CODEWITHSUNDEEP
parametersseabornalpha
Hoang Minh Nguyen
Hoang Minh Nguyen

Reputation: 135

How to pass alpha (transparency) into seaborn.jointplot?

I am practicing data exploration with seaborn, and recently encountered a problem: how to pass alpha (transparency) into seaborn.jointplot (onto the scatter plot part, not the histogram)?

More broadly, I would also like to know:

  1. What are the general functions of joint_kws, marginal_kws and annot_kws (i.e. how do I use/pass pyplot parameters into these parameters?)?

  2. What is the difference between these parameters and the kwargs parameter?

Thank you!

Upvotes: 6

Views: 6469

Answers (2)

Thomas Matthew
Thomas Matthew

Reputation: 2886

Just adding alpha=0.5 to your sns.jointplot call may give the following error:

TypeError: regplot() got an unexpected keyword argument 'alpha'

So in this case, you would nest this alpha setting into the scatter_kws, then into joint_kws, like so:

sns.jointplot(x, y, data, kind='reg',joint_kws = {'scatter_kws':dict(alpha=0.5)})

At which point, you will get adjustment of transparancy for the scatter in the jointplot.

Upvotes: 6

busybear
busybear

Reputation: 10590

As noted in the comments, you can simply add alpha=0.5 into your jointplot call.

As for your other questions, general information can be found in the documentation:

  1. You pass a dictionary to each of the kw parameters. These control the different portions of the plot created by jointplot. For instance, if you wanted to change the transparency of the histogram, you would pass it to marginal_kws. (This is a little bit more involved though since the "marginal" is created using sns.distplot which builds off plt.hist. So you would actually have marginal_kws={'hist_kws': {'alpha': 0.1}} for jointplot.

  2. Additional kwargs affect the scatter plot portion, just like joint_kws will. These arguments, however, will supersede those provided by joint_kws.

Upvotes: 0

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