In case you missed them, here are some articles from January of particular interest to R users.

Animated visualizations and analysis of data from NYC's municipal bike program, created with R.

Many local R user groups are sharing materials from meetups using Github.

A detailed R tutorial on analyzing your Twitter archive and performing sentiment analysis.

How to combine R and Python in Jupyter notebooks.

Many datasets are available for analysis in R using Kaggle's online platform, including the American Community Survey.

Getting started with Markov Chains in R and even more R packages for Markov

Chain analysis.

Replays are available for recent webinars on Microsoft R Open and Microsoft R Server.

Microsoft R Open 3.2.3 (formerly Revolution R Open), and new CRAN Time Machine now available at MRAN.

Overview of parallel computing in R.

R packages providing sources of data.

Visual Studio will soon support the R language.

Microsoft R Server available free to students and developers.

Revolution R is now Microsoft R.

A new ggplot2 extension avoids overlapping text labels.

R played a big part in a scientific breakthrough regarding reproducibility of results.

An online data science course using Microsoft Azure and R.

A review of the 7th R user conference in Spain.

Using network analysis in R to explore connections in the movie "Love Actually".

The most popular posts on the Revolutions blog in 2015.

General interest stories (not related to R) in the past month included: pinball skills, when walking up the escalator is inefficient, Pokemon or Big Data and mimicking famous guitar styles.

As always, thanks for the comments and please send any suggestions to me at davidsmi@microsoft.com. Don't forget you can follow the blog using an RSS reader, via email using blogtrottr, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.

In case you missed them, here are some articles from December of particular interest to R users.

A look back at accomplishments of the R Project and community in 2015.

Segmented regression with the "segmented" package, applied to long-distance running records.

Creating multi-tab reports in R with knitr and jQuery UI.

New version 2.0 update to ggplot2 adds extensibility and many improvements.

A circle diagram of translations of "Merry Christmas".

Upcoming R events and conferences, and sponsorship for R user groups.

How to embed images in R help pages.

An Azure ML Studio fraud detection template relies heavily on R components.

R is the fastest-growing language on Stackoverflow, as shown in a subway-style rank chart from ggplot2.

Buzzfeed is using R for some (serious!) data journalism.

A tutorial on using SQL Server R Services to analyze a billion taxi rides.

Some suggestions on how to cryptographically store secrets in R code.

Some tips and trade-offs to consider when reading large data files with the RevoScaleR package.

A brief summary of improvements in R 3.2.3.

Implementing Wald's sequential analysis test in R.

Using the gtrendsR package to download and chart Google Trends data.

Distributed data structures in R with the ddR package.

Using the leaflet package to create an interactive, photo-annotated map of GPS data from a hike.

Microsoft Azure's Data Science Virtual Machine includes R.

Feature selection when modeling wide data sets with genetic algorithms using the caret package.

Tips on setting up a virtual machine with RStudio in Azure.

Querying recursive CTEs (common table expressions) in a database with the sqldf package.

General interest stories (not related to R) in the past month included: your Macbook charger has more CPU than the

original Macintosh, how 5 particles can jam a hopper, and a film based on the NASA photo archive.

As always, thanks for the comments and please send any suggestions to me at davidsmi@microsoft.com. Don't forget you can follow the blog using an RSS reader, via email using blogtrottr, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.

In case you missed them, here are some articles from November of particular interest to R users.

You can use emojis as plotting symbols in ggplot2 charts with the emoGG package.

A review of local R user group activity in 2015.

Giving thanks to the R Core Group.

Some best practices for handling secret API keys in R scripts.

An animated globe showing locations of Marriott and Starwood hotels using the rthreejs package.

PowerBI has added support for R graphics in PowerBI dashboards.

A detailed R-based analysis of over a billion taxi rides in New York City.

Joseph Rickert recommends books for learning the R language and for data analysis in R.

The AzureML package has been updated to allow R functions to connect with workspaces, datasets, and experiments in Azure

ML Studio.

A simulation-based approach to explaining Simpson's Paradox.

Two new surveys show that R continues to be the most popular language for data scientists.

R was featured in many presentations at this year's H2Oworld conference.

Some tips on handling packages when working with R projects.

A new R integration library for JVM developers: fluent-r.

Online investing service Betterment uses R for modeling, analysis and reporting.

Applications of R were presented at the EARL conference by Verizon, Pfizer, Wikipedia, and many others.

Simulating sample data reproducibly using the wakefield package.

Using the RJSONIO package to download Bitcoin exchange data.

A series on using differential privacy for machine learning.

The R Consortium has funded its first community project, and is now accepting proposals for future projects.

General interest stories (not related to R) in the past month included: ball-moving contraptions in Lego, why you can't photograph propellers, fun with magnets, and a dangerous playground in Australia.

As always, thanks for the comments and please send any suggestions to me at davidsmi@microsoft.com. Don't forget you can follow the blog using an RSS reader, via email using blogtrottr, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.

In case you missed them, here are some articles from October of particular interest to R users.

