Процедурой бутстреп создайте 10 подвыборок и для каждой найдите 0.99-квантиль. Напечатайте их на экране через перенос строки.

Изучите функцию quantile() (англ. «квантиль значений») у объектов pandas.Series.

import pandas as pd
import numpy as np

data = pd.Series([
    10.7 ,  9.58,  7.74,  8.3 , 11.82,  9.74, 10.18,  8.43,  8.71,
     6.84,  9.26, 11.61, 11.08,  8.94,  8.44, 10.41,  9.36, 10.85,
    10.41,  8.37,  8.99, 10.17,  7.78, 10.79, 10.61, 10.87,  7.43,
     8.44,  9.44,  8.26,  7.98, 11.27, 11.61,  9.84, 12.47,  7.8 ,
    10.54,  8.99,  7.33,  8.55,  8.06, 10.62, 10.41,  9.29,  9.98,
     9.46,  9.99,  8.62, 11.34, 11.21, 15.19, 20.85, 19.15, 19.01,
    15.24, 16.66, 17.62, 18.22, 17.2 , 15.76, 16.89, 15.22, 18.7 ,
    14.84, 14.88, 19.41, 18.54, 17.85, 18.31, 13.68, 18.46, 13.99,
    16.38, 16.88, 17.82, 15.17, 15.16, 18.15, 15.08, 15.91, 16.82,
    16.85, 18.04, 17.51, 18.44, 15.33, 16.07, 17.22, 15.9 , 18.03,
    17.26, 17.6 , 16.77, 17.45, 13.73, 14.95, 15.57, 19.19, 14.39,
    15.76])

state = np.random.RandomState(12345)

for i in range(10):
    subsample = data.sample(frac=1, replace=True, random_state=state)
    print(subsample.quantile(0.99))

Результат

19.192200000000003
20.85
19.20660000000001
19.028400000000012
19.42440000000001
19.42440000000001
20.85
19.42440000000001
19.42440000000001
19.19