Matplotlib .plot()未显示全部数据点问题求助

我一眼就发现问题所在啦——你看你的group_data里，Group4、Group5、Group6的数值完全一模一样！从代码里的列表就能看出来，这三个组的10个年度数据点没有任何区别，所以用plot()绘制的时候，三条折线完全重叠在一起，视觉上就只剩一条了，这可不是Matplotlib的bug哦。

问题原因 #

你的group_data中索引为3、4、5的三个子列表（对应Group4、5、6）的数值完全相同，例如：

group_data[3] == group_data[4] == group_data[5]  # 结果是True

当多条折线的x、y坐标完全一致时，它们会精确重合，肉眼无法区分，看起来就像只显示了一条。

解决办法 #

根据你的需求，有几种实用的方案：

方案1：为重合数据添加微小偏移（适合需要区分趋势的场景） #

如果数据确实是独立的组（只是数值碰巧完全一致），可以给每组数据加一个极小的偏移量，让折线稍微分开一点：

import matplotlib.pyplot as plt
from matplotlib.ticker import StrMethodFormatter

group_data = [[0.019661816751867872, 0.02043028685790527, 0.02023318156674184, 0.017430534194606787, 0.019330407797782608, 0.01969285217721039, 0.020037761795104064, 0.02195322742933805, 0.02104150568005187, 0.023173911874613543], [0.046087298466378296, 0.04628085390260173, 0.04816816305689119, 0.05218907002973444, 0.060561320045386814, 0.0625292296024774, 0.0604625274209567, 0.05977172708885976, 0.05898549566113317, 0.06442723875581365], [0.015257569799449469, 0.01667778519012675, 0.017148206459299604, 0.015841279606274992, 0.01711575004442986, 0.01660873412121595, 0.01645803092974778, 0.019442835218668374, 0.02056187659321236, 0.019746216092695647], [0.1048368069209595, 0.1054869913275517, 0.10197438406876304, 0.0988584708978434, 0.0944373812355603, 0.09515262592428743, 0.09366234843441344, 0.09388053785407202, 0.09037455478874115, 0.0906121461408178], [0.1048368069209595, 0.1054869913275517, 0.10197438406876304, 0.0988584708978434, 0.0944373812355603, 0.09515262592428743, 0.09366234843441344, 0.09388053785407202, 0.09037455478874115, 0.0906121461408178], [0.1048368069209595, 0.1054869913275517, 0.10197438406876304, 0.0988584708978434, 0.0944373812355603, 0.09515262592428743, 0.09366234843441344, 0.09388053785407202, 0.09037455478874115, 0.0906121461408178]]
years = ['2008','2009','2010','2011','2012','2013','2014','2015','2016','2017']
# 定义微小偏移量，根据y轴比例调整
offset = 0.0005

plt.xlabel('Year')
plt.ylabel('Percentage')
plt.gca().yaxis.set_major_formatter(StrMethodFormatter('{x:,.0%}'))

plt.plot(years, group_data[0], label='Group 1')
plt.plot(years, group_data[1], label='Group 2')
plt.plot(years, group_data[2], label='Group 3')
# 给后三组添加偏移
plt.plot(years, [x + offset for x in group_data[3]], label='Group 4')
plt.plot(years, [x + 2*offset for x in group_data[4]], label='Group 5')
plt.plot(years, [x + 3*offset for x in group_data[5]], label='Group 6')

plt.legend()
plt.show()

方案2：使用不同的线条样式/标记（适合强调组的独立性） #

如果不需要改变数据本身，可以用不同的线条样式（实线、虚线、点线）或标记点来区分重合的折线，即使重叠也能通过样式识别：

import matplotlib.pyplot as plt
from matplotlib.ticker import StrMethodFormatter

group_data = [[0.019661816751867872, 0.02043028685790527, 0.02023318156674184, 0.017430534194606787, 0.019330407797782608, 0.01969285217721039, 0.020037761795104064, 0.02195322742933805, 0.02104150568005187, 0.023173911874613543], [0.046087298466378296, 0.04628085390260173, 0.04816816305689119, 0.05218907002973444, 0.060561320045386814, 0.0625292296024774, 0.0604625274209567, 0.05977172708885976, 0.05898549566113317, 0.06442723875581365], [0.015257569799449469, 0.01667778519012675, 0.017148206459299604, 0.015841279606274992, 0.01711575004442986, 0.01660873412121595, 0.01645803092974778, 0.019442835218668374, 0.02056187659321236, 0.019746216092695647], [0.1048368069209595, 0.1054869913275517, 0.10197438406876304, 0.0988584708978434, 0.0944373812355603, 0.09515262592428743, 0.09366234843441344, 0.09388053785407202, 0.09037455478874115, 0.0906121461408178], [0.1048368069209595, 0.1054869913275517, 0.10197438406876304, 0.0988584708978434, 0.0944373812355603, 0.09515262592428743, 0.09366234843441344, 0.09388053785407202, 0.09037455478874115, 0.0906121461408178], [0.1048368069209595, 0.1054869913275517, 0.10197438406876304, 0.0988584708978434, 0.0944373812355603, 0.09515262592428743, 0.09366234843441344, 0.09388053785407202, 0.09037455478874115, 0.0906121461408178]]
years = ['2008','2009','2010','2011','2012','2013','2014','2015','2016','2017']

plt.xlabel('Year')
plt.ylabel('Percentage')
plt.gca().yaxis.set_major_formatter(StrMethodFormatter('{x:,.0%}'))

plt.plot(years, group_data[0], label='Group 1')
plt.plot(years, group_data[1], label='Group 2')
plt.plot(years, group_data[2], label='Group 3')
# 用不同的线条样式和标记
plt.plot(years, group_data[3], label='Group 4', linestyle='--', marker='o')
plt.plot(years, group_data[4], label='Group 5', linestyle=':', marker='s')
plt.plot(years, group_data[5], label='Group 6', linestyle='-.', marker='^')

plt.legend()
plt.show()

方案3：合并图例说明（如果数据确实是重复的） #

如果这三组数据本来就是重复的（比如是同一数据的多次复制），可以在图例里说明它们是重合的，比如把这三个组的标签改成Group 4/5/6 (重合)，只绘制一次即可：

import matplotlib.pyplot as plt
from matplotlib.ticker import StrMethodFormatter

group_data = [[0.019661816751867872, 0.02043028685790527, 0.02023318156674184, 0.017430534194606787, 0.019330407797782608, 0.01969285217721039, 0.020037761795104064, 0.02195322742933805, 0.02104150568005187, 0.023173911874613543], [0.046087298466378296, 0.04628085390260173, 0.04816816305689119, 0.05218907002973444, 0.060561320045386814, 0.0625292296024774, 0.0604625274209567, 0.05977172708885976, 0.05898549566113317, 0.06442723875581365], [0.015257569799449469, 0.01667778519012675, 0.017148206459299604, 0.015841279606274992, 0.01711575004442986, 0.01660873412121595, 0.01645803092974778, 0.019442835218668374, 0.02056187659321236, 0