将带有图例的python绘图简化为循环

有什么好办法可以把下面的代码简化成一个循环？重复的代码将达到数千个。e、 g.test-101.csv…test-2233.csv

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


data = pd.read_csv('reports/test-101.csv', header=None)
line1, = plt.plot(data[2], data[1], label='line 101')
line1m, = plt.plot(np.array([0, 12]), np.array([np.mean(data[1]), 
np.mean(data[1])]), label='line-101 mean')

data = pd.read_csv('reports/test-102.csv', header=None)
line2, = plt.plot(data[2], data[1], label='line 102')
line2m, = plt.plot(np.array([0, 12]), np.array([np.mean(data[1]), 
np.mean(data[1])]), label='line-102 mean')

data = pd.read_csv('reports/test-103.csv', header=None)
line3, = plt.plot(data[2], data[1], label='line 103')
line3m, = plt.plot(np.array([0, 12]), np.array([np.mean(data[1]), 
np.mean(data[1])]), label='line-103 mean')
.
.
.


plt.legend(handles=[line1, line2, line3,
                      line1m, line2m, line3m])

---

我相信这可能会有帮助

import os

import numpy as np
import pandas as pd

from matplotlib import pyplot as plt

csv_dir = 'reports/'
csv_files = [csv for csv in os.listdir(csv_dir)]

plt_handles = []
index = 0

for csv_file in csv_files:
    # You can parse the csv_file to get the index handle if you wish
    data = pd.read_csv(csv_dir + csv_file, header=None)
    line, = plt.plot(data[2], data[1], label='line %d' % index)
    line_m, = plt.plot(np.array([0, 12]), np.array([np.mean(data[1]), 
        np.mean(data[1])]), label='line-%d mean' % index)

    plt_handles.append((line, line_m))
    index += 1  # for demonstration purposes - if you do not parse csv fname

lines, lines_m = zip(*plt_handles)  # transpose matrix - lines before means

plt.legend(handles=lines + lines_m)

---

如何循环标签？我改进了答案，忘记了标签！还有什么方法可以简化这一行（

line\m，=…

）吗？很高兴我能帮上忙。我没有你拥有的数据，我也不知道你到底想用它们做什么，但我认为你可以用

np.full（（2，），data[1].mean（））

简化第二个参数。我相信有很多方法可以简化python中的事情。玩吧，谢谢。这就是我所需要的。顺便说一下，您需要在代码中修复

dirname

。