccount_df,left_on=['Team','date'],right_on=['team','date'],how='left')
 player_games_df['player_game'] = player_games_df.groupby('player_id').cumcount()+1
-
+ 
 date_range_list = pd.date_range(start=player_games_df.date.min()+timedelta(days=6),end=player_games_df.date.max())
 
-
 team_abv_nst_dict = {'All':''} | team_abv_nst.set_index('team_abv')['team_name'].to_dict()
 
 position_dict = {'All':'','F':'Forwards','D':'Defense'}
-
+ 
+player_games_df.player_id = player_games_df.player_id.astype(int)
 player_games_df = player_games_df.rename(columns={'Total Points_pp':'PP Points'})
 
 stat_input_list = ['TOI', 'Goals', 'Total Assists',
        'First Assists',  'Total Points', 'PP Points','Shots', 'Hits',
         'Shots Blocked']
-
+ 
 
 df_cum_stat_total = player_games_df.groupby(['player_id','Player','Position']).agg(
     GP = ('GP','count'),
-    Total_Points = ('Total Points','sum')
+   Total_Points = ('Total Points','sum')
         ).reset_index()
 
+ 
 df_all_sort = df_cum_stat_total.copy()
 stat_pick = 'Total_Points'
 count=11
@@ -169,7 +184,7 @@ import matplotlib.image as mpimg
 app_ui = ui.page_fluid(
     #shinyswatch.theme.cosmo(),
     ui.layout_sidebar(
-    
+     
     # Available themes:
     #  cerulean, cosmo, cyborg, darkly, flatly, journal, litera, lumen, lux,
     #  materia, minty, morph, pulse, quartz, sandstone, simplex, sketchy, slate,
@@ -204,35 +219,35 @@ app_ui = ui.page_fluid(
         #                 ui.input_date("x", "Date input"),),
         #         ui.column(
         #             1,
-        #             ui.input_select("level_id", "Select Level",level_dict,width=1)),
-        #         ui.column(
-        #             3,
-        #             ui.input_select("stat_id", "Select Stat",plot_dict_small,width=1)),
-        #         ui.column(
-        #             2,
-        #             ui.input_numeric("n", "Rolling Window Size", value=50)),
-        #         ),
-        #             ui.output_table("result_batters")),
-
-                # ui.nav(
-                #     "Pitchers",
-
-                #                 ui.row(
-                # ui.column(
-                #     3,
-                #     ui.input_select("id_pitch", "Select Pitcher",pitcher_dict,width=1,selected=675911),
-                #     ),
-                # ui.column(
-                #     1,
-                #     ui.input_select("level_id_pitch", "Select Level",level_dict,width=1)),
-                # ui.column(
-                #     3,
-                #     ui.input_select("stat_id_pitch", "Select Stat",plot_dict_small_pitch,width=1)),
-                # ui.column(
-                #     2,
-                #         ui.input_numeric("n_pitch", "Rolling Window Size", value=50)),
-                # ),
-                #     ui.output_table("result_pitchers")),
+#             ui.input_select("level_id", "Select Level",level_dict,width=1)),
+#         ui.column(
+#             3,
+#             ui.input_select("stat_id", "Select Stat",plot_dict_small,width=1)),
+#         ui.column(
+#             2,
+#             ui.input_numeric("n", "Rolling Window Size", value=50)),
+#         ),
+#             ui.output_table("result_batters")),
+
+        # ui.nav(
+        #     "Pitchers",
+
+        #                 ui.row(
+        # ui.column(
+        #     3,
+        #     ui.input_select("id_pitch", "Select Pitcher",pitcher_dict,width=1,selected=675911),
+        #     ),
+        # ui.column(
+        #     1,
+        #     ui.input_select("level_id_pitch", "Select Level",level_dict,width=1)),
+        # ui.column(
+        #     3,
+        #     ui.input_select("stat_id_pitch", "Select Stat",plot_dict_small_pitch,width=1)),
+        # ui.column(
+        #     2,
+        #         ui.input_numeric("n_pitch", "Rolling Window Size", value=50)),
+        # ),
+        #     ui.output_table("result_pitchers")),
 #             )
 #         )
 # )
@@ -246,29 +261,28 @@ app_ui = ui.page_fluid(
 
 
 
-
 def server(input, output, session):
 
