The art of R programming

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1. carlosggJul 2017
   "The Art of R Programming" is very good.

   https://www.nostarch.com/artofr.htm

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2. disgruntledphd2Mar 2016
   If you know almost nothing about the field, then introduction to statistical learning is a good choice.

   http://www-bcf.usc.edu/~gareth/ISL/ISLR%20First%20Printing.p...

   It assumes some understanding of calculus, but doesn't require matrix algebra.

   The original (and amazing) book that lots of people used is Elements of Statistical Learning.

   https://web.stanford.edu/~hastie/local.ftp/Springer/OLD/ESLI...

   Chapters 1-7 are worth their weight in gold. This is one of the cases where the physical books are much better, as you'll need to flick back and forth to see the figures (which are one of the best parts).

   The forgoing assumes that you already know some statistics/data analysis (the latter probably being more important).

   If you haven't done this before, then I suggest that you acquire some data you care about, install R (a good book is the Art of R Programming by Matloff), and start trying to make inferences. And draw graphs. Many, many, many graphs.

   If you keep at this, finding papers/books and reading theory, and implementing it in your spare time, then you can probably get a good data science job in 1-2 years. You'll probably need to devote much of your free time to it though.

   I'm assuming that you can already code, given the context :)

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3. larrydagSep 2015
   My favorite intro to R book is The Art of R Programming by Norman Matloff http://www.amazon.com/The-Art-Programming-Statistical-Softwa...
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4. jmountSep 2014
   One of the blog/book authors here (John Mount). Yes the book and blog are both by Nina Zumel and John Mount. Obviously my opinion is biased, but here is a bit anyway. "R in Action" is one of our favorite R books (that and "The Art of R Programming"). "Practical Data Science with R" is more about working examples of data science (lots of the grungy tubing steps, how to think about some of the statistical tests, what sort of software to use at moderate data size). So if you would like the book depends a lot on if you are interested in those steps are not. My more hard-sell push of the book is here: http://www.win-vector.com/blog/2014/06/how-does-practical-da...
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5. doug1001May 2014
   i doubt there is any personal bias (from the author of the blog post). The OP has been an active and prolific member of both the Python and R communities for over a decade (don't know what his interest, if any, is in Julia).

   i have never met Dr Matloff, (who i believe is a professor at UC Davis), but i have read/studied a fair amount of his work over the past 5-7 years, which includes excellent extended tutorials in python on various topics such as co-routines, discrete-event simulation, and simulation using simpy. He is also the author of a book i highly recommend called "Art of R Programming"

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6. dbeckerJan 2013
   If you are looking for a book, "The Art of R Programming" is (by far) my favorite R book.

   It explains a lot of the general principles behind the language, so you can figure out details for yourself (in comparison to, for instance, the R Cookbook, which has hundreds more pages of details and code samples for specific use cases).

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