from numpy import random, mean
from matplotlib import pyplot
import random
 
 
def sample_distribution(sample_size, filename, number_of_samples=1000):
    samples = [[random.randint(1, 6) for _ in range(sample_size)] for _ in range(number_of_samples)]
    means = list()
    for i in range(0, number_of_samples):
        means.append(mean(samples[i]))
 
    pyplot.hist(means)
    pyplot.savefig(filename)
    pyplot.close()
 
    return(mean(means))
 
 
mean_1 = sample_distribution(1, "means_1.png")
print(mean_1)
mean_2 = sample_distribution(2, "means_2.png")
print(mean_2)
mean_5 = sample_distribution(5, "means_5.png")
print(mean_5)
mean_10 = sample_distribution(10, "means_10.png")
print(mean_10)
mean_20 = sample_distribution(20, "means_20.png")
print(mean_20)
mean_30 = sample_distribution(30, "means_30.png")
print(mean_30)
mean_40 = sample_distribution(40, "means_40.png")
print(mean_40)
mean_50 = sample_distribution(50, "means_50.png")
print(mean_50)
 
 
s = [random.randint(1, 6) for _ in range(100000)]
pyplot.hist(s)
pyplot.savefig("distribution_of_population.png")