[R] Best way to study internals of R ( mix of C, C++, Fortran, and R itself)?
murdoch.duncan at gmail.com
Tue Nov 21 22:24:42 CET 2017
On 21/11/2017 2:14 PM, Robert Wilkins wrote:
> How difficult is it to get a good feel for the internals of R, if you want
> to learn the general code base, but also the CPU intensive stuff ( much of
> it in C or Fortran?) and the ways in which the general code and the CPU
> intensive stuff is connected together?
That's a pretty difficult question to answer. How hard compared to what?
> R has a very large audience, but my understanding is that only a small
> group have a good understanding of the internals (and some of those will
> eventually move on to something else in their career, or retire
That's true, but the good news is that there are people who know the
internals now who didn't know them 5 or 10 years ago. So there is
renewal happening. And there are a number of independent
implementations of the language or subsets of it; see the Wikipedia
> While I'm at it, a second question: 15 years ago, nobody would ever offer a
> job based on R skills ( SAS, yes, SPSS, maybe, but R skills, year after
> year, did not imply job offers). How much has that changed, both for R and
> for NumPy/Pandas/SciPy ?
The web page <http://r4stats.com/articles/popularity/> is fairly up to
date. It doesn't say what things were like in 2002, but in early 2017,
the ranking was Python > R > SAS in the count of job ads in data
science. In 2012 it was SAS > Python > R (but R and Python were very
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