I 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 September:
The deadline to enter the "R Applications" contest with $20,000 in
prizes is October 31: http://bit.ly/qufEjy
The RHadoop Project, a new collection of open-source R packages from
Revolution Analytics, makes it possible to write map-reduce jobs in R
to analyze huge data sets stored in Hadoop: http://bit.ly/nbG3qv . The
slides and replay from a webinar on this project are available for
download: http://bit.ly/offYSJ
Instructions on how to read Google Spreadsheets into R have been
updated to work with Googe's SSL connection: http://bit.ly/nYuSeD
Insurance giant Lloyds of London uses R for performance management,
exposure analysis, Monte-Carlo simulation, data visualization,
reporting, and much more: http://bit.ly/oqlu4k
A summary of discussions on LinkedIn comparing R and SAS for
businesses: http://bit.ly/oWKdtP
A KDnuggets poll finds R to be the most commonly-used software for
data mining and analytics: http://bit.ly/r4aHqo
Fortune magazine declares "Data Scientist" to be the "hot new gig
in
Tech": http://bit.ly/q7ZNCu
Two presentations from Revolution Analytics on analyzing big data with
R: http://bit.ly/r5VbGR
A ggplot2 chart created with R is used to illustrate the "half-life"
of links posted to Facebook, YouTube and Twitter, based on data from
bitly: http://bit.ly/pBqokB
I published an article on ReadWriteWeb, "Unlocking Big Data with R",
with examples from the New York Times, Orbitz and OkCupid:
http://bit.ly/mWqqgR
A review of The Economist's feature article on how incorrect analysis
and failures in reproducible research (detected partly using R) led to
a cancer trial being shut down: http://bit.ly/oRUpVs
An example from Dirk Eddelbuettel on using RCpp to speed up recursive
algorithms in R: http://bit.ly/nq4NdH
Revolution Analytics is running weekly webinars: upcoming topics
include uses of R with SAS in Banking, Revolution R Enterprise, and
Scalable Data analysis in R: http://bit.ly/nVo432
How to create time series in R from very large time-stamped log files:
http://bit.ly/phOf3H
A preview of R 2.14.0, to be released on October 31:
http://bit.ly/mVsg69 . R 2.13.2 was released on September 29:
http://bit.ly/mRKVux
The 2010 "Flash Crash" was the largest one-day stock market decline in
history. An analysis in R of 24 billion trades investigates whether
SEC rules to prevent a reoccurrence are effective:
http://bit.ly/ohOv12
Nathan Yau of FlowingData mentions R in a post about "5 misconceptions
about data visualization", and I take issue with charts that inject a
political point of view (and not to mention chartjunk) into data
visualizations:?http://bit.ly/oaSQQh
Revolution Analytics has partnered with Cloudera to support using R
with Hadoop: http://bit.ly/oSKHh7
R user Harlan Harris created a presentation, "What is a Data
Scientist, anyway", with a history of uses of the term:
http://bit.ly/neWvU9
The R Graph Gallery has added social features, such as the ability to
"like" a chart with Facebook: http://bit.ly/nnAB09
Other non-R-related stories in the past month included: more growth in
analytics and data science jobs (http://bit.ly/r73Ijs), the fastest
method for boarding airplanes (http://bit.ly/pKqxGB), conversations
between chatbots (http://bit.ly/r29KRX), the strange images created by
photographing propellers with iPhones (http://bit.ly/ovCF4D), an
audible illusion (http://bit.ly/p0GR6X), and a visual trigonometric
pun (http://bit.ly/qQLbB4).
There are new R user groups (http://bit.ly/eC5YQe) in Tokyo, Shanghai,
Stamford, Medford and Barcelona: http://bit.ly/ovwoYb . Meeting times
for these groups 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/.
Join the Revolution 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 like Google 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 (Palo Alto, CA, USA)
