James McCool commited on
Commit
fd6e941
1 Parent(s): 5b60329

adjusted some pick6 objects and variables

Browse files
Files changed (1) hide show
  1. app.py +32 -17
app.py CHANGED
@@ -439,21 +439,21 @@ with tab5:
439
 
440
  df.replace("", 0, inplace=True)
441
 
442
- if prop == "NBA_GAME_PLAYER_POINTS":
443
  df['Median'] = df['Points']
444
- elif prop == "NBA_GAME_PLAYER_REBOUNDS":
445
  df['Median'] = df['Rebounds']
446
- elif prop == "NBA_GAME_PLAYER_ASSISTS":
447
  df['Median'] = df['Assists']
448
- elif prop == "NBA_GAME_PLAYER_3_POINTERS_MADE":
449
  df['Median'] = df['3P']
450
- elif prop == "NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS":
451
  df['Median'] = df['PRA']
452
- elif prop == "NBA_GAME_PLAYER_POINTS_REBOUNDS":
453
  df['Median'] = df['Points'] + df['Rebounds']
454
- elif prop == "NBA_GAME_PLAYER_POINTS_ASSISTS":
455
  df['Median'] = df['Points'] + df['Assists']
456
- elif prop == "NBA_GAME_PLAYER_REBOUNDS_ASSISTS":
457
  df['Median'] = df['Rebounds'] + df['Assists']
458
 
459
  flex_file = df
@@ -520,14 +520,15 @@ with tab5:
520
  prop_df_raw = prop_frame[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
521
  elif game_select_var == 'Pick6':
522
  prop_df_raw = pick_frame[['Full_name', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
523
- prop_df_raw.rename(columns={"Full_name": "Player"}, inplace = True)
524
 
525
  for books in ['FANDUEL', 'DRAFTKINGS', 'BET365', 'CONSENSUS']:
526
  if game_select_var == 'Pick6':
527
  books = 'Pick6'
528
  prop_df = prop_df_raw.loc[prop_df_raw['book'] == books]
529
- if prop_type_var == "NBA_GAME_PLAYER_POINTS" or prop_type_var == "Points":
530
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS']
 
 
531
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
532
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
533
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -535,8 +536,10 @@ with tab5:
535
  prop_df['Over'] = 1 / prop_df['over_line']
536
  prop_df['Under'] = 1 / prop_df['under_line']
537
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
538
- elif prop_type_var == "NBA_GAME_PLAYER_REBOUNDS" or prop_type_var == "Rebounds":
539
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_REBOUNDS']
 
 
540
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
541
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
542
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -544,8 +547,10 @@ with tab5:
544
  prop_df['Over'] = 1 / prop_df['over_line']
545
  prop_df['Under'] = 1 / prop_df['under_line']
546
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
547
- elif prop_type_var == "NBA_GAME_PLAYER_ASSISTS" or prop_type_var == "Assists":
548
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_ASSISTS']
 
 
549
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
550
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
551
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -553,8 +558,10 @@ with tab5:
553
  prop_df['Over'] = 1 / prop_df['over_line']
554
  prop_df['Under'] = 1 / prop_df['under_line']
555
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
556
- elif prop_type_var == "NBA_GAME_PLAYER_3_POINTERS_MADE" or prop_type_var == "3-Pointers Made":
557
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_3_POINTERS_MADE']
 
 
558
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
559
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
560
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -562,8 +569,10 @@ with tab5:
562
  prop_df['Over'] = 1 / prop_df['over_line']
563
  prop_df['Under'] = 1 / prop_df['under_line']
564
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
565
- elif prop_type_var == "NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS" or prop_type_var == "Points + Rebounds + Assists":
566
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS']
 
 
567
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
568
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
569
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -571,8 +580,10 @@ with tab5:
571
  prop_df['Over'] = 1 / prop_df['over_line']
572
  prop_df['Under'] = 1 / prop_df['under_line']
573
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
574
- elif prop_type_var == "NBA_GAME_PLAYER_POINTS_REBOUNDS" or prop_type_var == "Points + Rebounds":
575
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_REBOUNDS']
 
 
576
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
577
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
578
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -580,8 +591,10 @@ with tab5:
580
  prop_df['Over'] = 1 / prop_df['over_line']
581
  prop_df['Under'] = 1 / prop_df['under_line']
582
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
583
- elif prop_type_var == "NBA_GAME_PLAYER_POINTS_ASSISTS" or prop_type_var == "Points + Assists":
584
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_ASSISTS']
 
 
585
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
586
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
587
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -589,8 +602,10 @@ with tab5:
589
  prop_df['Over'] = 1 / prop_df['over_line']
590
  prop_df['Under'] = 1 / prop_df['under_line']
591
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
592
- elif prop_type_var == "NBA_GAME_PLAYER_REBOUNDS_ASSISTS" or prop_type_var == "Assists + Rebounds":
593
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_REBOUNDS_ASSISTS']
 
 
594
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
595
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
596
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
 
439
 
440
  df.replace("", 0, inplace=True)
441
 
442
+ if prop == "NBA_GAME_PLAYER_POINTS" or prop == "Points":
443
  df['Median'] = df['Points']
444
+ elif prop == "NBA_GAME_PLAYER_REBOUNDS" or prop == "Rebounds":
445
  df['Median'] = df['Rebounds']
446
+ elif prop == "NBA_GAME_PLAYER_ASSISTS" or prop == "Assists":
447
  df['Median'] = df['Assists']
448
+ elif prop == "NBA_GAME_PLAYER_3_POINTERS_MADE" or prop == "3-Pointers Made":
449
  df['Median'] = df['3P']
450
+ elif prop == "NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS" or prop == "Points + Rebounds + Assists":
451
  df['Median'] = df['PRA']
452
+ elif prop == "NBA_GAME_PLAYER_POINTS_REBOUNDS" or prop == "Points + Rebounds":
453
  df['Median'] = df['Points'] + df['Rebounds']
454
+ elif prop == "NBA_GAME_PLAYER_POINTS_ASSISTS" or prop == "Points + Assists":
455
  df['Median'] = df['Points'] + df['Assists']
456
+ elif prop == "NBA_GAME_PLAYER_REBOUNDS_ASSISTS" or prop == "Assists + Rebounds":
457
  df['Median'] = df['Rebounds'] + df['Assists']
458
 
459
  flex_file = df
 
520
  prop_df_raw = prop_frame[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
521
  elif game_select_var == 'Pick6':
522
  prop_df_raw = pick_frame[['Full_name', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
 
523
 
524
  for books in ['FANDUEL', 'DRAFTKINGS', 'BET365', 'CONSENSUS']:
525
  if game_select_var == 'Pick6':
526
  books = 'Pick6'
527
  prop_df = prop_df_raw.loc[prop_df_raw['book'] == books]
528
+ if prop_type_var == "NBA_GAME_PLAYER_POINTS":
529
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS']
530
+ elif prop_type_var == "Points":
531
+ prop_df = prop_df.loc[prop_df['prop_type'] == 'Points']
532
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
533
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
534
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
 
536
  prop_df['Over'] = 1 / prop_df['over_line']
537
  prop_df['Under'] = 1 / prop_df['under_line']
538
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
539
+ elif prop_type_var == "NBA_GAME_PLAYER_REBOUNDS":
540
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_REBOUNDS']
541
+ elif prop_type_var == "Rebounds":
542
+ prop_df = prop_df.loc[prop_df['prop_type'] == 'Rebounds']
543
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
544
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
545
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
 
547
  prop_df['Over'] = 1 / prop_df['over_line']
548
  prop_df['Under'] = 1 / prop_df['under_line']
549
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
550
+ elif prop_type_var == "NBA_GAME_PLAYER_ASSISTS":
551
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_ASSISTS']
552
+ elif prop_type_var == "Assists":
553
+ prop_df = prop_df.loc[prop_df['prop_type'] == 'Assists']
554
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
555
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
556
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
 
558
  prop_df['Over'] = 1 / prop_df['over_line']
559
  prop_df['Under'] = 1 / prop_df['under_line']
560
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
561
+ elif prop_type_var == "NBA_GAME_PLAYER_3_POINTERS_MADE":
562
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_3_POINTERS_MADE']
563
+ elif prop_type_var == "3-Pointers Made":
564
+ prop_df = prop_df.loc[prop_df['prop_type'] == '3-Pointers Made']
565
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
566
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
567
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
 
569
  prop_df['Over'] = 1 / prop_df['over_line']
570
  prop_df['Under'] = 1 / prop_df['under_line']
571
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
572
+ elif prop_type_var == "NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS":
573
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS']
574
+ elif prop_type_var == "Points + Rebounds + Assists":
575
+ prop_df = prop_df.loc[prop_df['prop_type'] == 'Points + Rebounds + Assists']
576
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
577
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
578
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
 
580
  prop_df['Over'] = 1 / prop_df['over_line']
581
  prop_df['Under'] = 1 / prop_df['under_line']
582
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
583
+ elif prop_type_var == "NBA_GAME_PLAYER_POINTS_REBOUNDS":
584
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_REBOUNDS']
585
+ elif prop_type_var == "Points + Rebounds":
586
+ prop_df = prop_df.loc[prop_df['prop_type'] == 'Points + Rebounds']
587
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
588
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
589
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
 
591
  prop_df['Over'] = 1 / prop_df['over_line']
592
  prop_df['Under'] = 1 / prop_df['under_line']
593
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
594
+ elif prop_type_var == "NBA_GAME_PLAYER_POINTS_ASSISTS":
595
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_ASSISTS']
596
+ elif prop_type_var == "Points + Assists":
597
+ prop_df = prop_df.loc[prop_df['prop_type'] == 'Points + Assists']
598
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
599
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
600
  prop_df = prop_df.loc[prop_df['Prop'] != 0]
 
602
  prop_df['Over'] = 1 / prop_df['over_line']
603
  prop_df['Under'] = 1 / prop_df['under_line']
604
  df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
605
+ elif prop_type_var == "NBA_GAME_PLAYER_REBOUNDS_ASSISTS":
606
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_REBOUNDS_ASSISTS']
607
+ elif prop_type_var == "Assists + Rebounds":
608
+ prop_df = prop_df.loc[prop_df['prop_type'] == 'Assists + Rebounds']
609
  prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
610
  prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
611
  prop_df = prop_df.loc[prop_df['Prop'] != 0]