replicate(100, c( "OMG OMG, R is now famous?!", "People used to make fun of me for learning R since Splus is SO OLD!", "I still hear stories that SAS can do crazy tricks that make me jealous. But not enough to attempt learning it." )[ floor(runif(1, min=1,max=4)) ] )
This blog has been a long-time supporter of this both brilliant and insanely quirky statistical programming environment. Here are some graphs I’ve made in the last year or two that have R code attached:
- Wisdom of small crowds
- Simpson’s paradox via mosaic plots
- Dolores Labs color wheel! (code)
- Political bias SVD evaluation
- Presidential poll aggregation
- OK, we didn’t post the code, but check out our N-body trolley graph!
Learning R is hard because there’s a zillion packages, and the official documentation is reference-oriented. I’ve never looked at any of the books much. I think you can get very far with exactly two websites:
- Quick-R – the best introduction that’s organized by topic, not overly domain-specific, and not overly biased towards the author’s pet package. Check out the “Advanced Graphics” section for a good time.
- RSeek.org – searches the documentation, package listings, and most critically, the archives of the amazing user mailing list. Searching those archives alone is far more useful than any half-assed attempt at documentation — it records the expertise and advice of hundreds of statisticians solving real problems over the last 10 years. I’ve stumbled upon entire new areas of statistics just by reading the R-help archives.
For a few lucid demonstrations of R’s flaws, see these interesting Radford Neal posts: (1) (2) (3) . It has way more problems than these, of course. The core’s development model is too closed-source-y. There’s horrible repetition and inconsistencies even in the standard library. I swear I’ve seen its interpreter be even slower then Ruby. You have to memorize a zillion incomprehensible 3-letter-acronyms when making a final draft plot.
But yet it is still great. R takes one problem — programmatic single-machine data analysis — and solves it well, using a nice Scheme-like language, plus an impressive user community to boot.