python绘制正态分布

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

fig, ax = plt.subplots(1, 1)

# loc：均值 scale：标准差
loc=1
scale=2

# 均值, 方差, 偏度, 峰度
mean, var, skew, kurt = norm.stats(loc,scale,moments='mvsk')

# ppf：累积分布函数的反函数。q=0.01时，ppf就是p(X<x)=0.01时对应的x值。
x = np.linspace(norm.ppf(0.01,loc,scale),

                norm.ppf(0.99,loc,scale), 100)

ax.plot(x, norm.pdf(x,loc,scale),

       'r-', lw=5, alpha=0.6, label='norm pdf')

 

 

 

 

特殊情形：

fig, ax = plt.subplots(1, 1)
mean, var, skew, kurt = norm.stats(moments='mvsk')
x = np.linspace(norm.ppf(0.01),

                norm.ppf(0.99), 100)

ax.plot(x, norm.pdf(x),

       'r-', lw=5, alpha=0.6, label='norm pdf')

 

 

 

 参考博客：https://blog.csdn.net/data_cola/article/details/116026018