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