指示活动趋势的 seaborn 线图时间序列

Question

On a seaborn lineplot, I would like to indicate trend in a time-series data, preferably using different colours.

For example, taking this fake data:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.DataFrame(np.random.randint(100, size=50), columns=['max'])
df['day'] = pd.date_range('2016-1-1', periods=50, freq='SMS')#freq='W')
df['date'] = df['day'].dt.strftime('%Y-%m')

On a lineplot this produces the following figure:

sns.lineplot(data=df, x = df['date'], y='max', )
plt.xticks(rotation=45)

So I would like to indicate the trend in time series between 2017-01 and 2017-08 such that the plot's background in this area is in green, with begin and end marked (similar to the figure below, but inserting green background in the area indicated).

Answer 1

You can use ax.axvspan :

ax = sns.lineplot(data=df, x = df['date'], y='max', )
ax.axvspan('2017-01', '2017-08', color='g', alpha=0.1)

output:

alternative with a different zorder :

ax.axvspan('2017-01', '2017-08', color='g', alpha=0.5, zorder=0)

output: