Update app.py

app.py

@@ -84,39 +84,39 @@ co = matplotlib.colors.LinearSegmentedColormap.from_list("", ["#56B4E9","#FFFFFF
 
 
 
-# try: 
-#     data_r = requests.get("https://pub-api-ro.fantasysports.yahoo.com/fantasy/v2/league/427.l.public;out=settings/players;position=ALL;start=0;count=3000;sort=rank_season;search=;out=percent_owned;out=auction_values,ranks;ranks=season;ranks_by_position=season;out=expert_ranks;expert_ranks.rank_type=projected_season_remaining/draft_analysis;cut_types=diamond;slices=last7days?format=json_f").json()
-#     key_check = data_r['fantasy_content']['league']['players']
-
-# except KeyError:
-#     data_r = requests.get("https://pub-api-ro.fantasysports.yahoo.com/fantasy/v2/league/427.l.public;out=settings/players;position=ALL;start=0;count=400;sort=rank_season;search=;out=percent_owned;out=auction_values,ranks;ranks=season;ranks_by_position=season;out=expert_ranks;expert_ranks.rank_type=projected_season_remaining/draft_analysis;cut_types=diamond;slices=last7days?format=json_f").json()
-#     print('key_checked')
-
-# total_list = []
-
-# for x in data_r['fantasy_content']['league']['players']:
-#     single_list = []
-
-#     single_list.append(int(x['player']['player_id']))
-#     single_list.append(int(x['player']['player_ranks'][0]['player_rank']['rank_value']))
-#     single_list.append(x['player']['name']['full'])
-#     single_list.append(x['player']['name']['first'])
-#     single_list.append(x['player']['name']['last'])
-#     single_list.append(x['player']['draft_analysis']['average_pick'])
-#     single_list.append(x['player']['average_auction_cost'])
-#     single_list.append(x['player']['display_position'])
-#     single_list.append(x['player']['editorial_team_abbr'])
-#     if 'value' in x['player']['percent_owned']:
-#         single_list.append(x['player']['percent_owned']['value']/100)
-#     else:
-#         single_list.append(0)
-#     total_list.append(single_list)
-
-
-# yahoo_df = pd.DataFrame(total_list,columns = ['player_id','rank_value','full','first','last','average_pick','average_auction_cost','display_position','editorial_team_abbr','percent_owned'])
-
-yahoo_df = pd.read_csv('df_2023_small.csv',index_col=[0],usecols=range(12))
-yahoo_df.columns = ['rank_value','player_id','full','first','last','average_pick', 'average_cost','display_position','projected_auction_value','editorial_team_abbr','percent_owned']
+try: 
+    data_r = requests.get("https://pub-api-ro.fantasysports.yahoo.com/fantasy/v2/league/427.l.public;out=settings/players;position=ALL;start=0;count=3000;sort=rank_season;search=;out=percent_owned;out=auction_values,ranks;ranks=season;ranks_by_position=season;out=expert_ranks;expert_ranks.rank_type=projected_season_remaining/draft_analysis;cut_types=diamond;slices=last7days?format=json_f").json()
+    key_check = data_r['fantasy_content']['league']['players']
+
+except KeyError:
+    data_r = requests.get("https://pub-api-ro.fantasysports.yahoo.com/fantasy/v2/league/427.l.public;out=settings/players;position=ALL;start=0;count=400;sort=rank_season;search=;out=percent_owned;out=auction_values,ranks;ranks=season;ranks_by_position=season;out=expert_ranks;expert_ranks.rank_type=projected_season_remaining/draft_analysis;cut_types=diamond;slices=last7days?format=json_f").json()
+    print('key_checked')
+
+total_list = []
+
+for x in data_r['fantasy_content']['league']['players']:
+    single_list = []
+
+    single_list.append(int(x['player']['player_id']))
+    single_list.append(int(x['player']['player_ranks'][0]['player_rank']['rank_value']))
+    single_list.append(x['player']['name']['full'])
+    single_list.append(x['player']['name']['first'])
+    single_list.append(x['player']['name']['last'])
+    single_list.append(x['player']['draft_analysis']['average_pick'])
+    single_list.append(x['player']['average_auction_cost'])
+    single_list.append(x['player']['display_position'])
+    single_list.append(x['player']['editorial_team_abbr'])
+    if 'value' in x['player']['percent_owned']:
+        single_list.append(x['player']['percent_owned']['value']/100)
+    else:
+        single_list.append(0)
+    total_list.append(single_list)
+
+
+yahoo_df = pd.DataFrame(total_list,columns = ['player_id','rank_value','full','first','last','average_pick','average_auction_cost','display_position','editorial_team_abbr','percent_owned'])
+
+# yahoo_df = pd.read_csv('df_2023_small.csv',index_col=[0],usecols=range(12))
+# yahoo_df.columns = ['rank_value','player_id','full','first','last','average_pick', 'average_cost','display_position','projected_auction_value','editorial_team_abbr','percent_owned']
 
 yahoo_df_2 = yahoo_df.copy()