Happy New Year (if a little late!). Revolution Analytics staff write about R every weekday at the Revolutions blog: http://blog.revolutionanalytics.com and every month I post a summary of articles from the previous month of particular interest to readers of r-help. In case you missed them, here are some articles related to R from the month of December: A ComputerWorld tutorial on basic data processing with R: http://bit.ly/1cvhuqI Prediction: R will replace legacy SAS solutions and go mainstream http://bit.ly/1cvhtmS A chart of the growth of R user groups and local R meetings: http://bit.ly/1cvhuqH I discussed R, data science and big data in an interview with technology journalist Robert Scoble: http://bit.ly/1cvhuqG Looking at the evidence supporting the growth of R and Python: http://bit.ly/1cvhtmQ A replay of Mario Inchiosa?s webinar on scalable cross-platform R-based predictive analytics: http://bit.ly/1cvhuqF A look at the distribution of the number of R package dependencies: http://bit.ly/1cvhuqJ Revolution R Enterprise 7 is now available, with free download for academic users: http://bit.ly/1cvhtD7 Estimating the empirical distribution of Twitter follower counts with R: http://bit.ly/1cvhtD8 How R is used by insurance companies for catastrophe modeling: http://bit.ly/1cvhuqM Sheri Gilley creates an interactive chart of R package dependencies with DeployR, rCharts, and AngularJS: http://bit.ly/1cvhuqO Joseph Rickert offers 15 tips for computing with Big Data in R: http://bit.ly/1cvhuqN Daniel Hanson provides a step-by-step guide to download financial time data from Quandl into R, and then chart and analyze the time series using the xts package: http://bit.ly/1cvhuqR Luba Gloukhov used cluster analysis in R to allocate single-malt scotch whiskies to four distinct flavour profiles: http://bit.ly/1cvhuqS Some non-R stories in the past month included: Big Data Analytics predictions for 2014 (http://bit.ly/1cvhuqT), forced perspective illusions (http://bit.ly/1cvhtDb), analytics with Apache Spark (http://bit.ly/1cvhuqW), wind pattern visualization (http://bit.ly/1cvhuqX), privacy by design (http://bit.ly/1cvhtDc), Big Data Analytics platforms (http://bit.ly/1cvhuHb), the leidenfrost effect (http://bit.ly/1cvhuHa), big data and video gaming (http://bit.ly/1cvhuHi) and an ASCII fluid simulator (http://bit.ly/1cvhtDf). Meeting times for local R user groups (http://bit.ly/eC5YQe) can be found on the updated R Community Calendar at: http://bit.ly/bb3naW If you're looking for more articles about R, you can find summaries from previous months at http://blog.revolutionanalytics.com/roundups/. You can receive daily blog posts via email using services like blogtrottr.com, or join the Revolution Analytics mailing list at http://revolutionanalytics.com/newsletter to be alerted to new articles on a monthly basis. As always, thanks for the comments and please keep sending suggestions to me at david at revolutionanalytics.com . Don't forget you can also follow the blog using an RSS reader, or by following me on Twitter (I'm @revodavid). Cheers, # David -- David M Smith <david at revolutionanalytics.com> VP of Marketing, Revolution Analytics http://blog.revolutionanalytics.com Tel: +1 (650) 646-9523 (Seattle WA, USA) Twitter: @revodavid