 
     @reactive.Effect
     def _():
-        
 
+        
         team_select_list = [input.team_select()]    
         position_select_list =  [input.position_select()]    
-
+        
         if team_select_list[0] == 'All':
             team_select_list = team_abv_nst.team_abv.unique()
-
+        
         if position_select_list[0] == 'All':
             position_select_list = player_games_df.Position.unique()     
-
+        
         elif position_select_list[0] == 'F':
             position_select_list = player_games_df[player_games_df.Position != 'D'].Position.unique()     
 
         else:
             position_select_list = ['D'] 
-        
+
         print(team_select_list)
 
 
@@ -289,7 +303,7 @@ def server(input, output, session):
                 GP = ('GP','count'),
                 Total_Points = (f'{input.stat()}','sum')
                     ).reset_index()
-
+        
         df_all_sort = df_cum_stat_total.copy()
         stat_pick = 'Total_Points'
         count=6
@@ -307,195 +321,192 @@ def server(input, output, session):
         temp_df['temp'] =  temp_df[stat_pick+' per game Rank'].rank()#.sort_values(ascending=True)#.reset_index(drop=True)
         temp_df = temp_df.sort_values(by='temp',ascending=True)#.reset_index(drop=True)
         temp = temp_df[temp_df['temp']<=(count-len(df_all_sort_list))]
-
+        
         players_list_new = list(pd.concat([df_all_sort_list,temp]).reset_index(drop=True)['player_id'])
-
-
+        
+        
         skater_dict = df_cum_stat_total.sort_values(by=['Total_Points','GP'],ascending=[False,True]).drop_duplicates(subset='player_id').set_index('player_id')#.sort_values(by='Player')
         #skater_dict['skater_team'] = skater_dict.Player + ' - ' + skater_dict.Team
         skater_dict = skater_dict['Player'].to_dict()
         # players_list = list(df_all_sort['Player'])
-        
+
         ui.update_select(
             "id",
             label="Select Skater (max. 10 Skaters)",
             choices=skater_dict,
             selected=list(players_list_new[0:10]))
-  
-
-    @output
-    @render.table
-    def result():
-        if input.rookie_switch():
-
-            return player_games_df[(player_games_df.date <= pd.to_datetime(input.date()))&(player_games_df.player_id.isin(rookie_list))].groupby(['player_id','Player','Position']).agg(
-                GP = ('GP','count'),
-                Stat = (f'{input.stat()}','sum')
-                    ).reset_index().sort_values(by=['Stat','GP'],ascending=[False,True]).reset_index(drop=True)
-            
-        else:
-            return player_games_df[player_games_df.date <= pd.to_datetime(input.date())].groupby(['player_id','Player','Position']).agg(
-                GP = ('GP','count'),
-                Stat = (f'{input.stat()}','sum')
-                    ).reset_index().sort_values(by=['Stat','GP'],ascending=[False,True]).reset_index(drop=True)
-
-
-    @output
-    @render.plot(alt="A histogram")
-    def plot():
-
-
-        team_select_list = [input.team_select()]    
-        position_select_list =  [input.position_select()]    
-
-
-
-        if team_select_list[0] == 'All':
-            team_select_title = 'NHL '
-        else:
-            team_select_title = f'{team_abv_nst_dict[team_select_list[0]]} '
-            
+         
 
-        if position_select_list[0] == 'All':
-            position_select_title = '' 
+ 
+@output
+@render.table
+def result():
+    if input.rookie_switch():
 
-        elif position_select_list[0] == 'F':
-            position_select_title = 'Forwards '
+        return player_games_df[(player_games_df.date <= pd.to_datetime(input.date()))&(player_games_df.player_id.isin(rookie_list))].groupby(['player_id','Player','Position']).agg(
+            GP = ('GP','count'),
+            Stat = (f'{input.stat()}','sum')
+                ).reset_index().sort_values(by=['Stat','GP'],ascending=[False,True]).reset_index(drop=True)
+        
+    else:
+        return player_games_df[player_games_df.date <= pd.to_datetime(input.date())].groupby(['player_id','Player','Position']).agg(
+            GP = ('GP','count'),
+            Stat = (f'{input.stat()}','sum')
+                ).reset_index().sort_values(by=['Stat','GP'],ascending=[False,True]).reset_index(drop=True)
+    
+ 
+@output
+@render.plot(alt="A histogram")
+def plot():
+ 
+    team_select_list = [input.team_select()]    
+    position_select_list =  [input.position_select()]    
+
+    if team_select_list[0] == 'All':
+        team_select_title = 'NHL '
+    else:
+        team_select_title = f'{team_abv_nst_dict[team_select_list[0]]} '
+        
+    
+    if position_select_list[0] == 'All':
+        position_select_title = '' 
 
