Multichem commited on
Commit
194646b
·
1 Parent(s): b93093d

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +56 -43
app.py CHANGED
@@ -38,62 +38,74 @@ gcservice_account = init_conn()
38
 
39
  freq_format = {'Proj Own': '{:.2%}', 'Exposure': '{:.2%}', 'Edge': '{:.2%}'}
40
 
41
- @st.cache_resource(ttl=600)
42
- def load_dk_player_projections():
43
- sh = gcservice_account.open_by_url('https://docs.google.com/spreadsheets/d/1I_1Ve3F4tftgfLQQoRKOJ351XfEG48s36OxXUKxmgS8/edit#gid=1391856348')
44
  worksheet = sh.worksheet('SD_Projections')
45
  load_display = pd.DataFrame(worksheet.get_all_records())
46
- load_display.rename(columns={"PPR": "Median", "name": "Player"}, inplace = True)
47
- load_display['Floor'] = load_display['Median'] * .25
48
- load_display['Ceiling'] = load_display['Median'] + (load_display['Median'] * .75)
49
  load_display.replace('', np.nan, inplace=True)
50
- raw_display = load_display.dropna(subset=['Median'])
 
 
 
51
 
52
- return raw_display
53
-
54
- @st.cache_resource(ttl=600)
55
- def load_fd_player_projections():
56
- sh = gcservice_account.open_by_url('https://docs.google.com/spreadsheets/d/1I_1Ve3F4tftgfLQQoRKOJ351XfEG48s36OxXUKxmgS8/edit#gid=1391856348')
57
  worksheet = sh.worksheet('FD_SD_Projections')
58
  load_display = pd.DataFrame(worksheet.get_all_records())
59
- load_display.rename(columns={"Half_PPR": "Median", "name": "Player"}, inplace = True)
60
- load_display['Floor'] = load_display['Median'] * .25
61
- load_display['Ceiling'] = load_display['Median'] + (load_display['Median'] * .75)
62
  load_display.replace('', np.nan, inplace=True)
63
- raw_display = load_display.dropna(subset=['Median'])
64
-
65
- return raw_display
 
66
 
67
- @st.cache_resource(ttl=600)
68
- def load_dk_player_projections_2():
69
- sh = gcservice_account.open_by_url('https://docs.google.com/spreadsheets/d/1I_1Ve3F4tftgfLQQoRKOJ351XfEG48s36OxXUKxmgS8/edit#gid=1391856348')
70
  worksheet = sh.worksheet('SD_Projections_2')
71
  load_display = pd.DataFrame(worksheet.get_all_records())
72
- load_display.rename(columns={"PPR": "Median", "name": "Player"}, inplace = True)
73
- load_display['Floor'] = load_display['Median'] * .25
74
- load_display['Ceiling'] = load_display['Median'] + (load_display['Median'] * .75)
75
  load_display.replace('', np.nan, inplace=True)
76
- raw_display = load_display.dropna(subset=['Median'])
77
-
78
- return raw_display
 
79
 
80
- @st.cache_resource(ttl=600)
81
- def load_fd_player_projections_2():
82
- sh = gcservice_account.open_by_url('https://docs.google.com/spreadsheets/d/1I_1Ve3F4tftgfLQQoRKOJ351XfEG48s36OxXUKxmgS8/edit#gid=1391856348')
83
  worksheet = sh.worksheet('FD_SD_Projections_2')
84
  load_display = pd.DataFrame(worksheet.get_all_records())
85
- load_display.rename(columns={"Half_PPR": "Median", "name": "Player"}, inplace = True)
86
- load_display['Floor'] = load_display['Median'] * .25
87
- load_display['Ceiling'] = load_display['Median'] + (load_display['Median'] * .75)
88
  load_display.replace('', np.nan, inplace=True)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
89
  raw_display = load_display.dropna(subset=['Median'])
 
90
 
91
- return raw_display
92
 
93
- dk_roo_raw = load_dk_player_projections()
94
- dk_roo_raw_2 = load_dk_player_projections_2()
95
- fd_roo_raw = load_fd_player_projections()
96
- fd_roo_raw_2 = load_fd_player_projections_2()
97
 
98
  static_exposure = pd.DataFrame(columns=['Player', 'count'])
99
  overall_exposure = pd.DataFrame(columns=['Player', 'count'])
@@ -590,12 +602,9 @@ with tab2:
590
  st.cache_data.clear()
591
  for key in st.session_state.keys():
592
  del st.session_state[key]
593
- dk_roo_raw = load_dk_player_projections()
594
- dk_roo_raw_2 = load_dk_player_projections_2()
595
- fd_roo_raw = load_fd_player_projections()
596
- fd_roo_raw_2 = load_fd_player_projections_2()
597
 
