It's pretty easy (and free!) to download R and install it on your own PC, Mac or Linux machine, but if you don't have one of those or simply aren't ready to commit to installing it, you can now try it out online. R-Fiddle (from DataMind) provides an easy-to-use interactive R console that you can run from your browser....
Blog Archives
The rise of R as the language of analytics
It's no coincidence that while the usage of the R language is skyrocketing (as shown in the recent Rexer Analytics and KDNuggets polls), the growth in data scientist jobs is also skyrocketing. R is the lingua franca of data science, and as the pervasive statistical software in the academic sector, there's a steady-stream of newly-minted graduates trained in R,...
Getting started with R, for Stata users
If you learned statistics using Stata software but have an interest in learning the R language, it's worth checking out R~Stata: Notes on Exporing Data by Princeton's Oscar Torres-Reyna. D-Lab's Laura Nelson provides an overview, but in short it's a collection of 30 PDF slides that introduces R for Stata users, and provides translation tables like the one below...
Iterators in R: a tutorial
Iterators — object-oriented programming constructs that act as a pointer in an ordered sequence — are familiar to programmers of languages like Python, but are not a standard part of the R language. Nonetheless, by installing the iterators package (an open-source contribution by Revolution Analytics) you can create and manipulate iterator objects in R. If you're new to iterators,...
What Data Science can learn from small-data Statistics
Last month I joined Gregory Piatetsky (KDnuggets editor) for a webinar presentation Data Science: Not Just for Big Data, hosted by Kalido. In my portion of the prentation (you can see my slides below), I wanted to react to the Big Data focus which is so much a part of the Data Science movement today, to focus on the...
A detailed guide to memory usage in R
R is designed as an in-memory application: all of the data you work with must be hosted in the RAM of the machine you're running R on. This optimizes performance and flexibility, but does place contraints on the size of data you're working with (since it must all work in RAM). When working with large data sets in R,...
In case you missed it: October 2013 Roundup
In case you missed them, here are some articles from October of particular interest to R users: Joe Rickert recounts the R presence at the Strata + Hadoop World conference, including slides from the R and Hadoop tutorial. Hadley Wickham's favorite tools, gadgets and software (including of course R). Revolution R Enterprise 7 is announced, with updated R engine...
CRAN now has 5000 R packages
Prof. Ripley today announced on the r-devel mailing list that CRAN now has it's 5000th R package: Package 'quint' brought the number of packages on CRAN (for all platforms: some are Windows-only or non-Windows only) to 5000 a few minutes ago: see http://cran.r-project.org/web/packages/index.html. That's quite a milestone! The number of CRAN packages has been increasing rapidly recently, as the...
Was 2013 a record year for strikeouts in World Series Baseball?
The new book Analyzing Baseball Data with R by Max Marchi and Jim Albert is now available, and the authors have also launched a companion blog to share some of the analyses from the book. For example, they used the Lahman package in R to look at the strikeout rate in World Series baseball games over the last century...
Webinar replay: What’s new in Revolution R Enterprise 7
In case you missed yesterday's webinar, the slides and replay are now available for Introducing Revolution R Enterprise 7: The Big Data Big Analytics Platform. I've embedded the slides below — if you're already familiar with Revolution R Enterprise the new features start at Slide 21. You can also download the slides or watch the video replay from the...
Plotly: collaborative, publication-quality graphing. 
