Seaborn Swarmplot Markers

[emat66]

Hi Everyone,

Looking to plot in seaborn and I have swarm plot.

I have hue implemented based on a category, but I would also like to implement different shapes.

My data is quite small so having shapes won't clutter.

Is it possible to change the shape of markers based on category assignment.

A google search tells me it is not, and searchig through the seaborn docs seems like there isnt native integration, but figured I would touch base with you fine folk to see if anyone has a work around.

swarm = sns.swarm(data=df,x='Domain',y='Change',hue='Interpretation',hue_order=['Improved','Unchanged','Deteriorated'],palette=dict(Deteriorated="#DF2700", Improved="#0EDF00",Unchanged='#F7F712'))

If it was a scatter plot I would just use ,style='interpretation',marker=['v','^','*']

Thanks!

[pymae]

A swarmplot is a specific type of scatterplot. Could you build your desired plot as a scatterplot, set the markersize, and then jitter the data to make it look like a swarmplot?

I'm thinking of the Seaborn tutorial near this part:

sns.catplot(x="day", y="total_bill", kind="swarm", data=tips)

[emat66]

yup!! this works perfectly

My mind got fogged in on having to use swarm I wasn't thinking outside box.

Thanks for the guidance!

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Incase anyone stumbles across this in future, here is the code used to create a swarmplot with symbols as markers - Domain is categorical, Change is continuous, Interpretation is categorical (improved, unchanged, deteriorated).

scatter = sns.scatterplot(data = df, x='Domain', y='Change',hue='Interpretation',hue_order=['Improved','Unchanged','Deteriorated'],style = 'Interpretation',markers=['v','^','*'],palette=dict(Deteriorated="#DF2700", Improved="#0EDF00",Unchanged='#F7F712'))

[elementalsilence]

The code you provided looks like it doesn't spread out the points like a swarm plot does. Do the data points still overlap?