Planet R

The principle of "small multiples" — displaying multiple charts of the same type to compare differences — was introduced by Bill Cleveland and popularized by Edward Tufte and the "lattice" package in R. Now, the same principle is applied to movie posters in this display of "Over-Used Movie Poster Clichés":



Apparently, a couple standing back-to-back on the poster is a good indicator of a tough-love relationship between the protagonists, and an all-yellow background indicates an adorable indie-flick. Follow the link below for more examples:

FlavorWire: Visual Representations of 15 Over-Used Movie Poster Clichés

Another new local R user group has just started up, this time in Cleveland, OH. The Cleveland R User Group is the brainchild of R user Nicholas Hermez, and their first meeting on February 22 is a get-together to plan future topics, presenters and venues. If you're in the Cleveland area why not drop by and contribute your ideas?

By the way, don't forget that both existing R user groups and new R user groups like the Cleveland group are eligible for sponsor that sponsorships from Revolution Analytics.

MeetUp: Greater Cleveland useR Group

As I've mentioned before, I've always found it a little awkward to introduce myself as a Statistician -- it's not exactly the greatest conversation-generator at cocktail parties (or it just turns conversation to baseball, especially post-Moneyball). So it's nice to see that this is changing, as one of my heroes in Statistics relates:

“Most of my life I went to parties and heard a little groan when people heard what I did,” says Robert Tibshirani, a statistics professor at Stanford University. “Now they’re all excited to meet me.”

I've wholeheartedly embraced "data scientist" as a term because, frankly, it's had more sex appeal than "statistician". Good to see this is changing, and now maybe I can  be an out-and-proud Statistician.

NYT Bits Blog: What Are the Odds That Stats Would Be This Popular?

It's with great pleasure that the team at Revolution Analytics announces the winners of the inaugural "Applications of R in Business" contest:

You can learn more about all of the winning applications in the slideshow on the Applications of R in Business Contest Winners page, in the press release and in the reports in Read Write Web, Enterprise Apps Today and Information Management.

Thanks to everyone who participated in the contest. A special mention is due to Shannon Terry and Ben Ogorek, both from Customer Analytics within Nationwide Insurance. They have been gracious enough to donate both their grand prize and honorable mention prizes to charity Mid-Ohio Foodbank, a 501(c)(3) organization based in Columbus, OH and a close community partner with Nationwide Insurance, will receive $11,000 to support their efforts in hunger relief. What a wonderful contribution!

Revolution Analytics: Applications of R in Business Contest: 2012 Winners 

Last Friday I was fortunate enough to have the opportunity to travel to Boulder, CO and present R and Revolution Analytics to about 20 analysts as part of the Boulder BI Brain Trust (BBBT). It was a great pleasure to describe the vision for Revolution R Enterprise and got some great feedback from the particpants.

During the event, I had a great 10-minute conversation with BBBT president and founder Claudia Imhoff about the R project, how Revolution R Enterprise is used, and the future of Revolution Analytics. The podcast is now live on the web, and you can listen to it at the link below.

BBBT Podcasts: Revolution Analytics 

RBelgium is the latest local R user group to join the R community. Led by R user Jean-Baptiste Poullet, the group will host meetings on the first Friday of each month at the Alfot Hotel in Brussels, as well as weekly coffee get-togethers. The group also provides an on-line discussion forum on statistics and applications with R. 

You can find more information and join the group at MeetUp site linked below.

MeetUp: RBelgium

This is just wonderful:

From the description, I'd assumed that the movie clips would be autotuned to the song, but that appears not to be the case. Matthijs Vlot spent a lot of time finding lines of (approximately) the right pitch here. I predict many other songs will follow in this vein.

Have a great weekend!

Vimeo: Hello from ant1mat3rie  

Hadley Wickham, creator of the ggplot2 packages for R (as well as several others) will present a webinar on February 8 going behind the scenes of the popular graphics package. If you've never used ggplot2 before, this will be a great way to learn about the kinds of charts you can create with it; and if you're a regular ggplot2 user Hadley will give a preview of some of the new big-data visualizations coming soon to the package. Here's the webinar overview:

GGplot2 is one of R’s most popular, widely used packages, developed by Rice University’s Hadley Wickham. Ggplot2’s exploratory graphics capabilities are driving the use of R as a complement to legacy analytics tools such as SAS. SAS is well-regarded for its strength in data management and "production" statistics, where you know what you want to do and need to do it repeatedly. On the other hand, R is strong in data analysis and exploration in situations where figuring out what is needed is the biggest challenge. In this important way, SAS and R are strong companions.

This webinar will provide an all-access pass to Hadley’s latest work. He’ll discuss:

• A brief overview of ggplot2, and how it's different to other plotting systems
• A sneak peek at some of the new features coming to the next version of ggplot2
• What’s been learned about good development practices in the 5 years since first starting to develop ggplot
• Some of the internals of ggplot2, and talk about how he is gradually making it easier for others to contribute

Join this webinar to understand how ggplot2 adds valuable, unmatched capabilities to your analytics toolbox. 

To register for this webinar, follow the link below.

Revolution Analytics webinars: A backstage tour of ggplot2 with Hadley Wickham

A few days ago, Romain François explained how to interface with the Facebook Graph API explorer with R. This was a low-level interface, giving the R programmer the ability to the raw data that Facebook can provide about your connections. Now, just four days later, the first application in R (that I know of) based on the Facebook Graph API has been published.

Petr Simecek describes how to use R to visualize your Facebook friends as an interconnected graph. Petr uses Romain's facebook function to download the friends list via the API, and then constructs the friendship graph using the Rgraphviz package. To enhance the presentation, Petr goes one step further and downloads his friend's profile pictures (again, using the Facebook API and the download.file function), and uses the addlogo function (from the pixmap package) to decorate the nodes of the graph with faces. Here's the final result:

To find the R code to create a chart like this for your own Facebook friend network, follow the link to Petr's blog below.

Apply R: Mining Facebook Data: Most "Liked" Status and Friendship Network (via)

The RInside package provides C++ classes that make it easier to embed R in C++ code on many platforms. According to a post from package co-maintainer Dirk Eddelbuettel, the package has just been updated to version 0.2.6 with improved support on Windows, and compatibility with R's standard random number generator. You can download the latest version from CRAN or from the RInside homepage.

Thinking inside the box: RInside 0.2.6

Last Saturday, the New York Times published a feature article on the wealthiest 1% of Americans. The on-line version of the article included interactive features like this interactive map showing where your household ranks in the country and in local regions. The print edition, however, included some different (and necessarily static) representations of US wealth data, such as this map of where the wealthiest 1% live:

(Image credit: New York Times, January 14 2002.)

Kevin Quealy, graphics editor at the New York Times, used R to help create this chart. The process began with an initial proof of concept, which used R's maptools package and required five lines of R code. 

The original plan was to use ArcMap to generate the chart, but ArcView lacks the flexibility of styling the output that R has. Later iterations added color and algorithmically moved the labels around for legibility, and some final tweaking outside of R led to the chart in the print edition.

Interestingly, the chart doesn't appear in the on-line edition of the NYT. I knew that some features like interactive charts, were online only, but I wasn't aware that the reverse was also true, and that special content was made only for the print edition. Quealy points out that this is a necessity:

This is a good example, I think, of using each medium to its best potential, meeting the design constraints of each. More and more, this means making totally separate versions of things – admittedly, it frequently takes twice the time and energy – but the mediums are just so different that works well in one just doesn’t work well in another. 

For the full story of how this lovely chart was created, check out Kevin Quealy's tubmlr linked below.

chartsnthings: Before, During and After: The Richest 1 Percent