The biggest R stories from 2016

It's been another great year for the R project and the R community. Let's look at some of the highlights from 2016.

The R 3.3 major release brought some significant performance improvements to R, along with a spiffy new logo. There were also two updates in 2016: R 3.3.1 and R 3.3.2. (The R 3.2 series also received an update with R 3.2.4.) The R Foundation accepted five new members, and R-core accepted a new contributor as well. 

R’s popularity continued to grow in 2016, as measured by the 2016 O'Reilly Data Science Salary Survey (57%), IEEE Spectrum (5^th rank), and KDNuggets (1^st rank).

The network of R user groups expanded to more than 250 worldwide, bolstered by the rapidly-growing R-ladies network. The useR!2016 conference was a major success with fascinating keynotes, 128 contributed talks (livestreamed and recorded for the first time) covering 154 packages, and a free tutorial series.

The R Consortium was very active in 2016, adding new members IBM and ESRI, awarding several grants for R community projects and working groups, and launching the R-hub project.

R analyses were featured in several major news stories, including ones about Donald Trump's vs his staffers' tweets, conduct in the presidential debates, the Rio Olympics, issues with reproducibility in Psychology, and the FBI aerial surveillance program.

Microsoft continued to make major investments in R in 2016, not least integration of SQL Server and R, support for Spark 2.0 and HDInsight for Microsoft R Server, the Team Data Science Process, R support in PowerBI, and the new Microsoft R Client, Data Science Virtual Machine in Azure, and R Tools for Visual Studio.

The RStudio team released RStudio v1.0 and several packages for R, notably the Tidyverse collection of packages for working with data in R.

And to wrap up, the Revolutions blog was also very active in 2016 with a 23% increase in both pageviews and users compared to 2015. Here are the top 10 stories from 2016, as measured by pageviews:

• Japan's ageing population, animated with R
• Revolution R renamed Microsoft R, available free to developers and students
• Using R to detect fraud at 1 million transactions per second
• R coming to Visual Studio
• Introducing the free Microsoft R Client
• In-depth analysis of Twitter activity and sentiment, with R
• Getting Started with Markov Chains
• Deep Learning Part 2: Transfer Learning and Fine-tuning Deep Convolutional Neural Networks
• An analysis of Pokémon Go types, created with R
• Using Microsoft R Open with RStudio

The ML/DL blog also features a roundup of 2016 news from the R Project, Python, and other open source data science tools.