python 拟合泊松分布 numpy 泊松分布

# Draw 10,000 samples out of Poisson distribution: samples_poisson
samples_poisson=np.random.poisson(10,size=10000)

# Print the mean and standard deviation
print('Poisson:     ', np.mean(samples_poisson),
                       np.std(samples_poisson))

# Specify values of n and p to consider for Binomial: n, p
n=[20,100,1000]
p=[0.5,0.1,0.01]

# Draw 10,000 samples for each n,p pair: samples_binomial
for i in range(3):
    samples_binomial = np.random.binomial(n[i],p[i],size=10000)

    # Print results
    print('n =', n[i], 'Binom:', np.mean(samples_binomial),
                                 np.std(samples_binomial))

关于二项分布与泊松分布的一些解释：

https://www.zhihu.com/question/36214010/answer/208718886

# Draw 10,000 samples out of Poisson distribution: n_nohitters
n_nohitters=np.random.poisson(251/115,size=10000)

# Compute number of samples that are seven or greater: n_large
n_large = np.sum(n_nohitters>=7)
#n_large = len(n_nohitters[n_nohitters>=7])

# Compute probability of getting seven or more: p_large
p_large=n_large/10000

# Print the result
print('Probability of seven or more no-hitters:', p_large)

注：np.sum()用的很好，值得借鉴