r2d3 - R Interface to D3 Visualizations

2018-10-05 RStudio Team
As part our series on new features in the RStudio v1.2 Preview Release, we’re pleased to announce the r2d3 package, a suite of tools for using custom D3 visualizations with R. RStudio v1.2 includes several features to help optimize your development experience with r2d3. We’ll describe these features below, but first a bit more about the package. Features of r2d3 include: Translating R objects into D3 friendly data structures Read more →

sparklyr 0.9: Streams and Kubernetes

2018-10-01 Javier Luraschi
Today we are excited to share that a new release of sparklyr is available on CRAN! This 0.9 release enables you to: Create Spark structured streams to process real time data from many data sources using dplyr, SQL, pipelines, and arbitrary R code. Monitor connection progress with upcoming RStudio Preview 1.2 features and support for properly interrupting Spark jobs from R. Use Kubernetes clusters with sparklyr to simplify deployment and maintenance. Read more →

Getting started with deep learning in R

2018-09-12 Sigrid Keydana
There are good reasons to get into deep learning: Deep learning has been outperforming the respective “classical” techniques in areas like image recognition and natural language processing for a while now, and it has the potential to bring interesting insights even to the analysis of tabular data. For many R users interested in deep learning, the hurdle is not so much the mathematical prerequisites (as many have a background in statistics or empirical sciences), but rather how to get started in an efficient way. Read more →

Shiny 1.1.0: Scaling Shiny with async

2018-06-26 Joe Cheng
This is a significant release for Shiny, with a major new feature that was nearly a year in the making: support for asynchronous operations! Without this capability, when Shiny performs long-running calculations or tasks on behalf of one user, it stalls progress for all other Shiny users that are connected to the same process. Therefore, Shiny apps that feature long-running calculations or tasks have generally been deployed using many R processes, each serving a small number of users; this works, but is not the most efficient approach. Read more →

Applied Machine Learning Workshop

2018-05-15 Roger Oberg
Join Max Kuhn of RStudio for his popular Applied Machine Learning Workshop in Washington D.C.! If you’d missed his sold out course at rstudio::conf 2018 now is your chance. Register here: This two-day course will provide an overview of using R for supervised learning. The session will step through the process of building, visualizing, testing, and comparing models that are focused on prediction. The goal of the course is to provide a thorough workflow in R that can be used with many different regression or classification techniques. Read more →

sparklyr 0.8: Production pipelines and graphs

2018-05-14 Kevin Kuo
We’re pleased to announce that sparklyr 0.8 is now available on CRAN! Sparklyr provides an R interface to Apache Spark. It supports dplyr syntax for working with Spark DataFrames and exposes the full range of machine learning algorithms available in Spark ML. You can also learn more about Apache Spark and sparklyr at and the sparklyr webinar series. In this version, we added support for Spark 2.3, Livy 0. Read more →

leaflet 2.0.0

2018-05-10 Barret Schloerke
leaflet 2.0.0 is now on CRAN! The leaflet R package wraps the Leaflet.js JavaScript library, and this release of the R package marks a major upgrade from the outdated Leaflet.js 0.7.x to the current Leaflet.js 1.x (specifically, 1.3.1). Leaflet.js 1.x includes some non-backward-compatible API changes versus 0.7.x. If you’re using only R code to create your Leaflet maps, these changes should not affect you. If you are using custom JavaScript, some changes may be required to your code. Read more →

Building tidy tools workshop

2018-04-09 Roger Oberg
Join RStudio Chief Data Scientist Hadley Wickham for his popular Building tidy tools workshop in San Francisco! If you’d missed the sold out course at rstudio::conf 2018 now is your chance. Register here: You should take this class if you have some experience programming in R and you want to learn how to tackle larger scale problems. You’ll get the most if you’re already familiar with the basics of functions (i. Read more →

DT 0.4: Editing Tables, Smart Filtering, and More

2018-03-29 Yihui Xie
It has been more than two years since we announced the initial version of the DT package. Today we want to highlight a few significant changes and new features in the recent releases v0.3 and v0.4. The full changes can be found in the release notes. Editable tables Now you can make a table editable through the new argument datatable(..., editable = TRUE). Then you will be able to edit a cell by double-clicking on it. Read more →

reticulate: R interface to Python

2018-03-26 JJ Allaire
We are pleased to announce the reticulate package, a comprehensive set of tools for interoperability between Python and R. The package includes facilities for: Calling Python from R in a variety of ways including R Markdown, sourcing Python scripts, importing Python modules, and using Python interactively within an R session. Translation between R and Python objects (for example, between R and Pandas data frames, or between R matrices and NumPy arrays). Read more →