Matplotlib軸上的可讀值

我正在使用 Matplotlib 并嘗試繪制一個帶有條形和線條的組合框。下面你可以看到我的資料：

import numpy as np
import pandas as pd

import matplotlib.pyplot as plt
from matplotlib.cm import get_cmap
from matplotlib.ticker import FormatStrFormatter

# Data
data = {
         'Year': ['2010','2011','2012','2013','2014','2015','2016','2017','2018','2019'],
         'Rate':[10,10,9,7,5,5,5,5,5,5],
         'ChangeRate_1':[7,-50,24,150,8,10,60,5,180,5],
         'ChangeRate_2':[7,6,-3,1,8,5,8,5,15,5],
         
        }

df = pd.DataFrame(data, columns = ['Year',
                                   'Rate',
                                   'ChangeRate_1',
                                   'ChangeRate_2'
                                   
                                   ])
df

下面你可以看到代碼：

# Ploting combo plot
fig, ax_1 = plt.subplots(figsize = (8, 5))
ax_2 = ax_1.twinx()
ax_3 = ax_2.twinx()   ### <---- Problem is probably here 
cmap = get_cmap('tab10')

ax_1.bar(df['Year'], df['Rate'], label = 'Rate', color = cmap(0))
ax_2.plot(df['Year'], df['ChangeRate_1'], label = 'ChangeRate_2', color = cmap(0.1),linewidth = '3.5')
ax_3.plot(df['Year'], df['ChangeRate_2'], label = 'ChangeRate_2', color = cmap(0.2),linewidth = '3.5')

handles_1, labels_1 = ax_1.get_legend_handles_labels()
handles_2, labels_2 = ax_2.get_legend_handles_labels()
handles_3, labels_3 = ax_3.get_legend_handles_labels()

ax_1.set_ylim(0, 16)
ax_2.set_ylim(-50,180)

ax_1.legend(handles = handles_1   handles_2   labels_3, 
            labels = labels_1   labels_2   labels_3, 
            loc = 'upper right', 
            shadow = True)
ax_1.grid(axis = 'y')
ax_1.set_title('Comparison of revenues',fontsize=11)

ax_1.set_ylabel('Rate')
ax_2.set_ylabel('ChangeRate_1')
ax_3.set_ylabel('ChangeRate_2')

ax_1.xaxis.set_major_formatter(FormatStrFormatter('%.0f'))
plt.savefig('ComparisonOfRevenues.pdf')  
plt.show()

上面的代碼生成了一個如下所示的圖。

如上圖所示，y-axis左側和右側的值與值重疊并且不可讀。

對于左側，“Rate”的比例應在 0 到 16 的范圍內，而對于右側，ChangeRate_1 和 ChangeRate_2，從 -50 到 180。

那么有人可以幫我解決這個問題嗎？

uj5u.com熱心網友回復：

第三個 Axes 物件的實體化ax_3 = ax_2.twinx()可以通過在右側僅使用一個額外的 y 軸并繪制ChangeRate_1并ChangeRate_2在該軸上保持（右）y 軸標簽為ChangeRate，然后為線條分配正確的標簽來規避。

代碼：

fig, ax_1 = plt.subplots(figsize=(8, 5))
ax_2 = ax_1.twinx()

cmap = get_cmap('tab10')

ax_1.bar(df['Year'], df['Rate'], label='Rate', color=cmap(0))
ax_2.plot(df['Year'], df['ChangeRate_1'], label='ChangeRate_1', color=cmap(0.1), linewidth='3.5')
ax_2.plot(df['Year'], df['ChangeRate_2'], label='ChangeRate_2', color=cmap(0.2), linewidth='3.5')

handles_1, labels_1 = ax_1.get_legend_handles_labels()
handles_2, labels_2 = ax_2.get_legend_handles_labels()

ax_1.set_ylim(0, 16)
ax_2.set_ylim(-50,180)

ax_1.legend(handles=handles_1   handles_2, labels=labels_1   labels_2, 
loc='upper right', shadow=True)

ax_1.grid(axis='y')
ax_1.set_title('Comparison of revenues',fontsize=11)

ax_1.set_ylabel('Rate')
ax_2.set_ylabel('ChangeRate')

ax_1.xaxis.set_major_formatter(FormatStrFormatter('%.0f'))
plt.show()

標籤：Pythonmatplotlib

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