cortex

vs Clojure. X <- D[D$type == "Seismic",] vs (def X (dt/where (comp #(= % "Seismic") :type) D)) E.g. aggregating in R vs Clojure. X <- aggregate(count ~ type, data=D, sum) vs (def X (dt/aggregate :type #(reduce + (map :count %)) D)) Having said that it's functional, and doesn't require one to loop or to mutate, it's just not as terse. Clojure is good for stats (because of Anglican) and good for ML (because of Java and https://github.com/thinktopic/cortex). RE viz: Clojure sucks at Viz. There's no compelling notebook solution (Gorilla REPL...) that supports mod-cons like exporting or easy sharing. However, I really like orgmode + babel. It makes it easy to grab data from Clojure and push it into an R block which generates graphs for example and it exports into everything. RE macros: I haven't written any custom macros at the moment tbh. If I do in the near term it'll probably be for logging or timing. I find that the function format is extremely flexible. RE general: Clojure has a steep and short learning curve. As in you cry for a few days but then suddenly understand loads. I also think the way of thinking it encourages is more mathematical. If you stay away from swap!, refs, agents, etc (which you can), then your world is immutable which makes testing so much easier. True error messages suck but as soon as you get a handle for how to write the code interactively with the REPL it's pretty easy to track down what causes an issue.