说明

将数据生成直方图，观测是否符合正态分布，来进行检验

代码

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# 随机数据
# s = pd.DataFrame(np.random.randn(1000)+10,columns = ['value'])
# 指定数据
x = [84.5,79.5,84.5,84.5,84.5,0,84.5,84.5,84.5,75.8,80.5,84.5,70.3,84.5,75.4,84.5,78.5,84.5,76,84.5,75.6,84.5,84.5,84.5,92.8,84.5,84.5,84.5,84.5,84.5,84.5,93,0,84.5,84.5,84.5,0,84.5,84.5,84.5,84.5,84.5,79.5,90.2,84.5,84.5]
s = pd.DataFrame(x,columns = ['value'])
print(s.head())
# 创建随机数据

fig = plt.figure(figsize = (10,6))
ax1 = fig.add_subplot(2,1,1)  # 创建子图1
ax1.scatter(s.index, s.values)
plt.grid()
# 绘制数据分布图

ax2 = fig.add_subplot(2,1,2)  # 创建子图2
s.hist(bins=30,alpha = 0.5,ax = ax2)
s.plot(kind = 'kde', secondary_y=True,ax = ax2)
plt.grid()
plt.show()
# 绘制直方图
# 呈现较明显的正太性

执行结果：

参考：
https://www.cnblogs.com/Renyi-Fan/p/13282262.html