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Jeffrey Breen (the man behind the Twitter airline sentiment analysis example) recently posted a collection of slides with some great tips for accessing data from R.

The next minor update to R — version 2.15.2 "Trick or Treat" — will be released on October 26, R-core member Peter Dalgaard announced today. You can find the planned updates in the current NEWS file (scroll down to the section 'CHANGES IN R VERSION 2.15.1 patched'; the changes at the top of the file are planned for the next major release).

The changes will include:

The Maker Movement has led to the production of open-source 3-D printers and other manufacturing machines that allow hobbyists to design, create and produce real-world objects affordably.

How can this slowly moving ball bearing translate into enough power to launch the can from the table?

As an open-source project, the R source code has always been available to download from the R-project website. You can find source code for the latest released version here, and for the changing-daily new version in progress (R-devel) here.

Last month we shared an visualization showing the changing extent of Arctic sea-ice. This visualization by the multinational Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) switches the view to the Southern pole and takes the visualization to a whole new level, by animating it in 3-D:

I had a great time yesterday moderating the "R in Action" panel discussion at the DataWeek conference in San Francisco. Each of the panelists represented a company that is actively using R and/or Revolution R Enterprise. Here (from memory, since I couldn't take notes) are some the things they shared:

I'm back from a very relaxing holiday in Australia. Many thanks to our guest bloggers for filling in over the last couple of weeks with some great information about R while I was away. If you missed any of the posts, be sure to check them out:

Coursera offers a number of on-line courses, all available for free and taught by experts in their fields. Today, the course Computing for Data Analysis begins. Taught by Johns Hopkins Biostatistics professor (and co-author of the Simply Statistics blog) Roger Peng, the course will teach you how to program in R and use the language for data analysis.

Today's guest post comes from Revolution Analytics data scientist Luba Gloukhov — ed.