from scipy.stats import binom, norm, beta, expon
import numpy as np
import matplotlib.pyplot as plt
#泊松分佈
x = np.random.poisson(lam=34.7, size=10000)  
pillar = 100
a = plt.hist(x, bins=pillar, color='black', alpha=0.5)
plt.xlabel((u'頻數'))
plt.ylabel(u'頻數出現數目')
plt.grid()
plt.show()
#負二項分佈
from scipy.stats import nbinom
help(nbinom)
p=0.055
r=2.1734
x = nbinom.rvs(r, p, size=10000)
pillar = 50
a = plt.hist(x, bins=pillar)
plt.xlabel((u'頻數'))
plt.ylabel(u'頻數出現數目')
plt.grid()
plt.show()