James McCool commited on
Commit
9287978
·
1 Parent(s): 6dac0fa

Added season numbers

Browse files
Files changed (1) hide show
  1. app.py +19 -21
app.py CHANGED
@@ -47,7 +47,7 @@ def init_baselines():
47
  raw_display = raw_display.reset_index(drop=True)
48
  trend_table = raw_display[raw_display['PLAYER_NAME'] != ""]
49
  trend_table.replace('', np.nan, inplace=True)
50
- trend_table = trend_table[['PLAYER_NAME', 'Team', 'Position', 'FD_Position', 'L10 MIN', 'L10 Fantasy', 'L10 FPPM', 'L10 Ceiling', 'L10 FD_Fantasy',
51
  'L10 FD_Ceiling', 'L5 MIN', 'L5 Fantasy', 'L5 FPPM', 'L5 Ceiling', 'L5 FD_Fantasy', 'L5 FD_Ceiling', 'L3 MIN', 'L3 Fantasy',
52
  'L3 FPPM', 'L3 Ceiling', 'L3 FD_Fantasy', 'L3 FD_Ceiling', 'Trend Min', 'Trend Median', 'Trend FPPM', 'DK_Proj', 'Adj Median', 'Adj Ceiling',
53
  'Trend FD_Median', 'FD_Proj', 'Adj FD_Median', 'Adj FD_Ceiling', 'DK_Salary', 'DK_Avg_Val', 'DK_Ceiling_Value',
@@ -58,17 +58,17 @@ def init_baselines():
58
  data_cols = trend_table.columns.drop(['PLAYER_NAME', 'Team', 'Position', 'FD_Position'])
59
  trend_table[data_cols] = trend_table[data_cols].apply(pd.to_numeric, errors='coerce')
60
 
61
- dk_minutes_table = trend_table[['PLAYER_NAME', 'Team', 'L10 MIN', 'L5 MIN', 'L3 MIN', 'Trend Min']]
62
 
63
- fd_minutes_table = trend_table[['PLAYER_NAME', 'Team', 'L10 MIN', 'L5 MIN', 'L3 MIN', 'Trend Min']]
64
 
65
- dk_medians_table = trend_table[['PLAYER_NAME', 'Team', 'L10 Fantasy', 'L5 Fantasy', 'L3 Fantasy', 'Trend Median']]
66
 
67
- fd_medians_table = trend_table[['PLAYER_NAME', 'Team', 'L10 FD_Fantasy', 'L5 FD_Fantasy', 'L3 FD_Fantasy', 'Trend FD_Median']]
68
 
69
- dk_fppm_table = trend_table[['PLAYER_NAME', 'Team', 'L10 FPPM', 'L5 FPPM', 'L3 FPPM', 'Trend FPPM']]
70
 
71
- fd_fppm_table = trend_table[['PLAYER_NAME', 'Team', 'L10 FPPM', 'L5 FPPM', 'L3 FPPM', 'Trend FPPM']]
72
 
73
  dk_proj_medians_table = trend_table[['PLAYER_NAME', 'Team', 'Position', 'DK_Salary', 'DK_Proj', 'Adj Median', 'DK_Avg_Val', 'Adj Ceiling', 'DK_Ceiling_Value']]
74
 
@@ -89,32 +89,30 @@ with col1:
89
  split_var1 = st.radio("What table would you like to view?", ('Minutes Trends', 'Fantasy Trends', 'FPPM Trends', 'Slate specific', 'Overall'), key='split_var1')
90
  site_var1 = st.radio("What site would you like to view?", ('Draftkings', 'Fanduel'), key='site_var1')
91
  if site_var1 == 'Draftkings':
92
- trend_table = trend_table[['PLAYER_NAME', 'Team', 'Position', 'L10 MIN', 'L10 Fantasy', 'L10 FPPM', 'L10 Ceiling',
93
- 'L5 MIN', 'L5 Fantasy', 'L5 FPPM', 'L5 Ceiling', 'L3 MIN', 'L3 Fantasy',
94
- 'L3 FPPM', 'L3 Ceiling', 'Trend Min', 'Trend Median', 'Trend FPPM', 'DK_Proj', 'Adj Median', 'Adj Ceiling',
95
  'DK_Salary', 'DK_Avg_Val', 'DK_Ceiling_Value']]
96
  minutes_table = dk_minutes_table
97
  medians_table = dk_medians_table
98
  fppm_table = dk_fppm_table
99
  proj_medians_table = dk_proj_medians_table
100
  elif site_var1 == 'Fanduel':
101
- trend_table = trend_table[['PLAYER_NAME', 'Team', 'FD_Position', 'L10 MIN', 'L10 FD_Fantasy', 'L10 FPPM', 'L10 FD_Ceiling',
102
- 'L5 MIN', 'L5 FD_Fantasy', 'L5 FPPM', 'L5 FD_Ceiling', 'L3 MIN', 'L3 FD_Fantasy', 'L3 FPPM', 'L3 FD_Ceiling',
103
- 'Trend Min', 'Trend FD_Median', 'Trend FPPM', 'FD_Proj', 'Adj FD_Median', 'Adj FD_Ceiling',
104
  'FD_Salary', 'FD_Avg_Val', 'FD_Ceiling_Value']]
105
  minutes_table = fd_minutes_table
106
  medians_table = fd_medians_table
107
  fppm_table = fd_fppm_table
108
  proj_medians_table = fd_proj_medians_table
109
- trend_table = trend_table.set_axis(['PLAYER_NAME', 'Team', 'Position', 'L10 MIN', 'L10 Fantasy', 'L10 FPPM', 'L10 Ceiling',
110
- 'L5 MIN', 'L5 Fantasy', 'L5 FPPM', 'L5 Ceiling', 'L3 MIN', 'L3 Fantasy',
111
- 'L3 FPPM', 'L3 Ceiling', 'Trend Min', 'Trend Median', 'Trend FPPM', 'FD_Proj', 'Adj FD_Median', 'Adj FD_Ceiling',
112
  'FD_Salary', 'FD_Avg_Val', 'FD_Ceiling_Value'], axis=1)
113
- minutes_table = minutes_table.set_axis(['PLAYER_NAME', 'Team', 'L10 MIN', 'L5 MIN', 'L3 MIN', 'Trend Min'], axis=1)
114
- medians_table = medians_table.set_axis(['PLAYER_NAME', 'Team', 'L10 Fantasy','L5 Fantasy', 'L3 Fantasy', 'Trend Median'], axis=1)
115
- fppm_table = fppm_table.set_axis(['PLAYER_NAME', 'Team', 'L10 FPPM', 'L5 FPPM', 'L3 FPPM', 'Trend FPPM'], axis=1)
116
- proj_medians_table = proj_medians_table.set_axis(['PLAYER_NAME', 'Team', 'Position', 'Salary', 'Proj',
117
- 'Adj Median', 'Avg_Val', 'Adj Ceiling', 'Ceiling_Value'], axis=1)
118
  if split_var1 == 'Overall':
119
  view_var1 = trend_table.Team.values.tolist()
120
  split_var2 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var2')
 
47
  raw_display = raw_display.reset_index(drop=True)
48
  trend_table = raw_display[raw_display['PLAYER_NAME'] != ""]
49
  trend_table.replace('', np.nan, inplace=True)
50
+ trend_table = trend_table[['PLAYER_NAME', 'Team', 'Position', 'FD_Position', 'Season MIN', 'Season Fantasy', 'Season FPPM', 'Season Ceiling', 'Season FD_Fantasy', 'Season FD_Ceiling', 'L10 MIN', 'L10 Fantasy', 'L10 FPPM', 'L10 Ceiling', 'L10 FD_Fantasy',
51
  'L10 FD_Ceiling', 'L5 MIN', 'L5 Fantasy', 'L5 FPPM', 'L5 Ceiling', 'L5 FD_Fantasy', 'L5 FD_Ceiling', 'L3 MIN', 'L3 Fantasy',
52
  'L3 FPPM', 'L3 Ceiling', 'L3 FD_Fantasy', 'L3 FD_Ceiling', 'Trend Min', 'Trend Median', 'Trend FPPM', 'DK_Proj', 'Adj Median', 'Adj Ceiling',
53
  'Trend FD_Median', 'FD_Proj', 'Adj FD_Median', 'Adj FD_Ceiling', 'DK_Salary', 'DK_Avg_Val', 'DK_Ceiling_Value',
 
58
  data_cols = trend_table.columns.drop(['PLAYER_NAME', 'Team', 'Position', 'FD_Position'])
59
  trend_table[data_cols] = trend_table[data_cols].apply(pd.to_numeric, errors='coerce')
60
 
61
+ dk_minutes_table = trend_table[['PLAYER_NAME', 'Team', 'Season MIN', 'L10 MIN', 'L5 MIN', 'L3 MIN', 'Trend Min']]
62
 
63
+ fd_minutes_table = trend_table[['PLAYER_NAME', 'Team', 'Season MIN', 'L10 MIN', 'L5 MIN', 'L3 MIN', 'Trend Min']]
64
 
65
+ dk_medians_table = trend_table[['PLAYER_NAME', 'Team', 'Season Fantasy', 'L10 Fantasy', 'L5 Fantasy', 'L3 Fantasy', 'Trend Median']]
66
 
67
+ fd_medians_table = trend_table[['PLAYER_NAME', 'Team', 'Season FD_Fantasy', 'L10 FD_Fantasy', 'L5 FD_Fantasy', 'L3 FD_Fantasy', 'Trend FD_Median']]
68
 
