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As a language for statistical computing, R has always had a bias towards linear algebra, and is optimized for operations dealing in complete vectors and matrixes. This can be surprising to programmers coming to R from lower-level languages, where iterative programming (looping over the elements of a vector or matrix) is more natural and often more efficient. That's not the case with R, though: Noam Ross explains why vectorized programming in R is a good idea:   

A new Task View on CRAN will be of anyone who needs to connect R with Web-based applications. The Web Technologies and Services Task View lists R functions and pacakges for reading data from websites (via public APIs or by scraping data from HTML packegs); for interfacing with Cloud-based platforms (including AWS); for authenticating and accessing data from social media services (including Twitter and Facebook); and for integrating with Web frameworks for building your own Web-aware applications with R.

You've probably seen dozens of those brand videos from big corporations, carefully designed to make you feel good about how wonderful the company is. This one is just like all the others, except that it's based on a satirical poem by Kendra Eash and made entirely of stock video footage (which you can buy from the company that made the video, which is rather meta).

 

Here's something fun you can do with R and its interface to Twitter, the TwitteR package. An R script by CMU student Mark Patterson downloads your Twitter profile picture, counts the number of Twitter followers you have, and then creates a pointillist version of your profile picture with as many dots as you have followers.

As announced this morning on mailing list, R 3.1.0 (codenamed "Spring Dance") has been released. The source code is available now; as of this writing binary versions haven't yet appeared on CRAN or propagated to the mirrors, but I expect they'll be available in a day or two.

You can check out the full list of changes in the Release Notes, but the highlights include: