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Python Open Source

Is Python a Legitimate Data Analysis Tool? 67

Back in May we discussed using Python, R, and Octave as data analysis tools, and compared the relative strength of each. One point of contention was whether Python could be considered a legitimate tool for such work. Now, Bei Lu writes while Python on its own may be lacking, Python with packages is very much up to the task: "My passion with Python started with its natural language processing capability when paired with the Natural Language Toolkit (NLTK). Considering the growing need for text mining to extract content themes and reader sentiments (just to name a few functions), I believe Python+packages will serve as more mainstream analytical tools beyond the academic arena." She also discusses an emerging set of solutions for R which let it better handle big data.
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Is Python a Legitimate Data Analysis Tool?

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  • It Works (Score:5, Insightful)

    by mrsquid0 ( 1335303 ) on Friday July 06, 2012 @02:56PM (#40567633) Homepage

    Python may not be a legitimate data analysis tool, but it is widely used for data analysis, and it gives the right results. For the most part that is what really matters.

  • Re:It Works (Score:5, Insightful)

    by mcgrew ( 92797 ) * on Friday July 06, 2012 @03:01PM (#40567699) Homepage Journal

    Python is a language. It's a tool to build other tools with, including data analysis tools.

  • Use what works (Score:5, Insightful)

    by hawguy ( 1600213 ) on Friday July 06, 2012 @03:12PM (#40567889)

    Since people do use python for data analysis (hence the data analysis related packages that are available), of course it's legitimate.

    Just like how when you're standing on the roof and you need to pound in a couple nails, that heavy pair of pliers in your pocket is a legitimate tool. It may not be the best tool for the job, the best tool might be a pneumatic nail gun, but if all you have with you and what you know how to use is pliers, then that's the right tool. Why spend time and money learning some other "more appropriate" language (or buying an air compressor and nail gun) when you already have a tool at your fingertips that will do what you need.

    As your needs grow you might need to find another more appropriate tool, but if you can get the job done with Python, why bother searching for the "perfect" tool?

    Depending on your needs, sh, awk, sed, sort, and uniq may be all the tools you need - many log parsing, analysis and reporting programs have been writing with those tools, often ingesting more rows of data per day than many small business BI systems.

  • Re:It Works (Score:5, Insightful)

    by ceoyoyo ( 59147 ) on Friday July 06, 2012 @03:19PM (#40568005)

    What does "legitimate data analysis tool" mean? MatLab was included in the comparison, and MatLab is more of an engineering tool. The built in (excuse me, optional paid for) stats library is pretty limited.

    R is great for doing statistical analysis, but it's not great for doing things like image analysis. Without additional libraries R isn't nearly as good as it is with libraries either.

  • by hey! ( 33014 ) on Friday July 06, 2012 @05:51PM (#40569997) Homepage Journal

    Alright, you're old-fashioned. And you're mixing up apples and oranges.

    I think what most people these days are talking about is not just having some kind of online analytics data resource, but having a system where having that resource is taken as a given and the task is to use mathematics and AI to classify records, discover patterns and relationships, locate unusual data (without necessarily specifying the nature of the anomaly in advance), and whatnot.

    A spreadsheet is fine for doing simple summaries of small, heterogeneous, tabular datasets (calculating averages and whatnot). But it's not going to help you find one record out of millions where your search criteria are too complex to be expressed in a SQL where clause.

"Hey Ivan, check your six." -- Sidewinder missile jacket patch, showing a Sidewinder driving up the tail of a Russian Su-27