sparklyr 0.8

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. 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 →

TensorFlow for R

2018-02-06 Tareef Kawaf
Over the past year we’ve been hard at work on creating R interfaces to TensorFlow, an open-source machine learning framework from Google. We are excited about TensorFlow for many reasons, not the least of which is its state-of-the-art infrastructure for deep learning applications. In the 2 years since it was initially open-sourced by Google, TensorFlow has rapidly become the framework of choice for both machine learning practitioners and researchers. On Saturday, we formally announced our work on TensorFlow during J. Read more →

sparklyr 0.7

2018-01-29 Kevin Kuo
We are excited to share that sparklyr 0.7 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. You can also learn more about Apache Spark and sparklyr in and our new webinar series on Apache Spark. Features in this release: Adds support for ML Pipelines which provide a uniform set of high-level APIs to help create, tune, and deploy machine learning pipelines at scale. Read more →

pool package on CRAN

2017-11-17 Bárbara Borges
The pool package makes it easier for Shiny developers to connect to databases. Up until now, there wasn’t a clearly good way to do this. As a Shiny app author, if you connect to a database globally (outside of the server function), your connection won’t be robust because all sessions would share that connection (which could leave most users hanging when one of them is using it, or even all of them if the connection breaks). Read more →

Announcing blogdown: Create Websites with R Markdown

2017-09-11 Yihui Xie
Today I’m excited to announce a new R package, blogdown, to help you create general-purpose (static) websites with R Markdown. The first version of blogdown is available on CRAN now, and you can install it with: install.packages("blogdown") The source package is hosted on Github in the repository rstudio/blogdown. Since blogdown is a new package, you may install and test the development version using devtools::install_github("rstudio/blogdown") if you run into problems with the CRAN version. Read more →

Keras for R

2017-09-05 JJ Allaire
We are excited to announce that the keras package is now available on CRAN. The package provides an R interface to Keras, a high-level neural networks API developed with a focus on enabling fast experimentation. Keras has the following key features: Allows the same code to run on CPU or on GPU, seamlessly. User-friendly API which makes it easy to quickly prototype deep learning models. Built-in support for convolutional networks (for computer vision), recurrent networks (for sequence processing), and any combination of both. Read more →