Update app.py

app.py

@@ -84,36 +84,41 @@ 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'])
+# 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.read_csv('df_2023_small.csv',index_col=[0])
+yahoo_df.percent_owned = yahoo_df.percent_owned.astype(float)
+#yahoo_df_scrape.columns = ['yahoo_id','idx','full','first','last','average_pick','average_auction_cost','projected_auction_value','position','team','percent_owned','status']
+#yahoo_df_scrape.status = yahoo_df_scrape.status.astype(str)
+
+
+#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']