core.matrix

I'm a big R user; but it's true what the guy says. When you step off the happy path because the data is an awkward size or because you can't apply, aggregate or tidyr your way to a good solution, what results is often slow and hideous. I've switched to Clojure for data work. It's fast, data centric and you can usually work out an elegant solution no matter how grizzly the problem, and in truth, despite the huge number of R packages, I use only a tiny portion. For working with matrices and datasets: https://github.com/mikera/core.matrix https://github.com/emiruz/dataset-tools https://github.com/emiruz/sparse-data https://github.com/clojure/data.csv For optimisation, simulation and modelling: https://github.com/probprog/ For complex plots: http://www.gnuplot.info/ (+ clojure dsl) For reports (clojure outputs csv + images): latex orgmode + b

Clojure matrix libs: https://github.com/mikera/core.matrix https://data-sorcery.org/ https://github.com/mikera/vectorz-clj http://neanderthal.uncomplicate.org/ https://github.com/tel/clatrix

You can be pretty productive. Have a look at core.matrix (https://github.com/mikera/core.matrix) and vectorz.clj (https://github.com/mikera/vectorz-clj) libs. They give you almost native speeds. If you need even more performance, checkout neanderthal (https://github.com/uncomplicate/neanderthal) which has a GPU back-end.

Very cool and thanks for the response! I'll need to experiment with this + a clojure matrix math library at some point. I'm new to the clojure ecosystem but it looks like https://github.com/mikera/core.matrix could be worth trying.