Tejesh-Raut

import matplotlib.pyplot as plt

cos_analytical_value = np.sin(2)

plt.plot([cos_analytical_value]*50)
plt.plot(mcos_estimates, '.')
plt.plot(cos_analytical_value + np.array(mcos_std)*3, 'r')
plt.plot(cos_analytical_value - np.array(mcos_std)*3, 'r')
plt.xlabel('Sample size')
plt.ylabel('Monte Carlo estimate')

Tejesh-Raut

import numpy as np
from scipy.stats import uniform

np.random.seed(0)

mcos_estimates = [None]*50
mcos_std = [None]*50

for i in range(1,51):
    unif_array = uniform.rvs(size = i*1000)*2