Using Seaborn, I'm trying to generate a factorplot with each subplot showing a stripplot. In the stripplot, I'd like to control a few aspects of the markers.
Here is the first method I tried:
import seaborn as sns
tips = sns.load_dataset("tips")
g = sns.FacetGrid(tips, col="time", hue="smoker")
g = g.map(sns.stripplot, 'day', "tip", edgecolor="black",
linewideth=1, dodge=True, jitter=True, size=10)
And produced the following output without dodge
While most of the keywords were implemented, the hue wasn't dodged.
I was successful with another approach:
kws = dict(s=10, linewidth=1, edgecolor="black")
tips = sns.load_dataset("tips")
sns.factorplot(x='day', y='tip', hue='smoker', col='time', data=tips,
kind='strip',jitter=True, dodge=True, **kws, legend=False)
This gives the correct output:
In this output, the hue is dodged.
My question is: why did g.map(sns.stripplot...)
not dodge the hue?
The hue
parameter would need to be mapped to the sns.stripplot
function via the g.map
, instead of being set as hue
to the Facetgrid
.
import seaborn as sns
tips = sns.load_dataset("tips")
g = sns.FacetGrid(tips, col="time")
g = g.map(sns.stripplot, 'day', "tip", "smoker", edgecolor="black",
linewidth=1, dodge=True, jitter=True, size=10)
This is because map
calls sns.stripplot
individually for each value in the time
column, and, if hue
is specified for the complete Facetgrid
, for each hue value, such that dodge
would loose its meaning on each individual call.
I can agree that this behaviour is not very intuitive unless you look at the source code of map
itself.
Note that the above solution causes a Warning:
lib\site-packages\seaborn\categorical.py:1166: FutureWarning:elementwise comparison failed;
returning scalar instead, but in the future will perform elementwise comparison
hue_mask = self.plot_hues[i] == hue_level
I honestly don't know what this is telling us; but it seems not to corrupt the solution for now.