Can you plot interquartile range as the error band on a seaborn lineplot?

Question

I'm plotting time series data using seaborn lineplot (https://seaborn.pydata.org/generated/seaborn.lineplot.html), and plotting the median instead of mean. Example code:

import seaborn as sns; sns.set()
import matplotlib.pyplot as plt

fmri = sns.load_dataset("fmri")
ax = sns.lineplot(x="timepoint", y="signal", estimator = np.median, data=fmri)

I want the error bands to show the interquartile range as opposed to the confidence interval. I know I can use ci = "sd" for standard deviation, but is there a simple way to add the IQR instead? I cannot figure it out.

Thank you!

Answer 1

I don't know if this can be done with seaborn alone, but here's one way to do it with matplotlib, keeping the seaborn style. The describe() method conveniently provides summary statistics for a DataFrame, among them the quartiles, which we can use to plot the medians with inter-quartile-ranges.

import seaborn as sns; sns.set()
import matplotlib.pyplot as plt

fmri = sns.load_dataset("fmri")
fmri_stats = fmri.groupby(['timepoint']).describe()

x = fmri_stats.index
medians = fmri_stats[('signal', '50%')]
medians.name = 'signal'
quartiles1 = fmri_stats[('signal', '25%')]
quartiles3 = fmri_stats[('signal', '75%')]

ax = sns.lineplot(x, medians) 
ax.fill_between(x, quartiles1, quartiles3, alpha=0.3); 

Answer 2

You can calculate the median within lineplot like you have done, set ci to be none and fill in using ax.fill_between()

import numpy as np
import seaborn as sns; sns.set()
import matplotlib.pyplot as plt

fmri = sns.load_dataset("fmri")
ax = sns.lineplot(x="timepoint", y="signal", estimator = np.median, 
                  data=fmri,ci=None)

bounds = fmri.groupby('timepoint')['signal'].quantile((0.25,0.75)).unstack()
ax.fill_between(x=bounds.index,y1=bounds.iloc[:,0],y2=bounds.iloc[:,1],alpha=0.1)