Seaborn axvspan() 两条线之间的阴影

Question

I can't shade the area between two dates with using seaborn and pandas data frame. Codes are as follows. How can I do that. I can't loop the function. I don't know how to loop it.

import matplotlib.pyplot as plt 
import seaborn as sns 
import pandas_datareader.data as pdr 
import pandas as pd 
import datetime
import matplotlib.dates as mdates

start = datetime.datetime (2000,1,1)
end = datetime.datetime (2020,12,31)
df =  pdr.DataReader(['FEDFUNDS','TERMCBPER24NS','TERMCBCCALLNS','T5YIFR','T10YIE'], 'fred', start, end)
df.columns = ['Effective Federal Funds Rate','Finance Rate on Personal Loans at Commercial Banks','Commercial Bank Interest Rate on Credit Card Plans',
         '5-Year, 5-Year Forward Inflation Expectation Rate','10-Year Breakeven Inflation Rate']

fig, axes = plt.subplots(5,1, figsize=(20,25))
for ax, col in zip(axes, df.columns):
ax.axvspan(mdates.date2num(datetime.datetime(2007,1,12)), mdates.date2num(datetime.datetime(2009,6,1)), color='teal', alpha=0.5,
           label='2008 Crisis')
ax.axvspan(mdates.date2num(datetime.datetime(2019,12,1)), mdates.date2num(datetime.datetime(2020,2,1)), color='orange', alpha=0.5,
           label='Pandemic')
ax.set_title(col)

axes[0].set_title('Effective Federal Funds Rate')
sns.scatterplot(x='DATE', y='Effective Federal Funds Rate',  data=df,  s=50, ax=axes[0])
axes[1].set_title('Finance Rate on Personal Loans at Commercial Banks')
sns.scatterplot(x='DATE', y='Finance Rate on Personal Loans at Commercial Banks',  data=df, s=50,ax=axes[1])
axes[2].set_title('Commercial Bank Interest Rate on Credit Card Plan')
sns.scatterplot(x='DATE', y='Commercial Bank Interest Rate on Credit Card Plans',  data=df,  s=50, ax=axes[2]) 
axes[3].set_title('5-Year, 5-Year Forward Inflation Expectation Rate')
sns.scatterplot(x='DATE', y='5-Year, 5-Year Forward Inflation Expectation Rate', data=df,  s=50, ax=axes[3])
axes[4].set_title('10-Year Breakeven Inflation Rate')
sns.scatterplot(x='DATE', y='10-Year Breakeven Inflation Rate',  data=df,  s=50, ax=axes[4])

plt.tight_layout
plt.style.use('seaborn-whitegrid')

Answer 1

I think the answer to your previous question has axvspan enabled because it is automatically converted to a time series in the pandas plot. If this code consists only of matplotlib, then you will need to transform the time series data. See this .

import matplotlib.pyplot as plt 
import seaborn as sns 
import pandas_datareader.data as pdr 
import pandas as pd 
import datetime
import matplotlib.dates as mdates

start = datetime.datetime (2000,1,1)
end = datetime.datetime (2020,12,31)
df = pdr.DataReader(['FEDFUNDS','TERMCBPER24NS','TERMCBCCALLNS','T5YIFR','T10YIE'], 'fred', start, end)
df.columns = ['Effective Federal Funds Rate','Finance Rate on Personal Loans at Commercial Banks','Commercial Bank Interest Rate on Credit Card Plans',
             '5-Year, 5-Year Forward Inflation Expectation Rate','10-Year Breakeven Inflation Rate']

fig, axes = plt.subplots(5,1, figsize=(20,25))
for ax, col in zip(axes, df.columns):
    ax.axvspan(mdates.date2num(datetime.datetime(2007,1,12)), mdates.date2num(datetime.datetime(2009,6,1)), color='teal', alpha=0.5,
               label='2008 Crisis')
    ax.axvspan(mdates.date2num(datetime.datetime(2019,12,1)), mdates.date2num(datetime.datetime(2020,2,1)), color='orange', alpha=0.5,
               label='Pandemic')
    ax.set_title(col)

axes[0].set_title('Effective Federal Funds Rate')
sns.scatterplot(x='DATE', y='Effective Federal Funds Rate',  data=df,  s=50, ax=axes[0])
axes[1].set_title('Finance Rate on Personal Loans at Commercial Banks')
sns.scatterplot(x='DATE', y='Finance Rate on Personal Loans at Commercial Banks',  data=df, s=50,ax=axes[1])
axes[2].set_title('Commercial Bank Interest Rate on Credit Card Plan')
sns.scatterplot(x='DATE', y='Commercial Bank Interest Rate on Credit Card Plans',  data=df,  s=50, ax=axes[2]) 
axes[3].set_title('5-Year, 5-Year Forward Inflation Expectation Rate')
sns.scatterplot(x='DATE', y='5-Year, 5-Year Forward Inflation Expectation Rate', data=df,  s=50, ax=axes[3])
axes[4].set_title('10-Year Breakeven Inflation Rate')
sns.scatterplot(x='DATE', y='10-Year Breakeven Inflation Rate',  data=df,  s=50, ax=axes[4])

plt.tight_layout
plt.style.use('seaborn-whitegrid')