如何用matplotlib在方框图中显示低于平均值和高于平均值的标准偏差

Question

我试图用matplotlib在一个方框图中显示一个高于或低于一个数据列表平均值的标准偏差。我能知道怎么认识吗 使用boxBy Plot（）？或者其他任何方法都能做到？

Answer 1

我想出来了，应该是这样的：

import matplotlib.pyplot as plt
import numpy as np

data_to_plot = [[0.61,0.62,0.6,0.62,0.64,0.63,0.61,0.6,0.57,0.62,0.6,0.62,0.6,0.64,0.61,0.6,0.64,0.58,0.6,0.62],
                [0.66,0.63,0.63,0.64,0.62,0.67,0.62,0.68,0.58,0.64,0.6,0.64,0.57,0.63,0.59,0.64,0.61,0.58,0.63,0.67],
                [0.6,0.58,0.59,0.6,0.61,0.57,0.63,0.6,0.57,0.6,0.6,0.6,0.61,0.59,0.59,0.59,0.64,0.59,0.58,0.62],
                [0.84,0.77,0.83,0.84,0.76,0.74,0.81,0.8,0.83,0.74,0.82,0.8,0.8,0.78,0.81,0.73,0.79,0.8,0.74,0.69]]

positions = np.arange(4) + 1

bp = plt.boxplot(data_to_plot,
                 showmeans=True,
                 positions=positions,
                 labels=['ReadUnCommit','ReadCommit','RepeatableRead','Serializable'])

means = [np.mean(data) for data in data_to_plot]
above_dev = [np.mean(data)+np.std(data) for data in data_to_plot]
under_dev = [np.mean(data)-np.std(data) for data in data_to_plot]
maxV = [np.max(data) for data in data_to_plot]
minV = [np.min(data) for data in data_to_plot]
plt.plot(positions, above_dev, 'rs')
plt.plot(positions, under_dev, 'bs')
plt.plot(positions, maxV, 'ks')
plt.plot(positions, minV, 'ys')
plt.xlabel("isolation level")
plt.ylabel("average execution time")
plt.title('S=100,E=20,P=100')

plt.show()