[vegabook]

this is not software engineering or production. It is batch jobs / exploratory analysis. It requires little or no structure apart from the analysis itself.

also in anything that has not been coded in C directly underneath, Python is 20x faster and C is 500× faster. R is literally the slowest mainstream language today by a long shot. That's a key consideration for production.

[ignasl]

Where did you get those numbers from? They are most definitely wrong unless you don't vectorize your code and run loops all around. A lot of R is actually written in C so you can squeeze really good performance if you know what you are doing. I would recommend reading Hadley's Advanced R and profile your code, I think you might be pleasantly surprised.

[vegabook]

I make extensive use of vectorization and use as many calls as I possibly can to the built-ins and/or c-based libraries. However as you well know, part of the fun in R is applying your own functions and unless you write these in C, you're back to native R and that's tediously slow. Ggplot another culprit -> amazing library, but if you're chucking out large amounts of custom charts with it it takes ages. Base graphics an order of magnitude faster (if less pretty and convenient for axis training).

[blahi]

I would also suggest The R Inferno.