Hugging Face's logo

Spaces:
Multichem
/
NBA_DFS_ROO
Running

App Files Community
James McCool commited on
Commit
3dc7dac
·
1 Parent(s): b943545

ping ping

Browse files
Files changed (1) hide show
  1. app.py +1 -6
app.py CHANGED
@@ -64,7 +64,6 @@ def load_overall_stats():
64
  raw_display = pd.DataFrame(worksheet.get_all_records())
65
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
66
  raw_display.replace("", 'Welp', inplace=True)
67
- raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
68
  raw_display = raw_display.loc[raw_display['Salary'] > 0]
69
  raw_display = raw_display.loc[raw_display['Median'] > 0]
70
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
@@ -74,7 +73,6 @@ def load_overall_stats():
74
  raw_display = pd.DataFrame(worksheet.get_all_records())
75
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
76
  raw_display.replace("", 'Welp', inplace=True)
77
- raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
78
  raw_display = raw_display.loc[raw_display['Median'] > 0]
79
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
80
  fd_raw = raw_display.sort_values(by='Median', ascending=False)
@@ -83,7 +81,6 @@ def load_overall_stats():
83
  raw_display = pd.DataFrame(worksheet.get_all_records())
84
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
85
  raw_display.replace("", 'Welp', inplace=True)
86
- raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
87
  raw_display = raw_display.loc[raw_display['Median'] > 0]
88
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
89
  dk_raw_sec = raw_display.sort_values(by='Median', ascending=False)
@@ -92,7 +89,6 @@ def load_overall_stats():
92
  raw_display = pd.DataFrame(worksheet.get_all_records())
93
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
94
  raw_display.replace("", 'Welp', inplace=True)
95
- raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
96
  raw_display = raw_display.loc[raw_display['Median'] > 0]
97
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
98
  fd_raw_sec = raw_display.sort_values(by='Median', ascending=False)
@@ -100,7 +96,6 @@ def load_overall_stats():
100
  worksheet = sh.worksheet('Player_Level_ROO')
101
  raw_display = pd.DataFrame(worksheet.get_all_records())
102
  raw_display.replace("", 'Welp', inplace=True)
103
- raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
104
  raw_display = raw_display.loc[raw_display['Median'] > 0]
105
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
106
  roo_raw = raw_display.sort_values(by='Median', ascending=False)
@@ -109,7 +104,7 @@ def load_overall_stats():
109
 
110
  return dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp
111
 
112
- @st.cache_data(ttl = 299)
113
  def init_DK_lineups():
114
 
115
  collection = db["DK_NBA_seed_frame"]
 
64
  raw_display = pd.DataFrame(worksheet.get_all_records())
65
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
66
  raw_display.replace("", 'Welp', inplace=True)
 
67
  raw_display = raw_display.loc[raw_display['Salary'] > 0]
68
  raw_display = raw_display.loc[raw_display['Median'] > 0]
69
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
 
73
  raw_display = pd.DataFrame(worksheet.get_all_records())
74
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
75
  raw_display.replace("", 'Welp', inplace=True)
 
76
  raw_display = raw_display.loc[raw_display['Median'] > 0]
77
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
78
  fd_raw = raw_display.sort_values(by='Median', ascending=False)
 
81
  raw_display = pd.DataFrame(worksheet.get_all_records())
82
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
83
  raw_display.replace("", 'Welp', inplace=True)
 
84
  raw_display = raw_display.loc[raw_display['Median'] > 0]
85
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
86
  dk_raw_sec = raw_display.sort_values(by='Median', ascending=False)
 
89
  raw_display = pd.DataFrame(worksheet.get_all_records())
90
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
91
  raw_display.replace("", 'Welp', inplace=True)
 
92
  raw_display = raw_display.loc[raw_display['Median'] > 0]
93
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
94
  fd_raw_sec = raw_display.sort_values(by='Median', ascending=False)
 
96
  worksheet = sh.worksheet('Player_Level_ROO')
97
  raw_display = pd.DataFrame(worksheet.get_all_records())
98
  raw_display.replace("", 'Welp', inplace=True)
 
99
  raw_display = raw_display.loc[raw_display['Median'] > 0]
100
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
101
  roo_raw = raw_display.sort_values(by='Median', ascending=False)
 
104
 
105
  return dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp
106
 
107
+ @st.cache_data(ttl = 300)
108
  def init_DK_lineups():
109
 
110
  collection = db["DK_NBA_seed_frame"]