请帮我绘制以下数据的正态分布:
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,我的代码有什么问题吗?
pylab
matplotlib.pyplot
您可以尝试将hist数据信息与拟合曲线一起放置,如下所示:
hist
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