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Open Source Programming Python

Comparing R, Octave, and Python for Data Analysis 61

Here is a breakdown of R, Octave and Python, and how analysts can rely on open-source software and online learning resources to bring data-mining capabilities into their companies. The article breaks down which of the three is easiest to use, which do well with visualizations, which handle big data the best, etc. The lack of a budget shouldn't prevent you from experiencing all the benefits of a top-shelf data analysis package, and each of these options brings its own set of strengths while being much cheaper to implement than the typical proprietary solutions.
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Comparing R, Octave, and Python for Data Analysis

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  • by Anonymous Coward on Wednesday May 23, 2012 @04:26PM (#40093031)

    I wish there was also a column for availibility of resources for learning like: tutorials, free books, example code, etc ....

  • by vlm ( 69642 ) on Wednesday May 23, 2012 @04:28PM (#40093059)

    how analysts can rely on open-source software

    I've done that kind of stuff at work and those criteria are NEVER how a package is selected.

    If I need a commercial product I need all manner of signoffs requiring at least weeks of delay and massive IT involvement so they can insert it into windoze images automatically or whatever it is they do.

    If I'm doing FOSS it just ... gets done that day. No agony. And it just works, and instead of a call center script reader in India who can only tell me to reinstall the software over and over, with FOSS the "whole internet" is my support system and they as in the whole internet know what they're doing.

    Nothing about this has changed in about 15 years, so I'm not sure how this is "news". This would have been a good "news" story in the early/mid nineties.

  • More crap from /. (Score:5, Insightful)

    by NoMaster ( 142776 ) on Wednesday May 23, 2012 @04:35PM (#40093139) Homepage Journal

    "Here is a breakdown of R, Octave and Python ..."

    No there isn't - that's there is not much more than a shitty 'feature' table, too high level to be anything other than facile, which is "Based on [the author's] own user experience and research".

    As an student user of all 3 I would have been interested in reading a good comparative review or explanation aimed at outsiders. This ain't it; it's just more slashvertising.

  • by Anonymous Coward on Wednesday May 23, 2012 @05:42PM (#40093861)

    Besides, in research, using something opensource (or at the very least gratis) makes it that much easier for others to replicate what you did. Getting SAS scripts just isn't fun.

  • Oh.. (Score:3, Insightful)

    by Anrego ( 830717 ) * on Wednesday May 23, 2012 @06:02PM (#40094089)

    Now that's just desperation.

    Come on .. keep this shit in bi. Either it takes off or it doesn't.

  • by Anonymous Coward on Wednesday May 23, 2012 @06:24PM (#40094369)

    I'm an astronomer. At this point in my career, I move to a new research institution every couple of years. Each institution may have a site licence for some piece of commercial software like IDL or Matlab, but I use free software (Python, in my case) because I know that I can keep using it, rather than rewriting all my scripts for a new language every time I move.

  • Both! (Score:4, Insightful)

    by Kludge ( 13653 ) on Wednesday May 23, 2012 @07:32PM (#40094987)

    The best option is to use python and R, through rpy for example.
    R rocks for statistical libraries and good documentation.
    Python rocks for everything else.

Nothing is finished until the paperwork is done.