# Draw 100000 samples from Normal distribution with stds of interest: samples_std1, samples_std3, samples_std10
samples_std1 = np.random.normal(20, 1, size=100000) 
samples_std3 = np.random.normal(20, 3, size=100000) 
samples_std10 = np.random.normal(20, 10, size=100000) 

# Make histograms
_ = plt.hist(samples_std1, 100, normed=True, histtype='step')
_ = plt.hist(samples_std3, 100, normed=True, histtype='step')
_ = plt.hist(samples_std10, 100, normed=True, histtype='step')

# Make a legend, set limits and show plot
_ = plt.legend(('std = 1', 'std = 3', 'std = 10'))
plt.ylim(-0.01, 0.42)
plt.show()
