I am using Seaborn to plot some data in Pandas.
I am making some very large plots (factorplot
s).
To see them, I am using some visualisation faciliti
In new versions of seaborn you can also use
axes_style()
and set_style()
to quickly set the plot style to one of the predefined styles: darkgrid, whitegrid, dark, white, ticks
st = axes_style("whitegrid")
set_style("ticks", {"xtick.major.size": 8, "ytick.major.size": 8})
More info in seaborn docs
I am not familiar with seaborn but the following appears to let you change
the background by setting the axes background. It can set any of the ax.set_*
elements.
import seaborn as sns
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
m=pd.DataFrame({'x':['1','1','2','2','13','13'],
'y':np.random.randn(6)})
facet = sns.factorplot('x','y',data=m)
facet.set(axis_bgcolor='k')
plt.show()
seaborn.set
takes and rc
argument that accepts a dictionary of valid matplotlib rcparams
. So we need to set two things: the axes.facecolor
, which is the color of the area where the data are drawn, and the figure.facecolor
, which is the everything a part of the figure outside of the axes
object.
So if you do:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn
seaborn.set(rc={'axes.facecolor':'cornflowerblue', 'figure.facecolor':'cornflowerblue'})
fig, ax = plt.subplots()
You get:
And that'll work with your FacetGrid
as well.