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James McCool commited on
Commit
7fecbe2
·
1 Parent(s): fd6e941

cleaned up some data parsing

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Files changed (1) hide show
  1. app.py +10 -56
app.py CHANGED
@@ -520,99 +520,53 @@ 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
 
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]
535
- st.table(prop_df)
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]
546
- st.table(prop_df)
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]
557
- st.table(prop_df)
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]
568
- st.table(prop_df)
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]
579
- st.table(prop_df)
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]
590
- st.table(prop_df)
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]
601
- st.table(prop_df)
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]
612
- st.table(prop_df)
613
- prop_df['Over'] = 1 / prop_df['over_line']
614
- prop_df['Under'] = 1 / prop_df['under_line']
615
- df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
 
616
 
617
  prop_dict = dict(zip(df.Player, df.Prop))
618
  book_dict = dict(zip(df.Player, df.book))
 
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 = prop_df_raw.rename(columns={"Full_name": "Player"})
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
+
530
  if prop_type_var == "NBA_GAME_PLAYER_POINTS":
531
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS']
532
  elif prop_type_var == "Points":
533
  prop_df = prop_df.loc[prop_df['prop_type'] == 'Points']
 
 
 
 
 
 
 
534
  elif prop_type_var == "NBA_GAME_PLAYER_REBOUNDS":
535
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_REBOUNDS']
536
  elif prop_type_var == "Rebounds":
537
  prop_df = prop_df.loc[prop_df['prop_type'] == 'Rebounds']
 
 
 
 
 
 
 
538
  elif prop_type_var == "NBA_GAME_PLAYER_ASSISTS":
539
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_ASSISTS']
540
  elif prop_type_var == "Assists":
541
  prop_df = prop_df.loc[prop_df['prop_type'] == 'Assists']
 
 
 
 
 
 
 
542
  elif prop_type_var == "NBA_GAME_PLAYER_3_POINTERS_MADE":
543
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_3_POINTERS_MADE']
544
  elif prop_type_var == "3-Pointers Made":
545
  prop_df = prop_df.loc[prop_df['prop_type'] == '3-Pointers Made']
 
 
 
 
 
 
 
546
  elif prop_type_var == "NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS":
547
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS']
548
  elif prop_type_var == "Points + Rebounds + Assists":
549
  prop_df = prop_df.loc[prop_df['prop_type'] == 'Points + Rebounds + Assists']
 
 
 
 
 
 
 
550
  elif prop_type_var == "NBA_GAME_PLAYER_POINTS_REBOUNDS":
551
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_REBOUNDS']
552
  elif prop_type_var == "Points + Rebounds":
553
  prop_df = prop_df.loc[prop_df['prop_type'] == 'Points + Rebounds']
 
 
 
 
 
 
 
554
  elif prop_type_var == "NBA_GAME_PLAYER_POINTS_ASSISTS":
555
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_ASSISTS']
556
  elif prop_type_var == "Points + Assists":
557
  prop_df = prop_df.loc[prop_df['prop_type'] == 'Points + Assists']
 
 
 
 
 
 
 
558
  elif prop_type_var == "NBA_GAME_PLAYER_REBOUNDS_ASSISTS":
559
  prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_REBOUNDS_ASSISTS']
560
  elif prop_type_var == "Assists + Rebounds":
561
  prop_df = prop_df.loc[prop_df['prop_type'] == 'Assists + Rebounds']
562
+
563
+ prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
564
+ prop_df = prop_df.rename(columns={"over_prop": "Prop"})
565
+ prop_df = prop_df.loc[prop_df['Prop'] != 0]
566
+ st.table(prop_df)
567
+ prop_df['Over'] = 1 / prop_df['over_line']
568
+ prop_df['Under'] = 1 / prop_df['under_line']
569
+ df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
570
 
571
  prop_dict = dict(zip(df.Player, df.Prop))
572
  book_dict = dict(zip(df.Player, df.book))