69
+ dk_fppm_table = trend_table[['PLAYER_NAME', 'Team', 'Season FPPM', 'L10 FPPM', 'L5 FPPM', 'L3 FPPM', 'Trend FPPM']]
70
 
71
+ fd_fppm_table = trend_table[['PLAYER_NAME', 'Team', 'Season FPPM', 'L10 FPPM', 'L5 FPPM', 'L3 FPPM', 'Trend FPPM']]
72
 
73
  dk_proj_medians_table = trend_table[['PLAYER_NAME', 'Team', 'Position', 'DK_Salary', 'DK_Proj', 'Adj Median', 'DK_Avg_Val', 'Adj Ceiling', 'DK_Ceiling_Value']]
74
 
 
89
  split_var1 = st.radio("What table would you like to view?", ('Minutes Trends', 'Fantasy Trends', 'FPPM Trends', 'Slate specific', 'Overall'), key='split_var1')
90
  site_var1 = st.radio("What site would you like to view?", ('Draftkings', 'Fanduel'), key='site_var1')
91
  if site_var1 == 'Draftkings':
92
+ trend_table = trend_table[['PLAYER_NAME', 'Team', 'Position', 'Season MIN', 'L10 MIN', 'L5 MIN', 'L3 MIN', 'Trend Min', 'Season Fantasy', 'L10 Fantasy', 'L5 Fantasy', 'L3 Fantasy',
93
+ 'Trend Median', 'Season FPPM', 'L10 FPPM', 'L5 FPPM', 'L3 FPPM', 'Trend FPPM', 'DK_Proj', 'Adj Median', 'Adj Ceiling',
 
94
  'DK_Salary', 'DK_Avg_Val', 'DK_Ceiling_Value']]
95
  minutes_table = dk_minutes_table
96
  medians_table = dk_medians_table
97
  fppm_table = dk_fppm_table
98
  proj_medians_table = dk_proj_medians_table
99
  elif site_var1 == 'Fanduel':
100
+ trend_table = trend_table[['PLAYER_NAME', 'Team', 'FD_Position', 'Season MIN', 'L10 MIN', 'L5 MIN', 'L3 MIN', 'Trend Min', 'Season FD_Fantasy', 'L10 FD_Fantasy', 'L5 FD_Fantasy', 'L3 FD_Fantasy',
101
+ 'Trend FD_Median', 'Season FPPM', 'L10 FPPM', 'L5 FPPM', 'L3 FPPM', 'Trend FPPM', 'FD_Proj', 'Adj FD_Median', 'Adj FD_Ceiling',
 
102
  'FD_Salary', 'FD_Avg_Val', 'FD_Ceiling_Value']]
103
  minutes_table = fd_minutes_table
104
  medians_table = fd_medians_table
105
  fppm_table = fd_fppm_table
106
  proj_medians_table = fd_proj_medians_table
107
+ trend_table = trend_table.set_axis(['PLAYER_NAME', 'Team', 'Position', 'Season MIN', 'L10 MIN', 'L5 MIN', 'L3 MIN', 'Trend Min', 'Season Fantasy', 'L10 Fantasy', 'L5 Fantasy', 'L3 Fantasy',
108
+ 'Trend Median', 'Season FPPM', 'L10 FPPM', 'L5 FPPM', 'L3 FPPM', 'Trend FPPM', 'DK_Proj', 'Adj Median', 'Adj Ceiling',
109
+ 'DK_Salary', 'DK_Avg_Val', 'DK_Ceiling_Value', 'FD_Proj', 'Adj FD_Median', 'Adj FD_Ceiling',
110
  'FD_Salary', 'FD_Avg_Val', 'FD_Ceiling_Value'], axis=1)
111
+ minutes_table = minutes_table.set_axis(['PLAYER_NAME', 'Team', 'Season MIN', 'L10 MIN', 'L5 MIN', 'L3 MIN', 'Trend Min'], axis=1)
112
+ medians_table = medians_table.set_axis(['PLAYER_NAME', 'Team', 'Season Fantasy', 'L10 Fantasy', 'L5 Fantasy', 'L3 Fantasy', 'Trend Median'], axis=1)
113
+ fppm_table = fppm_table.set_axis(['PLAYER_NAME', 'Team', 'Season FPPM', 'L10 FPPM', 'L5 FPPM', 'L3 FPPM', 'Trend FPPM'], axis=1)
114
+ proj_medians_table = proj_medians_table.set_axis(['PLAYER_NAME', 'Team', 'Position', 'DK_Salary', 'DK_Proj', 'Adj Median', 'DK_Avg_Val', 'Adj Ceiling', 'DK_Ceiling_Value',
115
+ 'FD_Salary', 'FD_Proj', 'Adj FD_Median', 'FD_Avg_Val', 'Adj FD_Ceiling', 'FD_Ceiling_Value'], axis=1)
116
  if split_var1 == 'Overall':
117
  view_var1 = trend_table.Team.values.tolist()
118
  split_var2 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var2')