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

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?"

Comments

Pandas

[MightyYar]

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

Re:R...

[radtea]

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.)