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Programming Stats Math Open Source Python

R Throwdown Challenge 185

theodp (442580) writes "'R beats Python!' screams the headline at Prof. Norm Matloff's Mad (Data) Scientist blog. 'R beats Julia! Anyone else wanna challenge R?' Not that he has anything against Python, Matloff adds, but he just doesn't believe that Python or Julia will become 'the new R' anytime soon, or ever. Why? 'R is written by statisticians, for statisticians,' explains Matloff. 'It matters. An Argentinian chef, say, who wants to make Japanese sushi may get all the ingredients right, but likely it just won't work out quite the same. Similarly, a Pythonista could certainly cook up some code for some statistical procedure by reading a statistics book, but it wouldn't be quite same. It would likely be missing some things of interest to the practicing statistician. And R is Statistically Correct.'"
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R Throwdown Challenge

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  • Re:Bad analogy (Score:5, Interesting)

    by Glock27 (446276) on Sunday May 25, 2014 @08:08AM (#47086871)

    Exactly. Julia will eat R for lunch soon enough, I think. It's an elegant, well designed and efficient language. It's only been around for a couple of years, and has a very vibrant and rapidly growing community.

    Check it out for yourself: The Julia Language Homepage []. It's got a lot to offer anyone with an interest in mathematics, including statisticians. It's based on the LLVM, and interfaces trivially with C libraries - plus it's a very fast language in it's own right, unlike R or Python.

  • by jythie (914043) on Sunday May 25, 2014 @08:44AM (#47086947)
    *nods* who uses a language has more impact on its usefulness then anything inherent to the language. LIbraries, support community, easy of hiring people who both know the language and have domain specific skills, much more important then what kind of sugar the language has.
  • Re:Bad analogy (Score:5, Interesting)

    by retchdog (1319261) on Sunday May 25, 2014 @08:48AM (#47086959) Journal

    my friend uses julia, and every few weeks complains about some bug. the other day he mentioned that the latest release broke Bernoulli sampling (wtf?). the others have been pretty fundamental too.

    this is a serious problem, of course. the other one is lack of libraries. R is an abysmal pile of shit, but at least it's a standard; pretty much 95%+ of applied stats is at least partially supported by someone's hacked-up library/package. julia is far, far short of that, and it appears that much of its community is more interested in pretty graphics, meta-wankery, and interface methodology than actual working statistics (not that there's anything wrong with that per se).

    yeah, yeah, "fix it yourself," and it's on my list to write at least a basic survival analysis package for it. but i wouldn't blame anyone for not using it, and i wouldn't recommend it for doing stats as it is now.

  • Re:Data mining (Score:2, Interesting)

    by Anonymous Coward on Sunday May 25, 2014 @09:02AM (#47087007)

    You got the title wrong.

    _Numerical Recipes in C_, by Press, W. et al

    IIRC there was also a _Numerical Recipes in FORTRAN_ as well.

    Also see . I think they only have a single book now called _Numerical Recipes_ and it is in its third edition.

  • by HuguesT (84078) on Sunday May 25, 2014 @09:13AM (#47087061)

    R has some pretty unique graphing packages. Nothing that I know of matches the way you can do 2D and 3D plots in R. Not Python, not Gnuplot, not Julia, not Matlab, not Excel, not Mathematica, nothing.

  • Re:I dislike Python (Score:4, Interesting)

    by KingOfBLASH (620432) on Sunday May 25, 2014 @09:48AM (#47087183) Journal

    Believe it or not, most statisticians are not programming wizards.

    Most stats guys use R, matlab, mathematica, or something similar. Even if it takes days to run a program that would take 20 minutes in C. Sort of like how the business guys will use VBA when they need anything, because that's what they know.

    Languages like R are used because they are accessible. And once they reach a critical mass, everyone learns them in a field.

    Sort of like how Fortran just won't die.

  • by umafuckit (2980809) on Sunday May 25, 2014 @10:09AM (#47087277)
    A few examples are provided in TFA but it's all rather vague as to why R "beats" Python. I've been using R for years for fitting mixed effects linear models. It does this really well, it makes it easy to compare models, it's got all the cutting-edge stuff in it. The problem with R, however, is that it's shitty and unintuitive as a programming language. I do all my pre-processing in MATLAB and I only ever export to R when I have a final data frame that needs a moderately complicated statistical analysis.

All Finagle Laws may be bypassed by learning the simple art of doing without thinking.