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Ask Slashdot: Switching From SAS To Python Or R For Data Analysis and Modeling? 143

Posted by timothy
from the in-the-parlance-of-our-times dept.
An anonymous reader writes "I work for a huge company. We use SAS all the time for everything, which is great if you have a bunch of non-programmer employees and you want them to do data analysis and build models... but it ends up stifling any real innovation, and I worry we will get left behind. Python and R both seem to be emerging stars in the data science game, so I would like to steer us towards one of them. What compelling arguments can you give that would help an old company change its standard if that company is pretty set in its ways?"
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Ask Slashdot: Switching From SAS To Python Or R For Data Analysis and Modeling?

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  • Pandas (Score:5, Interesting)

    by MightyYar (622222) on Thursday July 03, 2014 @09:35AM (#47376137)

    Python and R are sort-of converging via Pandas [pydata.org]. I'm partial to Python, but Pandas really starts to blur the lines conceptually.

  • by Alan Shutko (5101) on Thursday July 03, 2014 @10:21AM (#47376619) Homepage

    I work for a large Fortune 25 company. We have an existing SAS presence and we do some good work in SAS. There are two main reasons that we are bringing R into our environment: research and recruitment/retention.

    R is extremely common across research right now. When a new paper comes out describing a new algorithm or modeling technique, the odds are extremely good that it comes with R source code. With R in-house, there is very little time or effort to try these things out to see if they can help our current work. With SAS, we would need to invest time recoding everything or worse, wait until it is baked into SAS itself. That is a huge barrier to adopting new approaches.

    Recruitment and retention are related to R's popularity in research. Let's face it, data scientists are a hot commodity right now. Lots of companies are looking to hire them and there aren't enough good people to go around. We're seeing that a lot of the new talent have been using R in their graduate work rather than SAS, and are interested in an environment where they can continue using R. Additionally, it's harder to retain people once you've hired them if they can't use what's become a lingua franca.

    SAS remains a great tool, and we're not going to get rid of it. Rather, we want to add R to the toolbox.

    (I don't mention python here... We've got some folks working with Python especially for NLP, but for the work we do there's a lot more folks using R across industry and academia.)

  • by Anonymous Coward on Thursday July 03, 2014 @10:26AM (#47376677)

    I work in IT at a large company (>30k employees) who recently dropped SAS. Before we did, we tried out R but what we found out was that except for IT and some tech savvy engineers, nobody seemed to get anything done without help, even after training.
    We had decided to drop SAS due to the ludicrous license costs (at one point we were paying more on renewals than we did when we purchased it! WTF?) and due to some issues with their installation/upgrade process that they were not able to resolve within a reasonable timeframe. We ended up switching to StatSoft's STATISTICA, which has a much lower price point (~30% of what we paid for SAS), predictable renewal fees (20% of purchase price), vast feature set (in the Data Miner package we have), excellent Office integration and import/export compatibility with SAS data files. Oh, and it also features R integration so you can still use R from within it if you want. Users became proficient very quickly, after receiving some training.
    I recommend you consider their solutions... Open source is not always best, especially when it comes to borderline tech-illiterate business users.

  • Re:R... (Score:5, Interesting)

    by radtea (464814) on Thursday July 03, 2014 @01:10PM (#47378343)

    So can Python do everything that R can?

    No, but Rpy can.

    I've used R, and it really has a lot of strong points, but I prefer to access it these days via Rpy, which gives me all the power of R along with everything else I get from Python (other libraries, better application development frameworks, etc.)

    Both R and Python are real programming languages that are going to be completely useless to non-programmers, so neither of them is a SAS replacement, but of the two, I'd choose Python+Rpy over R for flexibility, power and ease of use (the latter is of course a strongly personal preference... if you really think like a traditional stats geek R will likely seem nicer, as it is clearly created for and by such people.)

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