Essayez d'utiliser pd.read_csv : 

url = "https://gladys.geog.ucl.ac.uk/bikesapi/load.php?scheme=saopaulo"

df = pd.read_csv(url)
print(df.head())

Résultat de sortie :

   #id timestamp|gmt_local_diff_sec|gmt_servertime_diff_sec                   name        lat        lon  bikes  spaces  installed  locked  temporary  total_docks  givesbonus_acceptspedelecs_fbbattlevel  pedelecs
0    1                               1692123219|10800|-3600    1 - Largo da Batata -23.566831 -46.693741     43      37       True   False      False           83                                     NaN        10
1    3                               1692123219|10800|-3600     3 - CPTM Pinheiros -23.566478 -46.701258      6       7       True   False      False           15                                     NaN         3
2    4                               1692123219|10800|-3600  4 - Rua Diogo Moreira -23.569145 -46.692003      2      20       True   False      False           23                                     NaN         2
3    5                               1692123219|10800|-3600        5 - Chicão Vive -23.569894 -46.697897      4       7       True   False      False           11                                     NaN         1
4    6                               1692123219|10800|-3600        6 - Rua Manduri -23.572137 -46.690107     10       7       True   False      False           19                                     NaN         0