topaz badge
for info in main_text.split('\n')[1:]:
sub_info = info.split('\t')
print(sub_info)
info_dict[sub_info[0]] = {base_heading[sub_info.index(key)]:key for key in sub_info[1:]}
```
What this is doing is allocating the numbers in a list to a dictionary which describes what those numbers indicate. Here, base_heading is
```py
base_heading = ['PLAYER', 'TEAM', 'GP', 'W', 'L', 'MIN', 'DRIVES', 'FGM', 'FGA', 'FG%', 'FTM', 'FTA', 'FT%', 'PTS', 'PTS%', 'PASS', 'PASS%', 'AST', 'AST%', 'TO', 'TOV%', 'PF', 'PF%']
So the problem here is that it misbehaves for a specifc column. As we can see:
['Jalen Williams', 'OKC', '60', '48', '12', '32.5', '13.3', '3.2', '6.7', '46.8', '1.7', '2.1', '79.7', '8.2', '61.7', '4.4', '33.0', '1.5', '10.9', '0.7', '5.0', '1.1', '8.1']
{'TEAM': 'OKC', 'GP': '60', 'W': '48', 'L': '12', 'MIN': '32.5', 'DRIVES': '13.3', 'FGM': '3.2', 'FGA': '6.7', 'FG%': '46.8', 'FTM': '1.7', 'FTA': '2.1', 'FT%': '79.7', 'PTS': '8.2', 'PTS%': '61.7', 'PASS': '4.4', 'PASS%': '33.0', 'AST': '1.5', 'AST%': '10.9', 'TO': '0.7', 'TOV%': '5.0', 'PF': '1.1', 'PF%': '8.1'}
['Deni Avdija', 'POR', '65', '31', '34', '29.3', '9.9', '2.0', '3.5', '56.4', '1.6', '2.0', '79.1', '5.7', '57.6', '4.4', '44.1', '1.0', '9.8', '0.8', '7.6', '1.0', '10.2']
{'TEAM': 'POR', 'GP': '65', 'W': '31', 'L': '34', 'MIN': '29.3', 'DRIVES': '9.9', 'FGM': '2.0', 'FGA': '3.5', 'FG%': '56.4', 'FTM': '1.6', 'FT%': '79.1', 'PTS': '5.7', 'PTS%': '57.6', 'PASS': '4.4', 'PASS%': '44.1', 'AST': '1.0', 'AST%': '9.8', 'TO': '0.8', 'TOV%': '7.6', 'PF%': '10.2'}
For somereason it decides to skip the PF on Deni Avidja's column and because of that it throws off the dictionary. This is even more weird because after 10.2, it's literally 1.0 but it decides to completely ignore it.
leaden sleet
