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by Andrie de Vries

In a previous post I demonstrated how to use the igraph package to create a network diagram of CRAN packages and compute the page rank.

Now I extend this analysis and try to find clusters of packages that are close to one another.

A quick heads-up that this Thursday (December 11), Allen Day from MapR and Bill Jacobs from Revolution Analytics will be live presenting a new webinar, Batter Up! Advanced Sports Analytics with R and Storm. The analysis will be of baseball data, but the webinar will be of interest to anyone interested in doing large-scale statistical analysis with R of data in Hadoop. Here's the abstract:

The word "planet" comes an ancient Greek word meaning "wanderer". Our forebears noticed these points of light wandering across the fixed background of stars, eventually figured out they were bodies orbiting the Sun just like the Earth, and finally visited most of them with robotic probes. (The probe to complete that list awakes tomorrow.)  Yet we still haven't landed ourselves on any other planet.

The choice of colors you use in a statistical graphic isn't just about making your chart look good: the colors you choose are often critical to interpretation. For example, you wouldn't want to use a scale like this to represent, say, average income on a map:

by Joseph Rickert

November was an active and creative month for R user groups with over 50 events listed on the Revolution Analytics' Community Calendar. Here are some highlights that can be found by visiting the websites of a few of the groups that post and share presentations.

Datamation has published its list of the Top 20 Big Data Companies and Revolution Analytics is second on the list:

by Andrie de Vries

A few weeks ago Joseph Rickert wrote an excellent post about using the igraph package, illustrating many concepts of using graphs.

If you're a current graduate or undergraduate student and have a knack for data visualization, why not submit a paper to the 2014 ASA Statistical Graphics Student Paper Competition?