[Blahah]

Indeed, all the examples appear to be showing datasets that would benefit from good data visualisation and in some cases dimension reduction, but all of them are terribly represented. I don't think this necessarily a problem with the library, but the examples certainly do not exemplify good visualisation of high-dimensional data.

[daveguy]

When you say it doesn't exemplify good visualization of high-dimensional data do you have alternate examples in mind? I would like to be able to see examples of good visualization of high dimensional data.

[Blahah]

I have many examples in mind. Here's an old article with good examples: https://cacm.acm.org/magazines/2010/6/92482-a-tour-through-t...

In general I'd say that for any dataset, the ideal visualisation depends on the features and meaning of the data, but almost always some combination of geometry, colour, shape and size can capture all the dimensions. Beyond a small number of categories, colour, shape and size are much less visually informative than geometry. Most often creative use of geometry on different scales is the best first stop for high-dimensional data, for example using faceting (like with ggplot2's facet capability: http://ggplot2.tidyverse.org/reference/facet_grid.html). Simulating 3D is almost never required or optimal.