[hadley]

I think R is a well-designed language. It definitely has its quirks (what language doesn't?), but by-and-large they are problems with the standard library, not the language. This is admittedly a subtle distinction, but it's much easier to fix problems with the standard library than it is with the language.

Three aspects of the language that make R particularly well suited for statistical programming are:

1) Missing values built in at a fundamental level.

2) Metaprogramming capabilities. The best way to solve many categories of data analysis problems is to design a domain specific language which allows you to easily combine independent pieces. R's incredible flexibility is great for this.

3) Fundamentally vectorised and functional. This allows you to elegantly express many common data analysis tasks.

[jph00]

Could you describe what facilities of R help with metaprogramming and make it good for designing DSLs?

[hadley]

http://adv-r.had.co.nz/dsl.html and the two prior chapters