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The RHadoop project, the open-source project supported by Revolution Analytics to integrate R and Hadoop, continues to evolve. Now available is version 2 of the rmr package, which makes it possible for R programmers to write map-reduce tasks in the R language, and have them run within the Hadoop cluster. This update is the "simplest and fastest rmr yet", according to lead developer Antonio Piccolboni.

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.