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).
>Solution :
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:
