James McCool commited on
Commit
9dcce38
·
1 Parent(s): 9bc6a1f

Update column renaming in load_overall_stats function in app.py: change 'DK_ID' and 'FD_ID' to 'player_ID' for improved clarity and consistency in data handling for WNBA league exports.

Browse files
Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -78,7 +78,7 @@ def load_overall_stats(league: str):
78
  'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
79
  raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
80
  elif league == 'WNBA':
81
- raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "DK_Proj": "Median", "DK_ID": "ID", "DK_Pos": "Position", "DK_Salary": "Salary", "DK_Own": "Own"})
82
  raw_display = raw_display.loc[raw_display['Median'] > 0]
83
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
84
  dk_raw = raw_display.sort_values(by='Median', ascending=False)
@@ -95,7 +95,7 @@ def load_overall_stats(league: str):
95
  'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
96
  raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
97
  elif league == 'WNBA':
98
- raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "FD_Proj": "Median", "FD_ID": "ID", "FD_Pos": "Position", "FD_Salary": "Salary", "FD_Own": "Own"})
99
  raw_display = raw_display.loc[raw_display['Median'] > 0]
100
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
101
  fd_raw = raw_display.sort_values(by='Median', ascending=False)
@@ -112,7 +112,7 @@ def load_overall_stats(league: str):
112
  'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
113
  raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
114
  elif league == 'WNBA':
115
- raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "DK_Proj": "Median", "DK_ID": "ID", "DK_Pos": "Position", "DK_Salary": "Salary", "DK_Own": "Own"})
116
  raw_display = raw_display.loc[raw_display['Median'] > 0]
117
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
118
  dk_raw_sec = raw_display.sort_values(by='Median', ascending=False)
@@ -129,7 +129,7 @@ def load_overall_stats(league: str):
129
  'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
130
  raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
131
  elif league == 'WNBA':
132
- raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "FD_Proj": "Median", "FD_ID": "ID", "FD_Pos": "Position", "FD_Salary": "Salary", "FD_Own": "Own"})
133
  raw_display = raw_display.loc[raw_display['Median'] > 0]
134
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
135
  fd_raw_sec = raw_display.sort_values(by='Median', ascending=False)
 
78
  'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
79
  raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
80
  elif league == 'WNBA':
81
+ raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "DK_Proj": "Median", "DK_ID": "player_ID", "DK_Pos": "Position", "DK_Salary": "Salary", "DK_Own": "Own"})
82
  raw_display = raw_display.loc[raw_display['Median'] > 0]
83
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
84
  dk_raw = raw_display.sort_values(by='Median', ascending=False)
 
95
  'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
96
  raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
97
  elif league == 'WNBA':
98
+ raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "FD_Proj": "Median", "FD_ID": "player_ID", "FD_Pos": "Position", "FD_Salary": "Salary", "FD_Own": "Own"})
99
  raw_display = raw_display.loc[raw_display['Median'] > 0]
100
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
101
  fd_raw = raw_display.sort_values(by='Median', ascending=False)
 
112
  'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
113
  raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
114
  elif league == 'WNBA':
115
+ raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "DK_Proj": "Median", "DK_ID": "player_ID", "DK_Pos": "Position", "DK_Salary": "Salary", "DK_Own": "Own"})
116
  raw_display = raw_display.loc[raw_display['Median'] > 0]
117
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
118
  dk_raw_sec = raw_display.sort_values(by='Median', ascending=False)
 
129
  'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
130
  raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
131
  elif league == 'WNBA':
132
+ raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "FD_Proj": "Median", "FD_ID": "player_ID", "FD_Pos": "Position", "FD_Salary": "Salary", "FD_Own": "Own"})
133
  raw_display = raw_display.loc[raw_display['Median'] > 0]
134
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
135
  fd_raw_sec = raw_display.sort_values(by='Median', ascending=False)