[R] Learning advanced R

[Barry Rowlingson]

Depending on your application, I'm not sure there's much point in being an
"advanced R programmer" these days. Become an adequate R programmer, and
learn C++ and Rcpp. Do basic data mashing in R, then do all your intensive
stuff in C++ with Rcpp. Eventually you'll probably get to the point where
you can express yourself in C++ as fast as you can in interpreted R, with
the bonus of C++ speed, type-safety etc.

</controversial>

On Wed, Mar 14, 2018 at 8:13 AM, Eric Berger <ericjberger at gmail.com> wrote:

> Bert's suggestion is good as a pointer to a variety of resources.
> Sticking to the book format there are two of Hadley Wickham's books, which
> have the advantage that they are freely available.
> You can either read them online or download the source from github and
> create your own copy (which you can then print, if desired.)
> 1. "R for Data Science"
>      online: http://r4ds.had.co.nz/
>      github: https://github.com/hadley/r4ds
> 2. "Advanced R"
>      online: https://adv-r.hadley.nz/
>      github: https://github.com/hadley/adv-r
>
> Best,
> Eric
>
>
>
> On Wed, Mar 14, 2018 at 12:13 AM, Rich Shepard <rshepard at appl-ecosys.com>
> wrote:
>
> > On Tue, 13 Mar 2018, Mark Leeds wrote:
> >
> > See Hadley's advanced R
> >>
> >
> >   +1 A very well writte, highly useful book. Recommended.
> >
> > Rich
> >
> >
> > ______________________________________________
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> > ng-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
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>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/
> posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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