central_limit_theorem.py

import numpy as np
import matplotlib.pyplot as plt

# generate random data and plot them
data = np.random.random_integers(10, 20, 100)
num, count = np.unique(data, return_counts=True)
plt.plot(num, count)

each_sample_size = 10
sample_size = 500
sample_average = []

for i in range(sample_size):    
    sample_average.append(np.random.choice(data, each_sample_size).mean())
    
# generate normal distributed plot 
mean, mean_count = np.unique(sample_average, return_counts=True)
plt.plot(mean, mean_count)