A video from the PASS 2015 conference in Seattle shows R running within SQL Server 2016. The preview for SQL Server 2016 includes Revolution R Enterprise (as SQL Server R Services).

A way of dealing with confounding variables in experiments: instrumental variable analysis with the ivmodel package for R.

The new dplyrXdf package allows you to manipulate large, out-of-memory data sets in the XDF format (used by the RevoScaleR package) using dplyr syntax.

Some guidelines for using explicit parallel programming (e.g. the parallel package) with the implicit multithreading provided by Revolution R Open.

Ross Ihaka was featured in a full-page advertisement for the University of Auckland in The Economist.

A comparison of fitting decision trees in R with the party and rpart packages.

The foreach suite of packages for parallel programming in R has been updated, and now includes support for progress bars when using doSNOW.

The "reach" package allows you to call Matlab functions directly from R.

A review of support vector machines (SVMs) in R.

A presentation (with sample code) shows how to call Revolution R Enterprise from SQL Server 2016.

A tutorial on using the miniCRAN package to set up packages for use with R in Azure ML.

Asif Salam shows how to use the RDCOMClient package to construct interactive Powerpoint slide shows with R.

A directory of online R courses for all skill levels.

Using R's nls() optimizer to solve a problem in Bayesian inference.

A professor uses the miniCRAN package to deliver R packages to offline facilities in Turkey and Iran.

Amanda Cox, graphics editor at the New York Times, calls R "the greatest software on Earth" in a podcast.

Hadley Wickham answered many questions in a Reddit "Ask Me Anything" session.

A roundup of several talks given at R user group meetings around the world.

General interest stories (not related to R) in the past month included: visualizing the movements of chess pieces, real-time face replication, a world map of antineutrinos, a gender transformation, and a warning about "big data" applications.

In case you missed them, here are some articles from September of particular interest to R users.

A tutorial on using R with Jupyter Notebooks and how to control the size of R graphics therein.

A new version of Revolution R Open is available, featuring multi-threaded computing for R 3.2.2.

One benefit of fitting statistical models to large data sets: learning curves.

Using the AzureML package to publish R functions as web services.

The R Consortium forms a committee to oversee projects, headed by Hadley Wickham.

Functions for interpolation in R.

The EARL London conference (preview here) included many applications of R, from AstraZeneca, Allstate, Douwe Egberts coffee and others.

A new online Data Science and Machine Learning course, featuring R and sponsored by Microsoft.

Reading financial time series data into R with the zoo package.

An update to the checkpoint package brings support for knitr and rmarkdown documents in reproducible projects.

The new Microsoft Data Science User Group Program offers sponsorships for R user groups worldwide.

A series on model validation in R using: basic methods; in-training set measures; out-of-sample procedures; and cross-validation techniques.

BlueSky Statistics, a new open-source GUI for R.

Accessing data in Google spreadsheets with the googlesheets package for R.

Antony Unwin on the care of datasets in R packages.

General interest stories (not related to R) in the past month included: building a scale model of the solar system, a new way to visualize the Discrete Fourier Transform, and a Portal-themed remodel.

As always, thanks for the comments and please send any suggestions to me at david@revolutionanalytics.com. Don't forget you can follow the blog using an RSS reader, via email using blogtrottr, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.

In case you missed them, here are some articles from August of particular interest to R users.

Creating interactive time series charts of financial data in R.

Many R books have been translated into Chinese.

A tutorial on visualizing current-events geographic data with choropleths.

Revolution R Enterprise 7.4.1 is now available on Windows and Linux servers and in the Azure Marketplace.

Zillow uses R to estimate the value of houses and rental properties.

There’s a new (and free) online course on edX for R beginners, sponsored by Microsoft and presented by DataCamp.

Mini-reviews of 5 new R packages: AzureML, distcomp, rotationForest, rpca, and SwarmSVM.

The R Consortium’s best practices for secure use of R.

How to extract data from a SQL Server database in Azure to an R client running Linux.

DeployR Open 7.4.1, the open-source server-based framework for simple and secure R integration for application developers, is now available.

R 3.2.2 is now available.

A review of the JSM 2015 conference and the prevalence of R there.

R is available with Cortana Analytics, which you can learn about in upcoming workshops and webinars.

A comparison of the network structure of the CRAN and Bioconductor repositories.

Using R to find signal in noisy data.

I discussed the R Consortium in the inaugural episode of the R Talk podcast.

An exponential random graph model of connections between CRAN packages.

Using the igraph package to simplify a network graph.

An introductory guide to the Bioconductor project.

An animation shows every commit to the R source code over 18 years.

General interest stories (not related to R) in the past month included: Macklemore on mopeds, reconstructed timelapses, a moving visualization of WW2 fatalities and the Magnus Effect.

As always, thanks for the comments and please send any suggestions to me at david@revolutionanalytics.com. Don't forget you can follow the blog using an RSS reader, via email using blogtrottr, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.

In case you missed them, here are some articles from July of particular interest to R users.

An alternative to stacked bar charts with the streamgraphs package.

