R: The Good and The Bad
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R: The Good and The Bad

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An overview of the pros and cons of R, the free and open source language and environment for statistical computing and graphics.

An overview of the pros and cons of R, the free and open source language and environment for statistical computing and graphics.

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R: The Good and The Bad R: The Good and The Bad Presentation Transcript

  • R: The Good and The Bad
    AnalyticsCamp NC, May 12, 2011Ian Cook, Organizer, Raleigh-Durham-Chapel Hill R Users Group
  • The Good…
    ?
    =
  • Effectively the lingua franca of data analysis and statistical computing
    Free and open source
    As a statistical language, it’s generally considered to be very easy to code in (vs. SAS, JSL, SPSS, etc.)
    The Good
  • Native cross-platform and 64-bit support
    Typically easy to install and configure
    Community of millions of users; brilliant minds
    Rapidly growing number of packages (2800+ on CRAN, 950+ projects on R-Forge)
    http://cran.r-project.org/web/packages/ and http://r-forge.r-project.org/
    The Good
  • Great free, open soruce IDEs and GUIs (e.g., StatET for Eclipse, RStudio just released in late February, Emacs Speaks Statistics, JGR, Tinn-R, lots more)
    See “Editors and IDEs” and “Graphical User Interfaces” sections of http://en.wikipedia.org/wiki/R_(programming_language). Also see http://sciviews.org/_rgui/ and http://stackoverflow.com/questions/1097367/what-ides-are-available-for-r-in-linux
    The Good
  • Active mailing lists, trolled by the gurus, very easy to get your questions answered
    On a humorous note: http://yihui.name/en/2010/04/rules-of-thumb-to-meet-r-gurus-in-the-help-list/
    CRAN Task Views
    http://cran.r-project.org/web/views/
    The Good
  • Growing coverage on Stack Exchange, also on “CrossValidated” statistical analysis Stack Exchange site
    http://stackoverflow.com/questions/tagged/r and http://stats.stackexchange.com/
    #rstatshashtag on Twitter
    http://twitter.com/search/%23rstats
    Blogger community dedicated to covering R
    http://www.r-bloggers.com/
    Growing list of print books and ebooks
    The Good
  • Commercial and open source data analysis/mining/analytics/visualization software increasingly integrating with R (Spotfire, SPSS, Netezza, JMP, SAS/IML, RapidMiner)
    http://decisionstats.com/2010/05/04/commercial-r-integration-in-software/
    Revolution Analytics (products, blog, community site)
    http://www.revolutionanalytics.com/, http://blog.revolutionanalytics.com/, and http://www.inside-r.org/
    The Good
  • The Bad…
    ?
    =
  • Command prompt, lack of GUI is intimidating
    Slow (especially looping)
    Poor parallelization
    Syntactical curiosities, annoyances, design flaws; little chance of them being remedied
    E.g., http://radfordneal.wordpress.com/2008/09/21/design-flaws-in-r-3-%E2%80%94-zero-subscripts/
    Indices start at 1!
    The Bad
  • Subtle problems with scoping
    http://stackoverflow.com/questions/3840769/scoping-and-functions-in-r-2-11-1-whats-going-wrong
    Poor memory performance, difficulty handing big data
    Can be difficult to compile base R and R packages from source
    Requires compilers for Fortran, Perl, C/C++, Tcl
    The Bad
  • Onerous termsof AGPL
    Has been proposed that the R community start over and build something better from scratch
    Estimated that a total rewrite could improve speed by 2 orders of magnitude
    http://stackoverflow.com/questions/3706990/is-r-that-bad-that-it-should-be-rewritten-from-scratch
    Increasingly attractive alternatives (e.g. Python)
    The Bad
  • The Verdict
    ?
  • Join the Raleigh-Durham-Chapel Hill R Users Group at:http://www.meetup.com/Triangle-useR/