# importing the relevent libraris
import random
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style='whitegrid')

## generaing random 9000 integers
population = [random.randint(0, 9000) for x in range(9000)]

sample_means = []
for x in range(3000):
    
    # radomly picking up 30 values from population for each iteration
    sample = random.sample(population, 30)
    
    # finding the mean = (sum/count)
    mean = sum(sample)/30
    
    # appending the list with means
    sample_means.append(mean)

# Distribution for population data
sns.distplot(population)
plt.title("Population")
plt.show()

# Distribution for sample data
sns.distplot(sample_means)
plt.title("sample")
plt.show()