pgf

csv_file = ''
df = pd.read_csv(csv_file, header=1)
gcd_dict = {}
for name, group in df.groupby(df.columns[0]):
    things = name.split('_')
    if not things[0].startswith('GN'):
        continue
    print(things)
    if things[0] == 'GNR':
        if group.GCD_S.mean() == 0:
            S = 0
        else:
            S = group.GCD_S.mean()
        gcd_dict[name] = [group.GCD_P.mean(), group.GCD_E.mean(),
                          S]
#     if name.split('_')[-2] == '2' and name.split('_')[-1] == '0.25':
#         if group.GCD_S.mean() == 0:
#             S = 0
#         else:
#             S = group.GCD_S.mean()
#         gcd_dict[name] = [group.GCD_P.mean(), group.GCD_E.mean(),
#                           S]

for key, val in sorted(gcd_dict.items(), key=lambda x: int(x[0].split('_')[1])):
    print(f'(10, {val[1]}) +- (0, 0)')