598
- slate_var1 = st.radio("Which data are you loading?", ('Paydirt (Main)', 'Paydirt (Secondary)', 'User'))
599
  site_var1 = 'Draftkings'
600
  if site_var1 == 'Draftkings':
601
  if slate_var1 == 'User':
@@ -604,6 +613,8 @@ with tab2:
604
  raw_baselines = dk_roo_raw
605
  elif slate_var1 == 'Paydirt (Secondary)':
606
  raw_baselines = dk_roo_raw_2
 
 
607
  elif site_var1 == 'Fanduel':
608
  if slate_var1 == 'User':
609
  raw_baselines = proj_dataframe
@@ -611,6 +622,8 @@ with tab2:
611
  raw_baselines = dk_roo_raw
612
  elif slate_var1 == 'Paydirt (Secondary)':
613
  raw_baselines = dk_roo_raw_2
 
 
614
 
615
  st.info("If you are uploading a portfolio, note that there is an adjustments to projections and deviation mapping to prevent 'Projection Bias' and create a fair simulation")
616
  insert_port1 = st.selectbox("Are you uploading a portfolio?", ('No', 'Yes'))
 
38
 
39
  freq_format = {'Proj Own': '{:.2%}', 'Exposure': '{:.2%}', 'Edge': '{:.2%}'}
40
 
41
+ @st.cache_resource(ttl=601)
42
+ def init_baselines():
43
+ sh = gcservice_account.open_by_url('https://docs.google.com/spreadsheets/d/1I_1Ve3F4tftgfLQQoRKOJ351XfEG48s36OxXUKxmgS8/edit#gid=1030253279')
44
  worksheet = sh.worksheet('SD_Projections')
45
  load_display = pd.DataFrame(worksheet.get_all_records())
 
 
 
46
  load_display.replace('', np.nan, inplace=True)
47
+ raw_display = load_display.dropna(subset=['PPR'])
48
+ raw_display.rename(columns={"name": "Player", "PPR": "Median"}, inplace = True)
49
+ raw_display = raw_display[['Player', 'Salary', 'Position', 'Team', 'Opp', 'Median', 'Own', 'rush_yards', 'rec']]
50
+ dk_roo_raw = raw_display.loc[raw_display['Median'] > 0]
51
 
 
 
 
 
 
52
  worksheet = sh.worksheet('FD_SD_Projections')
53
  load_display = pd.DataFrame(worksheet.get_all_records())
 
 
 
54
  load_display.replace('', np.nan, inplace=True)
55
+ raw_display = load_display.dropna(subset=['Half_PPR'])
56
+ raw_display.rename(columns={"name": "Player", "Half_PPR": "Median"}, inplace = True)
57
+ raw_display = raw_display[['Player', 'Salary', 'Position', 'Team', 'Opp', 'Median', 'Own', 'rush_yards', 'rec']]
58
+ fd_roo_raw = raw_display.loc[raw_display['Median'] > 0]
59
 
 
 
 
60
  worksheet = sh.worksheet('SD_Projections_2')
61
  load_display = pd.DataFrame(worksheet.get_all_records())
 
 
 
62
  load_display.replace('', np.nan, inplace=True)
63
+ raw_display = load_display.dropna(subset=['PPR'])
64
+ raw_display.rename(columns={"name": "Player", "PPR": "Median"}, inplace = True)
65
+ raw_display = raw_display[['Player', 'Salary', 'Position', 'Team', 'Opp', 'Median', 'Own', 'rush_yards', 'rec']]
66
+ dk_roo_raw_2 = raw_display.loc[raw_display['Median'] > 0]
67
 
 
 
 
68
  worksheet = sh.worksheet('FD_SD_Projections_2')
69
  load_display = pd.DataFrame(worksheet.get_all_records())
 
 
 
