In case you missed them, here are some articles from September of particular interest to R users.
The deadline to enter the "R Applications" contest with $20,000 in prizes is October 31.
The RHadoop Project, a new collection of open-source R packages from Revolution Analytics, makes it possible to write map-reduce jobs in R to analyze huge data sets stored in Hadoop. The slides and replay from a webinar on this project are available for download.
Instructions on how to read Google Spreadsheets into R have been updated to work with Googe's SSL connection.
Insurance giant Lloyds of London uses R for performance management, exposure analysis, Monte-Carlo simulation, data visualization, reporting, and much more.
A summary of discussions on LinkedIn comparing R and SAS for businesses.
A KDnuggets poll finds R to be the most commonly-used software for data mining and analytics.
Fortune magazine declares "Data Scientist" to be the "hot new gig in Tech".
Two presentations from Revolution Analytics on analyzing big data with R.
A ggplot2 chart created with R is used to illustrate the "half-life" of links posted to Facebook, YouTube and Twitter, based on data from bitly.
I published an article on ReadWriteWeb, "Unlocking Big Data with R", with examples from the New York Times, Orbitz and OkCupid.
A review of The Economist's feature article on how incorrect analysis and failures in reproducible research (detected partly using R) led to a cancer trial being shut down.
An example from Dirk Eddelbuettel on using RCpp to speed up recursive algorithms in R.
Revolution Analytics is running weekly webinars: upcoming topics include uses of R with SAS in Banking, Revolution R Enterprise, and Scalable Data analysis in R.
How to create time series in R from very large time-stamped log files.
A preview of R 2.14.0, to be released on October 31. R 2.13.2 was released on September 29.
The 2010 "Flash Crash" was the largest one-day stock market decline in history. An analysis in R of 24 billion trades investigates whether SEC rules to prevent a reoccurrence are effective.
Nathan Yau of FlowingData mentions R in a post about "5 misconceptions about data visualization", and I take issue with charts that inject a political point of view (and not to mention chartjunk) into data visualizations.
Revolution Analytics has partnered with Cloudera to support using R with Hadoop.
R user Harlan Harris created a presentation, "What is a Data Scientist, anyway", with a history of uses of the term.
The R Graph Gallery has added social features, such as the ability to "like" a chart with Facebook.
Other non-R-related stories in the past month included: more growth in analytics and data science jobs, the fastest method for boarding airplanes, conversations between chatbots, the strange images created by photographing propellers with iPhones, an audible illusion, and a visual trigonometric pun.
There are new R user groups in Tokyo, Shanghai, Stamford, Medford and Barcelona. Meeting times for these groups can be found on the updated R Community Calendar.
As always, thanks for the comments and please send any suggestions to me at david@revolutionanalytics.com. Don't forget you can follow the blog using an RSS reader like Google Reader, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.
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