Joseph Rickert shares his process for creating the monthly new and updated packages "spotlight" feature on MRAN.

Using R to analyze data from its API reveals R to be the 8th most popular language by activity on StackOverflow.

On accumulating results in R using looping operations.

In an in-depth profile, Hadley Wickham shares his motivations for creating his many useful R packages.

The latest rankings by IEEE Spectrum puts R as the 6th most popular programming language, rising 3 since 2014.

Revolution R Open 3.2.1 is now available, bringing multi-threaded performance and new platforms to the latest R engine.

A look at trends of questions on StackOverflow for Python and R.

Setting up a Linux VM on Azure, and importing data into R from MySQL and mariaDB.

The winners of the 2015 KDD Cup, and how you can analyze the data with R in Azure ML Studio.

The chair of the local committee shares some statistics from the useR! 2015 conference.

A review of R packages for extreme value statistics.

Using the igraph package to create interactive (and embeddable) network graphs from data in R.

Package author Ari Lamstein shares his tips for creating an email-based R course.

In an EMC-sponsored competition to analyze data generated by a motorcycle racer, both winners used R.

A visualization of the network structure of CRAN packages finds connected communities including one centered the "Hadleyverse".

Using R and A/B testing to evaluate the performance of advertising.

A roundup of press generated by the announcement of the R Consortium.

My reflections on the successful 2015 useR! Conference in Denmark.

Experiences using R Markdown and Github for teaching.

Resources from a tutorial on RHadoop, for using R with Hadoop.

General interest stories (not related to R) in the past month included: a short film about impossible business meetings, filming the motion of guitar strings with just a smartphone, an anthem for R users, a short documentary on the mission to Pluto, a review of "Statistics Done Wrong", and a clever illustration of personal bias.

As always, thanks for the comments and please send any suggestions to me at david@revolutionanalytics.com. Don't forget you can follow the blog using an RSS reader, via email using blogtrottr, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.

In case you missed them, here are some articles from June of particular interest to R users.

The R Consortium, a trade group dedicated to the support and growth of the R Community, has launched with the R Foundation, Microsoft, RStudio and others as founding members.

A detailed FAQ for fitting Generalized Linear Models in R.

My presentation on Microsoft’s embrace of R, both in supporting the open-source R community, and connecting R with Microsoft platforms.

Packages for analyzing the RStudio CRAN logs, used to calculate the top 100 R packages by downloads.

Counting the number of packages on CRAN by platform.

Getting data into and out of R applications with DeployR.

A review of the various options for using R with Hadoop.

Using R to search for CRAN packages by topic area.

R code to draw the Archimedes Spiral.

A controversial caution about using only pairwise-complete observations when calculating correlation/covariance matrices in R.

You can use the RBlpapi package to access Bloomberg data with R.

SparkR, a package to use the Spark distributed-computing framework from R, is now part of the Apache Spark project.

An interactive map locates the 160+ R user groups around the world.

R has 64-bit objects, but there are constraints having only 32-bit integers.

R is sometimes called a quirky language, but I argue that these design decisions have directly led to many innovations in statistical computing.

R and BioConductor were featured at “BUILD” (Microsoft’s developer conference in San Francisco), shown being called on-stage from a mobile app.

A review of some of the presentations at R/Finance 2015 in Chicago.

Using the rpud package to calculate distance matrices using the GPU in R.

A tutorial on using Azure as a data source for R.

A comparison of several high-performance computing approaches in R.

General interest stories (not related to R) in the past month included: planning A/B tests, a critique of US state flags, a new type of bearing, a warning about drop bears and a visual comparison of the Game of Thrones books and TV series.

In case you missed them, here are some articles from May of particular interest to R users.

RStudio 0.99 released with improved autocomplete and data viewer features.

A tutorial on the new Naive Bayes classifier in the RevoScaleR package.

R is the most popular Predictive Analytics / Data Mining / Data Science software in the latest KDnuggets poll.

A Shiny application predicts the winner of baseball games mid-game using R.

A list of over 100 open data sources you can use with R.

Revolution R Open 3.2.0 now available, following RRO 8.0.3.

A review of talks at the Extremely Large Databases conference, featuring Stephen Wolfram and John Chambers.

My TechCrunch article on the impact of open source software on business features several R examples.

You can improve performance of R even further by using Revolution R Open with Intel Phi coprocessors.

New features in Revolution R Enterprise 7.4, now available.

The next release of SQL Server will run R in-database.

Create embeddable, interactive graphics in R with htmlwidgets.

Computerworld reviews R packages for data wrangling.

A tutorial on using data stored in the Azure cloud with R.

Using histograms as points in scatterplots, and other embedded plots in R.

A comparison of data frames, data.table, and dplyr with a random walks problem.

A video on using R for human resources optimization.

How to call R and Python from base SAS.

General interest stories (not related to R) in the past month included: a song written by an iPhone, a Facebook algorithm that tells when “like” becomes “love”, a map of light pollution and a machine-learning application that tells you how old you look.