70
  load_display.replace('', np.nan, inplace=True)
71
+ raw_display = load_display.dropna(subset=['Half_PPR'])
72
+ raw_display.rename(columns={"name": "Player", "Half_PPR": "Median"}, inplace = True)
73
+ raw_display = raw_display[['Player', 'Salary', 'Position', 'Team', 'Opp', 'Median', 'Own', 'rush_yards', 'rec']]
74
+ fd_roo_raw_2 = raw_display.loc[raw_display['Median'] > 0]
75
+
76
+ worksheet = sh.worksheet('SD_Projections_3')
77
+ load_display = pd.DataFrame(worksheet.get_all_records())
78
+ load_display.replace('', np.nan, inplace=True)
79
+ raw_display = load_display.dropna(subset=['PPR'])
80
+ raw_display.rename(columns={"name": "Player", "PPR": "Median"}, inplace = True)
81
+ raw_display = raw_display[['Player', 'Salary', 'Position', 'Team', 'Opp', 'Median', 'Own', 'rush_yards', 'rec']]
82
+ dk_roo_raw_3 = raw_display.loc[raw_display['Median'] > 0]
83
+
84
+ worksheet = sh.worksheet('FD_SD_Projections_3')
85
+ load_display = pd.DataFrame(worksheet.get_all_records())
86
+ load_display.replace('', np.nan, inplace=True)
87
+ raw_display = load_display.dropna(subset=['Half_PPR'])
88
+ raw_display.rename(columns={"name": "Player", "Half_PPR": "Median"}, inplace = True)
89
+ raw_display = raw_display[['Player', 'Salary', 'Position', 'Team', 'Opp', 'Median', 'Own', 'rush_yards', 'rec']]
90
+ fd_roo_raw_3 = raw_display.loc[raw_display['Median'] > 0]
91
+
92
+ worksheet = sh.worksheet('SD_Projections')
93
+ load_display = pd.DataFrame(worksheet.get_all_records())
94
+ load_display.replace('', np.nan, inplace=True)
95
+ load_display.rename(columns={"PPR": "Median", "name": "Player"}, inplace = True)
96
+ raw_display = load_display.dropna(subset=['Median'])
97
+ dk_ids = dict(zip(raw_display['Player'], raw_display['player_id']))
98
+
99
+ worksheet = sh.worksheet('FD_SD_Projections')
100
+ load_display = pd.DataFrame(worksheet.get_all_records())
101
+ load_display.replace('', np.nan, inplace=True)
102
+ load_display.rename(columns={"Half_PPR": "Median", "name": "Player"}, inplace = True)
103
  raw_display = load_display.dropna(subset=['Median'])
104
+ fd_ids = dict(zip(raw_display['Player'], raw_display['player_id']))
105
 
106
+ return dk_roo_raw, dk_roo_raw_2, dk_roo_raw_3, fd_roo_raw, fd_roo_raw_2, fd_roo_raw_3, dk_ids, fd_ids
107
 
108
+ dk_roo_raw, dk_roo_raw_2, dk_roo_raw_3, fd_roo_raw, fd_roo_raw_2, fd_roo_raw_3, dkid_dict, fdid_dict = init_baselines()
 
 
 
109
 
110
  static_exposure = pd.DataFrame(columns=['Player', 'count'])
111
  overall_exposure = pd.DataFrame(columns=['Player', 'count'])
 
602
  st.cache_data.clear()
603
  for key in st.session_state.keys():
604
  del st.session_state[key]
605
+ dk_roo_raw, dk_roo_raw_2, dk_roo_raw_3, fd_roo_raw, fd_roo_raw_2, fd_roo_raw_3, dkid_dict, fdid_dict = init_baselines()
 
 
 
606
 
607
+ slate_var1 = st.radio("Which data are you loading?", ('Paydirt (Main)', 'Paydirt (Secondary)', 'Paydirt (Third)', 'User'))
608
  site_var1 = 'Draftkings'
609
  if site_var1 == 'Draftkings':
610
  if slate_var1 == 'User':
 
613
  raw_baselines = dk_roo_raw
614
  elif slate_var1 == 'Paydirt (Secondary)':
615
  raw_baselines = dk_roo_raw_2
616
+ elif slate_var1 == 'Paydirt (Third)':
617
+ raw_baselines = dk_roo_raw_3
618
  elif site_var1 == 'Fanduel':
619
  if slate_var1 == 'User':
620
  raw_baselines = proj_dataframe
 
622
  raw_baselines = dk_roo_raw
623
  elif slate_var1 == 'Paydirt (Secondary)':
624
  raw_baselines = dk_roo_raw_2
625
+ elif slate_var1 == 'Paydirt (Third)':
626
+ raw_baselines = dk_roo_raw_3
627
 
628
  st.info("If you are uploading a portfolio, note that there is an adjustments to projections and deviation mapping to prevent 'Projection Bias' and create a fair simulation")
629
  insert_port1 = st.selectbox("Are you uploading a portfolio?", ('No', 'Yes'))