使用 Matplotlib 在两条线之间着色

如何解决使用 Matplotlib 在两条线之间着色

我想使用 axvspan() 函数来可视化我使用 Pandas DataReader 获得的 DataFrame。但是当我使用以下代码时，我看到一个错误并且子图中没有阴影。我应该怎么办？ 谢谢。

import matplotlib.pyplot as plt
import pandas_datareader.data as pdr
import pandas as pd
import datetime
start = datetime.datetime (2000,1,1)
end = datetime.datetime (2021,5,1)
df  = pdr.DataReader(['WFRBSB50215','WFRBST01134','WFRBST01122','WFRBSN09139','WFRBSB50189','WFRBST01110','WFRBSB50191'],'fred',start,end)
df.columns = ['Share of Total Net Worth Held by the Bottom 50% (1st to 50th Wealth percentiles)','Share of Total Net Worth Held by the Top 1% (99th to 100th Wealth percentiles)','Share of Corporate Equities and Mutual Fund Shares Helb By Top1%(99th to 100th Wealth percentiles)','Share of Financial Assets Held by the 90th to 99th Wealth percentiles','Share of Total Assets Held by the Bottom 50% (1st to 50th Wealth percentiles)','Share of Real Estate Held by the Top 1% (99th to 100th Wealth percentiles)','Share of Real Estate Held by the Bottom %50(1st to 50th Wealth percentiles)'
              ]
ax = df.plot(subplots=True,layout=(7,1),figsize=(15,15),linewidth=3.5,colormap="summer")
ax.axvspan('2007-1-12','2009-6-1',color='c',alpha=0.5)
ax.axvspan('2019-12-1','2020-2-1',color= 'orange',alpha=0.5)
plt.xlabel('Date')
ax[0,].set_title('Share of Total Net Worth Held by the Bottom 50%')
ax[0,].set_ylabel('Percent of Aggregate')
ax[1,].set_title('Share of Total Net Worth Held by the Top 1%')
ax[1,].set_ylabel('Percent of Aggregate')
ax[2,].set_title('Share of Corporate Equities and Mutual Fund Shares Helb By Top 1%')
ax[2,].set_ylabel('Percent of Aggregate')
ax[3,].set_title('Share of Financial Assets Held by the 90th to 99th Wealth percentiles')
ax[3,].set_ylabel('Percent of Aggregate')
ax[4,].set_title('Share of Total Assets Held by the Bottom 50% ')
ax[4,].set_ylabel('Percent of Aggregate')
ax[5,].set_title('Share of Real Estate Held by the Top 1%')
ax[5,].set_ylabel('Percent of Aggregate')
ax[6,].set_title('Share of Real Estate Held by the Bottom %50')
ax[6,].set_ylabel('Percent of Aggregate')
plt.tight_layout()
plt.style.use('seaborn-white')
plt.show()

解决方法

尝试遍历所有子图并将 axvspan 添加到特定的 AxesSubplot：

axes = df.plot(subplots=True,layout=(7,1),figsize=(15,15),linewidth=3.5,colormap="summer",ylabel='Percent of Aggregate',xlabel='Date')

for (ax,),col in zip(axes,df.columns):
    ax.axvspan('2007-1-12','2009-6-1',color='c',alpha=0.5)
    ax.axvspan('2019-12-1','2020-2-1',color='orange',alpha=0.5)
    ax.set_title(col)

plt.tight_layout()
plt.style.use('seaborn-white')
plt.show()

使用 ylabel 的 xlabel 和 plot kwargs 稍微减少了一些代码，并且还从 df.columns 而不是手动设置子情节标题。

---

为 axvspan 添加图例。最简单的方法是为每个 axvspan 添加一个标签，并在每次迭代结束时制作图例：

axes = df.plot(subplots=True,xlabel='Date',legend=False)

for (ax,alpha=0.5,label='2008 Crisis')
    ax.axvspan('2019-12-1',label='Pandemic')
    ax.set_title(col)
    ax.legend()

plt.style.use('seaborn-white')
plt.tight_layout()
plt.show()

---

或者，可以只为危机制作一个图例：

fig,axes = plt.subplots(nrows=7,15))
df.plot(subplots=True,ax=axes,xlabel='Date')

for ax,label='Pandemic')
    ax.set_title(col)

handles,labels = axes[-1].get_legend_handles_labels()

fig.legend(handles[-2:],labels[-2:],title='Crises',loc='lower left',ncol=2)

plt.style.use('seaborn-white')
plt.tight_layout()
plt.show()

^ 单个图例位于左下方。