import numpy as np

import pandas as pd

import math

import time

n = 10000

for i in range(9):

sample_n = 2**i * 40

print(sample_n)

normally_dist = np.random.randn(sample_n)

rep_count = math.ceil(n / sample_n)

normally_dist = np.repeat(normally_dist, rep_count)

# limit

normally_dist = normally_dist[0:n]

sheet("A1", pd.DataFrame(normally_dist))

time.sleep(1)