将带有图例的 python 图简化为循环

Question

有什么好的方法可以将以下代码简化为循环吗？重复代码将达到数千。例如测试-101.csv...测试-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])

Answer 1

我相信这可能会有所帮助

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)

将带有图例的 python 图简化为循环

Simplify python plot with legend into loop

python

matlab

numpy

for-loop

simplify