CODEWITHSUNDEEP
pythonmatplotlibseabornboxplotswarmplot
Arnold Klein
Arnold Klein

Reputation: 3086

Combine (overlay) two factorplots in matplotlib

I need to add swarmplot to boxplot in matplotlib, but I don't know how to do it with factorplot. I think I can iterate with subplots, but I would like to learn how to do it with seaborn and factorplot.

A simple example (plotting by using the same axis ax):

import seaborn as sns
tips = sns.load_dataset("tips")
ax = sns.boxplot(x="tip", y="day", data=tips, whis=np.inf)
ax = sns.swarmplot(x="tip", y="day", data=tips, color=".2")

The result: enter image description here

In my case, I need to overlay the swarm factorplot:

g = sns.factorplot(x="sex", y="total_bill",
                      hue="smoker", col="time",
                      data=tips, kind="swarm",
                      size=4, aspect=.7);

and boxplot

I can't figure out how to use axes (extract from g)?

Something like:

g = sns.factorplot(x="sex", y="total_bill",
                          hue="smoker", col="time",
                          data=tips, kind="box",
                          size=4, aspect=.7);

enter image description here

I want something like this, but with factorplot and boxplot instead of violinplot

enter image description here

Upvotes: 2

Views: 1905

Answers (1)

ImportanceOfBeingErnest
ImportanceOfBeingErnest

Reputation: 339570

Instead of trying to overlay the two subplots of a factorplot with individual boxplots (which is possible, but I don't like it), one can just create the two subplots individually.

You would then loop over the groups and axes an plot a pair of box- and swarmplot to each.

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

tips = sns.load_dataset("tips")

fig, axes = plt.subplots(ncols=2, sharex=True, sharey=True)

for ax, (n,grp) in zip(axes, tips.groupby("time")):
    sns.boxplot(x="sex", y="total_bill", data=grp, whis=np.inf, ax=ax)
    sns.swarmplot(x="sex", y="total_bill", hue="smoker", data=grp, 
                  palette=["crimson","indigo"], ax=ax)
    ax.set_title(n)
axes[-1].get_legend().remove()
plt.show()

enter image description here

Upvotes: 4

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