Kaj Gets on the Meta Train

I took a look at it, and I couldn’t make head or tail of what it was. The documentation feels like endless grandiose claims without actually explaining what it is, aside from it being a Rebol descendant. (Apparently, if I use it enough the compiler will tell me where the differences are… which is lovely, but I don’t particularly feel like learning it via trial-and-error when I could just read a quick summary.)

The basic reason is: convenience. For one thing, R has a huge ecosystem which has everything a data analyst needs to do their work. For another, its metaprogramming facilities mean that library authors can bend the language to their needs to make code easy to read and quick to write (e.g. as in data-masking). Thirdly, the RStudio IDE is really nice. I consider R to be unusable for any program of, let’s say, >20 lines, but for exploratory data analysis it’s great.