如何学习 R 作为一种编程语言

For starters, you might want to look at this article by John Cook. Also make sure that you read "The R Inferno".

There are many good resources on the R homepage, but in particular, read "An Introduction to R" and "The R Language Definition".

Some very closely related stackoverflow questions:

• books-for-learning-the-r-language.
• what-are-some-good-books-web-resources-and-projects-for-learning-r
• suggestions-on-way-resources-to-start-learning-statistical-language-r

My favorite book on the subject: "Software for Data Analysis: Programming with R", by John Chambers, the creator of the S language.

I'm a very hands-on learner, so this advice may be specific to my learning style. I would suggest that the best place to start "learning to program" in any language involves finding problems outside of your normal range of experience and then trying to solve them using a programming language.

The projects that taught me the most about how to program with R had nothing to do with statistics at all.

Knowing functions like parse() and eval() is by no means a measure for being "a good R programmer". Applications that require heavy use of these functions do not make up a majority of the problem space in which you can apply R. Instead, I think you should try to be "a good programmer" who knows R. This involves refining your problem-solving approaches.

Programming is not a spectator sport-- a good book is indispensable as a reference on the tools available, but you need to find some problems upon which to hone your skills.

I would rather suggest a good and comprehensive start, like The R Book by Michael Crawley. It's an easy-to-read and complete book on R core functions, with statistical tips and a few exercises. It focuses a lot on R strengths (e.g. linear models) and gives also useful coding tricks. It helped me a lot while I was struggling on cryptic online courses.

A good book for learning R-as-a-programming-language (as opposed to R-for-statistics) is The Art of R Programming, by Norman Matloff.

It's very readable, doesn't assume you're a computer scientist, and is quite inexpensive as R books go.