Come see RStudio at JSM in Boston

2014-08-01 Roger Oberg
The Joint Statistical Meetings (JSM) start this weekend! We wanted to let you know we’ll be there. Be sure to check out these sessions from RStudio and friends: Sunday, August 3 4:00 PM: A Web Application for Efficient Analysis of Peptide Libraries: Eric Hare*+ and Timo Sieber and Heike Hofmann 4:00 PM: Gravicom: A Web-Based Tool for Community Detection in Networks: Andrea Kaplan*+ and Heike Hofmann and Daniel Nordman Monday, August 4 Read more →

Shiny 0.10.1

2014-08-01 Yihui Xie
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Shiny v0.10.1 has been released to CRAN. You can either install it from a CRAN mirror, or update it if you have installed a previous version. install.packages('shiny', repos = 'http://cran.rstudio.com') # or update your installed packages # update.packages(ask = FALSE, repos = 'http://cran.rstudio.com') The most prominent change in this patch release is that we added full Unicode support on Windows. Shiny apps running on Windows must use the UTF-8 encoding for ui. Read more →

The R Markdown Cheat Sheet

2014-08-01 Garrett Grolemund
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R Markdown is a framework for writing versatile, reproducible reports from R. With R Markdown, you write a simple plain text report and then render it to create polished output. You can: Transform your file into a pdf, html, or Microsoft Word document—even a slideshow—at the click of a button. Embed R code into your report. When you render the file, R will run the code and insert its results into your report. Read more →

httr 0.4

2014-07-31 Hadley Wickham
httr 0.4 is now available on CRAN. The httr packages makes it easy to talk to web APIs from R. The most important new features are two new vignettes to help you get started and to help you make wrappers for web APIs. Other important improvements include: New headers() and cookies() functions to extract headers and cookies from responses. status_code() returns HTTP status codes. POST() (and PUT(), and PATCH()) now have an encode argument that determine how the body is encoded. Read more →

Announcing Shiny Server Pro 1.2

2014-07-24 Roger Oberg
RStudio is very pleased to announce the general availability of Shiny Server Pro 1.2. Download a free 45 day evaluation of Shiny Server Pro 1.2 Shiny Server Pro 1.2 adds support for R Markdown Interactive Documents in addition to Shiny applications. Learn more about Interactive Documents by registering for the Reproducible Reporting webinar August 13 and Interactive Reporting webinar September 3. We are excited about the new ways in which you can now share your data analysis in Shiny Server Pro along with the security, management and performance tuning capabilities you and your IT teams need to scale. Read more →

New data packages

2014-07-23 Hadley Wickham
I’ve released four new data packages to CRAN: babynames, fueleconomy, nasaweather and nycflights13. The goal of these packages is to provide some interesting, and relatively large, datasets to demonstrate various data analysis challenges in R. The package source code (on github, linked above) is fully reproducible so that you can see some data tidying in action, or make your own modifications to the data. Below, I’ve listed the primary dataset found in each package. Read more →

Announcing Packrat v0.4

2014-07-22 Kevin Ushey
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We’re excited to announce a new release of Packrat, a tool for making R projects more isolated and reproducible by managing their package dependencies. This release brings a number of exciting features to Packrat that significantly improve the user experience: Automatic snapshots ensure that new packages installed in your project library are automatically tracked by Packrat. Bundle and share your projects with packrat::bundle() and packrat::unbundle() – whether you want to freeze an analysis, or exchange it for collaboration with colleagues. Read more →

Introducing tidyr

2014-07-22 Hadley Wickham
tidyr is new package that makes it easy to “tidy” your data. Tidy data is data that’s easy to work with: it’s easy to munge (with dplyr), visualise (with ggplot2 or ggvis) and model (with R’s hundreds of modelling packages). The two most important properties of tidy data are: Each column is a variable. Each row is an observation. Arranging your data in this way makes it easier to work with because you have a consistent way of referring to variables (as column names) and observations (as row indices). Read more →

Master interactive documents at the Shiny Dev Center

2014-07-21 Garrett Grolemund
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We’ve added a new section of articles to the Shiny Development Center. These articles explain how to create interactive documents with Shiny and R Markdown. You’ll learn how to Use R Markdown to create reproducible, dynamic reports. R Markdown offers one of the most efficient workflows for writing up your R results. Create interactive documents and slideshows by embedding Shiny elements into an R Markdown report. The Shiny + R Markdown combo does more than just enhance your reports; R Markdown provides one of the quickest ways to make light weight Shiny apps. Read more →

RStudio presents Essential Tools for Data Science with R

2014-07-16 Roger Oberg
The RStudio team recently rolled out new capabilities in RStudio, shiny, ggvis, dplyr, knitr, R Markdown, and packrat. The “Essential Tools for Data Science with R” free webinar series is the perfect place to learn more about the power of these R packages from the authors themselves. Click to learn more and register for one or more webinar sessions. You must register for each separately. If you miss a live webinar or want to review them, recorded versions will be available to registrants within 30 days. Read more →