使用Matplotlib绘制正态分布

Question

请帮我绘制下面数据的正态分布:

数据:

import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm

h = [186, 176, 158, 180, 186, 168, 168, 164, 178, 170, 189, 195, 172,
     187, 180, 186, 185, 168, 179, 178, 183, 179, 170, 175, 186, 159,
     161, 178, 175, 185, 175, 162, 173, 172, 177, 175, 172, 177, 180]

std = np.std(h) 
mean = np.mean(h)    
plt.plot(norm.pdf(h,mean,std))

输出:

Standard Deriviation = 8.54065575872 
mean = 176.076923077

情节不正确,我的代码出了什么问题？

Answer 1

您可以尝试hist将数据信息与拟合曲线一起使用,如下所示:

import numpy as np
import scipy.stats as stats
import pylab as pl

h = sorted([186, 176, 158, 180, 186, 168, 168, 164, 178, 170, 189, 195, 172,
     187, 180, 186, 185, 168, 179, 178, 183, 179, 170, 175, 186, 159,
     161, 178, 175, 185, 175, 162, 173, 172, 177, 175, 172, 177, 180])  #sorted

fit = stats.norm.pdf(h, np.mean(h), np.std(h))  #this is a fitting indeed

pl.plot(h,fit,'-o')

pl.hist(h,normed=True)      #use this to draw histogram of your data

pl.show()                   #use may also need add this 

Answer 2

假设你norm来自scipy.stats,你可能只需要对列表进行排序:

import numpy as np
import scipy.stats as stats
import matplotlib.pyplot as plt

h = [186, 176, 158, 180, 186, 168, 168, 164, 178, 170, 189, 195, 172,
     187, 180, 186, 185, 168, 179, 178, 183, 179, 170, 175, 186, 159,
     161, 178, 175, 185, 175, 162, 173, 172, 177, 175, 172, 177, 180]
h.sort()
hmean = np.mean(h)
hstd = np.std(h)
pdf = stats.norm.pdf(h, hmean, hstd)
plt.plot(h, pdf) # including h here is crucial

所以我得到: