How to add hatches to boxplots with sns.boxplot or sns.catplot

Question

I need to add hatches to a categorical box plot. What I have is this:

What I need is something like this (with the median lines):

And what I have tried is this code:

exercise = sns.load_dataset("exercise")
g = sns.catplot(x="time", y="pulse", hue="kind", data=exercise, kind="box")
bars = g.axes[0][0].patches
hatches=['//','..','xx','//','..','xx','//','..','xx']
for pat,bar in zip(hatches,bars):
    bar.set_hatch(pat)

That only generates the first figure. The idea for lines 3-6 comes from this question. But the idea to get axes[0][0] in line 3 comes from this question.

Because FacetGrids don't have attributes like patches or containers, it makes it harder to adapt the answers about hatches in individual plots to categorical plots, so I couldn't figure it out.

Other reviewed questions that don't work:

• Face pattern for boxes in boxplots

Answer 1

1. Iterate through each subplot / FacetGrid with for ax in g.axes.flat:.
2. ax.patches contains matplotlib.patches.Rectangle and matplotlib.patches.PathPatch, so the correct ones must be used.

• Caveat: all hues must appear for each group in each Facet, otherwise the patches and hatches will not match.
  • In this case, manual or conditional code will probably be required to correctly determine h, so zip(patches, h) works.
• Tested in python 3.10, pandas 1.4.2, matplotlib 3.5.1, seaborn 0.11.2

import matplotlib as mpl
import seaborn as sns

# load test data
exercise = sns.load_dataset("exercise")

# plot
g = sns.catplot(x="time", y="pulse", hue="kind", data=exercise, col='diet', kind="box")

# hatches must equal the number of hues (3 in this case)
hatches = ['//', '..', 'xx']

# iterate through each subplot / Facet
for ax in g.axes.flat:

    # select the correct patches
    patches = [patch for patch in ax.patches if type(patch) == mpl.patches.PathPatch]
    # the number of patches should be evenly divisible by the number of hatches
    h = hatches * (len(patches) // len(hatches))
    # iterate through the patches for each subplot
    for patch, hatch in zip(patches, h):
        patch.set_hatch(hatch)
        fc = patch.get_facecolor()
        patch.set_edgecolor(fc)
        patch.set_facecolor('none')

• Add the following, to change the legend.

for lp, hatch in zip(g.legend.get_patches(), hatches):
    lp.set_hatch(hatch)
    fc = lp.get_facecolor()
    lp.set_edgecolor(fc)
    lp.set_facecolor('none')

---

• If only using the axes-level sns.boxplot, there's no need to iterate through multiple axes.

ax = sns.boxplot(x="time", y="pulse", hue="kind", data=exercise)

# select the correct patches
patches = [patch for patch in ax.patches if type(patch) == mpl.patches.PathPatch]
# the number of patches should be evenly divisible by the number of hatches
h = hatches * (len(patches) // len(hatches))
# iterate through the patches for each subplot
for patch, hatch in zip(patches, h):
    patch.set_hatch(hatch)
    fc = patch.get_facecolor()
    patch.set_edgecolor(fc)
    patch.set_facecolor('none')

l = ax.legend()
    
for lp, hatch in zip(l.get_patches(), hatches):
    lp.set_hatch(hatch)
    fc = lp.get_facecolor()
    lp.set_edgecolor(fc)
    lp.set_facecolor('none')

---

• To keep the facecolor of the box plots:
  1. Remove patch.set_facecolor('none')
  2. Set the edgecolor as 'k' (black) instead of fc, patch.set_edgecolor('k').
  • Applies to the sns.catplot code too.

ax = sns.boxplot(x="time", y="pulse", hue="kind", data=exercise)

# select the correct patches
patches = [patch for patch in ax.patches if type(patch) == mpl.patches.PathPatch]
# the number of patches should be evenly divisible by the number of hatches
h = hatches * (len(patches) // len(hatches))
# iterate through the patches for each subplot
for patch, hatch in zip(patches, h):
    patch.set_hatch(hatch)
    patch.set_edgecolor('k')
    
l = ax.legend()
    
for lp, hatch in zip(l.get_patches(), hatches):
    lp.set_hatch(hatch)
    lp.set_edgecolor('k')