-        else:
-            position_select_title = 'Defense '
+    
+    elif position_select_list[0] == 'F':
+        position_select_title = 'Forwards '
 
-        rookie = ''
-        if input.rookie_switch():
-            rookie = 'Rookie '
-            
-        i = 0
-        #rookie = ''
-        current_season = '2023'
-        start_season = '2024'
+    
+    else:
+        position_select_title = 'Defense '
 
-        # player_lookup_list = ['Connor McDavid','David Pastrnak','Nathan MacKinnon']
+    
+    rookie = ''
+    if input.rookie_switch():
+        rookie = 'Rookie '
+        
+    i = 0
+    #rookie = ''
+    current_season = '2023'
+    start_season = '2024'
 
+    
+    # player_lookup_list = ['Connor McDavid','David Pastrnak','Nathan MacKinnon']
 
-        type(input.id())
-        print(input.id())
-        player_lookup_list = list(input.id())[0:10]
+    
+    type(input.id())
+    print(input.id())
+    player_lookup_list = list(input.id())[0:10]
 
+    
+    stat = input.stat()
+    sns.set_theme(style="whitegrid", palette="pastel")
+    #print(type([input.date()))
+    date_range_list = [pd.to_datetime(input.date())]
+    for k in range(len(date_range_list)):
+        print(date_range_list[k])
         stat = input.stat()
-        sns.set_theme(style="whitegrid", palette="pastel")
-        #print(type([input.date()))
-        date_range_list = [pd.to_datetime(input.date())]
-        for k in range(len(date_range_list)):
-            print(date_range_list[k])
-            stat = input.stat()
-            team_schedule_url_merge = []
-            max_games_player = []
-            max_games_team = []
-            max_stat = []
-            per_game = False
-            for i in range(0,len(player_lookup_list)):
-                team_schedule_url_merge.append(player_games_df[(player_games_df.player_id == int(player_lookup_list[i]))&(date_range_list[k] >= player_games_df.date)].reset_index(drop=True))
-                #print('touble',i, player_lookup_list[i],len(player_games_df[(player_games_df.player_id == player_lookup_list[i])]))
-                team_schedule_url_merge[i].index = team_schedule_url_merge[i].team_game
-                team_schedule_url_merge[i] = team_schedule_url_merge[i].reindex(np.arange(team_schedule_url_merge[i].team_game.min(), team_schedule_url_merge[i].team_game.max() + 1)).reset_index(drop=True)
-                #team_schedule_url_merge[0]['team_game'] = team_schedule_url_merge[0]['index']
-                #team_schedule_url_merge[0]['player_game'] = 
-                #schedule_ccount_df[schedule_ccount_df['team'].isin(team_schedule_url_merge[0].Team.unique())].merge(right=team_schedule_url_merge[0],left_on=['date','team'],right_on=['date','Team'],how='left')
-
-                team_schedule_url_merge[i]['stat'] = team_schedule_url_merge[i][stat].cumsum()
-
-
-                #team_schedule_url_merge[i]['stat'] = team_schedule_url_merge[i][stat_pick]
-                team_schedule_url_merge[i] = team_schedule_url_merge[i].append(team_schedule_url_merge[i]).sort_index()
-                team_schedule_url_merge[i] = team_schedule_url_merge[i].append(team_schedule_url_merge[i].iloc[0]).sort_index().reset_index(drop=True)
-
-                team_schedule_url_merge[i]['team_game'][0] = 0
-                team_schedule_url_merge[i]['player_game'][0] = 0
-                team_schedule_url_merge[i]['stat'][0] = 0
-
-                for j in range(1,len(team_schedule_url_merge[i]),2):
-                    team_schedule_url_merge[i]['player_game'][j] = team_schedule_url_merge[i]['player_game'][j]-1
-                    team_schedule_url_merge[i]['team_game'][j] = team_schedule_url_merge[i]['team_game'][j]-1
-                    team_schedule_url_merge[i]['stat'][j] = team_schedule_url_merge[i]['stat'][j] - team_schedule_url_merge[i][stat][j]
-
-                if len(team_schedule_url_merge[i]) >3:     
-                    if pd.isna(team_schedule_url_merge[i].iloc[3]['player_game']) and pd.isna(team_schedule_url_merge[i].iloc[1]['player_game']) == True:
-                        team_schedule_url_merge[i]['player_game'][2] = np.nan
-                        team_schedule_url_merge[i]['stat'][2] = np.nan
-
-                if len(team_schedule_url_merge[i]) >3:   
-                    if pd.isna(team_schedule_url_merge[i].iloc[len(team_schedule_url_merge[i])-1]['player_game']) == True:
-                        team_schedule_url_merge[i]['stat'][len(team_schedule_url_merge[i])-1] = np.nanmax(team_schedule_url_merge[i]['stat'])
-
-                if not (team_schedule_url_merge[i]['team_game'].values[1] == team_schedule_url_merge[i]['player_game'].values[0]):   
-                    team_schedule_url_merge[i].loc[0,'team_game'] = np.nan
-
-
-                max_games_player.append(np.around(np.nanmax(team_schedule_url_merge[i]['player_game'])))
-                max_games_team.append(np.around(np.nanmax(team_schedule_url_merge[i]['team_game'])))
-                max_stat.append((np.around(np.nanmax(team_schedule_url_merge[i]['stat']))))
-
-
-
-
-
-
-            fig, ax = plt.subplots(figsize=(15,15))
-            cgfont = {'fontname':'Century Gothic'}
-            font = font_manager.FontProperties(family='Century Gothic',
-                                                style='normal', size=18)
-
-
-            ax.axhline(0,color='black',linestyle ="--",linewidth=2,alpha=1.0,label='Missed Games')
-            ax.axhline(0,color='black',linestyle ="-",linewidth=2,alpha=1.0)
-
-
-            if 'Total' in stat:
-                stat = stat.replace('Total ',"")
-
-
-            colour_scheme = ['#648FFF','#785EF0','#DC267F','#FE6100','#FFB000','#FAEF3B','#861318','#2ED3BC','#341BBF','#B37E2C']
-
-            for i in range(len(team_schedule_url_merge)):
-                sns.lineplot(team_schedule_url_merge[i].reset_index()['team_game'],team_schedule_url_merge[i].reset_index()['stat'],linewidth=3-i*.2,color=colour_scheme[i])
-                plt.plot(team_schedule_url_merge[i]['team_game'],team_schedule_url_merge[i]['stat'],color=ax.lines[i*2+2].get_color(),label=str(i+1)+'. '+team_schedule_url_merge[i]['Player'][0]+', '+str(int(max_stat[i]))+' '+stat+' in '+str(int(max(team_schedule_url_merge[i]['player_game'])))+' Games',linewidth=6)
-                ax.lines[i*2+2].set_linestyle("--")
-
+        team_schedule_url_merge = []
+        max_games_player = []
+        max_games_team = []
+        max_stat = []
+        per_game = False
+        for i in range(0,len(player_lookup_list)):
+            team_schedule_url_merge.append(player_games_df[(player_games_df.player_id == int(player_lookup_list[i]))&(date_range_list[k] >= player_games_df.date)].reset_index(drop=True))
+            #print('touble',i, player_lookup_list[i],len(player_games_df[(player_games_df.player_id == player_lookup_list[i])]))
+            team_schedule_url_merge[i].index = team_schedule_url_merge[i].team_game
+            team_schedule_url_merge[i] = team_schedule_url_merge[i].reindex(np.arange(team_schedule_url_merge[i].team_game.min(), team_schedule_url_merge[i].team_game.max() + 1)).reset_index(drop=True)
+            #team_schedule_url_merge[0]['team_game'] = team_schedule_url_merge[0]['index']
+            #team_schedule_url_merge[0]['player_game'] = 
+            #schedule_ccount_df[schedule_ccount_df['team'].isin(team_schedule_url_merge[0].Team.unique())].merge(right=team_schedule_url_merge[0],left_on=['date','team'],right_on=['date','Team'],how='left')
 
+    
+            team_schedule_url_merge[i]['stat'] = team_schedule_url_merge[i][stat].cumsum()
 
-            fig.set_facecolor('#ffffff')
-            ax.set(xlim=(0,max([team_schedule_url_merge[x].team_game.max() for x in range(len(team_schedule_url_merge))])))
-            ax.set(ylim=(0,max([team_schedule_url_merge[x].stat.max() for x in range(len(team_schedule_url_merge))])))
+    
 
-            ax.legend_.remove()
+    
+            #team_schedule_url_merge[i]['stat'] = team_schedule_url_merge[i][stat_pick]
+            team_schedule_url_merge[i] = team_schedule_url_merge[i].append(team_schedule_url_merge[i]).sort_index()
+            team_schedule_url_merge[i] = team_schedule_url_merge[i].append(team_schedule_url_merge[i].iloc[0]).sort_index().reset_index(drop=True)
 
+            team_schedule_url_merge[i]['team_game'][0] = 0
+            team_schedule_url_merge[i]['player_game'][0] = 0
+            team_schedule_url_merge[i]['stat'][0] = 0
 
+    
+            for j in range(1,len(team_schedule_url_merge[i]),2):
+                team_schedule_url_merge[i]['player_game'][j] = team_schedule_url_merge[i]['player_game'][j]-1
+                team_schedule_url_merge[i]['team_game'][j] = team_schedule_url_merge[i]['team_game'][j]-1
+                team_schedule_url_merge[i]['stat'][j] = team_schedule_url_merge[i]['stat'][j] - team_schedule_url_merge[i][stat][j]
+
+            if len(team_schedule_url_merge[i]) >3:     
+                if pd.isna(team_schedule_url_merge[i].iloc[3]['player_game']) and pd.isna(team_schedule_url_merge[i].iloc[1]['player_game']) == True:
+                    team_schedule_url_merge[i]['player_game'][2] = np.nan
+                    team_schedule_url_merge[i]['stat'][2] = np.nan
+
+            if len(team_schedule_url_merge[i]) >3:   
+                if pd.isna(team_schedule_url_merge[i].iloc[len(team_schedule_url_merge[i])-1]['player_game']) == True:
+                    team_schedule_url_merge[i]['stat'][len(team_schedule_url_merge[i])-1] = np.nanmax(team_schedule_url_merge[i]['stat'])
+
+            if not (team_schedule_url_merge[i]['team_game'].values[1] == team_schedule_url_merge[i]['player_game'].values[0]):   
+                team_schedule_url_merge[i].loc[0,'team_game'] = np.nan
+    
+    
+            max_games_player.append(np.around(np.nanmax(team_schedule_url_merge[i]['player_game'])))
+            max_games_team.append(np.around(np.nanmax(team_schedule_url_merge[i]['team_game'])))
+            max_stat.append((np.around(np.nanmax(team_schedule_url_merge[i]['stat']))))
 
-            if per_game == False:
-                fig.suptitle(f'{rookie}{team_select_title}{position_select_title}{stat} Race',y=.98,fontsize=32,color='black',**cgfont)
-                ax.set_ylabel(stat,fontsize=20,color='black',**cgfont)
-            # else:
-            # fig.suptitle(stat+' Per Game, All Situations',y=.99,fontsize=48,color='black',**cgfont)
-            # ax.set_ylabel(stat+"/GP",fontsize=20,color='black',**cgfont)
+    
+        fig, ax = plt.subplots(figsize=(15,15))
+        cgfont = {'fontname':'Century Gothic'}
+        font = font_manager.FontProperties(family='Century Gothic',
+                                            style='normal', size=14)
 
+        ax.axhline(0,color='black',linestyle ="--",linewidth=2,alpha=1.0,label='Missed Games')
+        ax.axhline(0,color='black',linestyle ="-",linewidth=2,alpha=1.0)
 
+        if 'Total' in stat:
+            stat = stat.replace('Total ',"")
 
-            ax.set_title(str(current_season)[0:4]+'-'+str(start_season)[-4:]+' Season',y=1.01,fontsize=18,color='black',**cgfont,x=0,ha='left')
-            ax.set_xlabel('Team Game',fontsize=20,color='black',**cgfont)
-            ax.tick_params(axis="x", labelsize=24,colors='black')
-            ax.set_facecolor('#ffffff')
-            ax.xaxis.set_major_locator(MaxNLocator(integer=True))
-            ax.tick_params(axis="y", labelsize=24,colors='black')
-            ax.yaxis.set_major_locator(MaxNLocator(integer=True))
 
-            fig.text(x=0.025,y=0.01,s="Created By: @TJStats",color='black', fontsize=20, horizontalalignment='left',**cgfont)
-            fig.text(x=0.975,y=0.01,s="Data: Natural Stat Trick",color='black', fontsize=20, horizontalalignment='right',**cgfont)
-            fig.text(x=.975,y=0.92,s='Date: '+input.date().strftime('%B %d, %Y'),color='black', fontsize=18, horizontalalignment='right',**cgfont)
+        colour_scheme = ['#648FFF','#785EF0','#DC267F','#FE6100','#FFB000','#FAEF3B','#861318','#2ED3BC','#341BBF','#B37E2C']
 
-            ax.legend(prop=font,bbox_to_anchor=(0.01, 0.99),loc='upper left',framealpha=1,frameon=True)
-            plt.tight_layout()
-            #fig.savefig('gif_race/'+stat+rookie+str(date_range_list[k].date())+'.png', facecolor=fig.get_facecolor(), edgecolor='none',bbox_inches='tight',dpi=100)
-            #plt.close()
-            #fig.legend(prop=font,loc='best',framealpha=1,frameon=True)
+    
+        for i in range(len(team_schedule_url_merge)):
+            sns.lineplot(team_schedule_url_merge[i].reset_index()['team_game'],team_schedule_url_merge[i].reset_index()['stat'],linewidth=3-i*.2,color=colour_scheme[i])
+            plt.plot(team_schedule_url_merge[i]['team_game'],team_schedule_url_merge[i]['stat'],color=ax.lines[i*2+2].get_color(),label=str(i+1)+'. '+team_schedule_url_merge[i]['Player'][0]+', '+str(int(max_stat[i]))+' '+stat+' in '+str(int(max(team_schedule_url_merge[i]['player_game'])))+' Games',linewidth=6)
+            ax.lines[i*2+2].set_linestyle("--")
 
-app = App(app_ui, server)
+    
+        fig.set_facecolor('#ffffff')
+        ax.set(xlim=(0,max([team_schedule_url_merge[x].team_game.max() for x in range(len(team_schedule_url_merge))])))
+        ax.set(ylim=(0,max([team_schedule_url_merge[x].stat.max() for x in range(len(team_schedule_url_merge))])))
+
+        ax.legend_.remove()
+
+        if per_game == False:
+            fig.suptitle(f'{rookie}{team_select_title}{position_select_title}{stat} Race',y=.98,fontsize=32,color='black',**cgfont)
+            ax.set_ylabel(stat,fontsize=20,color='black',**cgfont)
+        # else:
+        # fig.suptitle(stat+' Per Game, All Situations',y=.99,fontsize=48,color='black',**cgfont)
+        # ax.set_ylabel(stat+"/GP",fontsize=20,color='black',**cgfont)
+        ax.set_title(str(current_season)[0:4]+'-'+str(start_season)[-4:]+' Season',y=1.01,fontsize=18,color='black',**cgfont,x=0,ha='left')
+        ax.set_xlabel('Team Game',fontsize=20,color='black',**cgfont)
+        ax.tick_params(axis="x", labelsize=24,colors='black')
+        ax.set_facecolor('#ffffff')
+        ax.xaxis.set_major_locator(MaxNLocator(integer=True))
+        ax.tick_params(axis="y", labelsize=24,colors='black')
+        ax.yaxis.set_major_locator(MaxNLocator(integer=True))
+    
+        fig.text(x=0.025,y=0.01,s="Created By: @TJStats",color='black', fontsize=20, horizontalalignment='left',**cgfont)
+        fig.text(x=0.975,y=0.01,s="Data: Natural Stat Trick",color='black', fontsize=20, horizontalalignment='right',**cgfont)
+        fig.text(x=.975,y=0.92,s='Date: '+input.date().strftime('%B %d, %Y'),color='black', fontsize=18, horizontalalignment='right',**cgfont)
+
+        ax.legend(prop=font,bbox_to_anchor=(0.01, 0.99),loc='upper left',framealpha=1,frameon=True)
+        plt.tight_layout()
+        #fig.savefig('gif_race/'+stat+rookie+str(date_range_list[k].date())+'.png', facecolor=fig.get_facecolor(), edgecolor='none',bbox_inches='tight',dpi=100)
+        #plt.close()
+        #fig.legend(prop=font,loc='best',framealpha=1,frameon=True)
+
+ 
+app = App(app_ui, server)