python数据分布_数据分布-Python实战

一、正态分布

import numpy as np

import matplotlib.pyplot as plt

import matplotlib.mlab as mlab

from scipy.stats import normaltest

data = np.loadtxt('http://jse.amstat.org/datasets/normtemp.dat.txt')

Temperature = []

for i in range(len(data)):

Temperature.append(float(str(data[i]).split()[0].split('[')[1]))

print(Temperature)

mu = np.mean(Temperature)

sigma = np.std(Temperature)

n, bins, patches = plt.hist(Temperature, normed=True, histtype='bar',bins='auto', color='#0504aa', rwidth=0.85)

y = mlab.normpdf(bins, mu, sigma)

plt.plot(bins,y,'r--', linewidth=1)

plt.title('Temperature distribution')

plt.xlabel('Temperature')

plt.ylabel('Probability')

plt.show()

print(normaltest(Temperature, axis=0))

二、常见数据分布

# coding = utf-8

import matplotlib.pyplot as plt

from scipy.stats import binom

import numpy as np

from pylab import mpl

from matplotlib.font_manager import _rebuild

_rebuild()

mpl.rcParams['font.sans-serif']=[u'SimHei']

mpl.rcParams['axes.unicode_minus']=False

# #二项分布

# n = 100

# p = 0.5

# mean, var, skew, kurt = binom.stats(n, p, moments= 'mvsk')

# x = np.arange(binom.ppf(0.01,n,p),binom.ppf(0.99,n,p))

# plt.plot(x, binom.pmf(x, n, p), 'o')

# plt.title(u"二项分布")

# plt.show()

# #泊松分布

# from scipy.stats import poisson

# mu = 10

# mean, var, skew, kurt = poisson.stats(mu, moments='mvsk')

# x = np.arange(poisson.ppf(0.01,mu),poisson.ppf(0.99,mu))

# plt.plot(x, poisson.pmf(x, mu), 'o')

# plt.title(u'泊松分布')

# plt.show()

# #均匀分布

# from scipy.stats import uniform

# loc = 1

# scale = 1

# mean, var, skew, kurt = uniform.stats(loc,scale, moments = 'mvsk')

# x = np.linspace(uniform.ppf(0.01, loc, scale), uniform.ppf(0.99, loc, scale), 100)

# plt.plot(x, uniform.pdf(x, loc, scale), 'b-', label ='uniform')

# plt.title(u'均匀分布')

# plt.show()