[R] Revolutions blog: December roundup

[David Smith]

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