Feature request: multiple grouping variables

Hi, thanks so much for the package, it's a huge help! I am cross-posting this issue on the stan forums in case there is a solution I am missing. Essentially I am trying to visualize the posterior predictive distributions across two grouping variables instead of one. I am using bayesplot::ppc_violin_grouped() which is working like a charm for the first grouping variable, but then I'd like to facet by the second grouping variable.

I thought I might be able to just add this to an existing plot using facet_wrap(). I looked at the data component of the bayesplot object and first tried to emulate that. However, I got an error that the length was wrong. If I then change the length of the facet variable to what the error asks for, it then wants a different length. Minimally reproducible example:

mod <- brms::brm(mpg ~ cyl + gear, data = mtcars, iter = 200)
ppc <- brms::posterior_predict(mod)
base.plot <- bayesplot::ppc_violin_grouped(y = mtcars$mpg, yrep = ppc, group = mtcars$gear) 

# try to replicate structure of base.plot$data
base.plot +
  facet_wrap(~c(rep(mtcars$cyl, each = 400), mtcars$cyl))

# change based on resulting error
base.plot +
  facet_wrap(~rep(mtcars$cyl, each = 400))

# change based on resulting error
base.plot +
  facet_wrap(~mtcars$cyl)

Start with the ppc_violin_grouped() example in this issue and inspect how its plot data is structured when two grouping variables are supplied. Reproduce the mtcars example, then determine the supported interface and plotting behavior needed to facet posterior predictive distributions by a second grouping variable; done means the example works without manual vector-length manipulation.