I find the best way for my feeble mind to understand more than 3 or 4 dimensions is a parallel coordinate graph where you can view the relationships between two of the dimensions at a time. You can do this interactively in R using plotly:

https://plot.ly/r/parallel-coordinates-plot/

As far as I can tell, HyperTools are a bunch of convenience functions for doing something along the lines of the following dummy R code

    df %>% dim_reduction_function() %>%
       ggplot() + geom_*()

So in a sense, I think you should be looking for a dimensionality reduction library, rather than a plotting library.

so it seems, looking at their gallery, and I'd rather just write the lines calling pca, or whatever.

You should take a look at tourrr which implements a bunch of "grand tour" algorithms in R. These take your on a smooth tour of random projections of your data, visualised in various ways (including into 3d if you have some red-blue 3d glasses!)

Interesting thanks

Good visualisation of high dimensional data is almost all about the mental model and mapping of dimensions, barely ever about the library. ggplot2 is excellent for displaying high dimensional data in R if you can reason well about your own data. If you can't, no library is going to save you.

Well I already use ggplot. I'm not sure ggplot does 3D much.... About the reasoning, well who knows.

If you present an example of high-dimensional data I'd be happy to help you reason about how to visualise it (although this is perhaps better suited to StackExchange).

edit: if you feel you need 3D, you've already failed to represent the data clearly

I took a visualization course and to paraphrase the prof. you have a 3d object projected onto a 2d (display) plane and reasoning about depth gives additional mental load, not to mention occlusion. You have to interact with the model a lot to get a view you want. The course was based on old papers about UX with a dash of cognitive science, so take it with a grain of salt.

Yup, this. There's almost always a way to represent the data that allows clearer interpretation.

He is umm. very opinionated. Its kind of like saying why need two dimensions, surely a 1D vector is good enough..