In [24]:
%load_ext autoreload
%autoreload 2

import matplotlib.pyplot as plt
%matplotlib inline
from central_limit_theorem import *

sample_sizes = [1, 2, 10, 100, 1000, 10000]
number_of_samples = 10000

for i, sample_size in enumerate(sample_sizes):
    means = clt(sample_size=sample_size, number_of_samples=number_of_samples)
#     print(means)
    plt.subplot(len(sample_sizes), 1, i+1)
    plt.hist(means, bins='auto')
The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload
In [35]:
%load_ext autoreload
%autoreload 2

import matplotlib.pyplot as plt
%matplotlib inline
from central_limit_theorem import *

sample_sizes = [1000]
number_of_samples = 10000

for i, sample_size in enumerate(sample_sizes):
    means = clt(sample_size=sample_size, number_of_samples=number_of_samples)
#     print(means)
    plt.subplot(len(sample_sizes), 1, i+1)
    plt.hist(means, bins='auto')
The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload