RStudio is proud to announce the general availability of RStudio Cloud, its cloud-based platform for doing, teaching, and learning data science. WIth RStudio Cloud, there's nothing to configure and no dedicated hardware or installation required. Individual users, instructors, and students only need a browser. Read more →

Data science teams using Qubole now have the ability to use RStudio Server Pro seamlessly within the Qubole platform to access and analyze large datasets. Read more →

In this post I present three "wild-caught" examples solicited from the R community of how they use interoperability between R, Python and other languages to solve real-world problems. Read more →

Yes, Shiny apps can be fast and scalable. But only if you build them in the right way and use the proper tools. Read more →

We’re excited to announce that the call for talks for rstudio::global(2021) is now open! Since we’re rethinking the conference to make the most of the new venue, the talks are going to be a little different to usual. This year we are particularly interested in talks from people who can’t usually make it in person, or are newer to conference speaking. We’re excited to partner with Articulation Inc to offer free speaker coaching: as long as you have an interesting idea and are willing to put in some work, we’ll help you develop a great talk. Read more →

We’ve made the difficult decision to cancel rstudio:conf(2021) for the health and safety of our attendees and the broader community 😢. Instead, we’re excited to announce rstudio::global(2021): our first ever virtual event focused on all things R and RStudio! We have never done a virtual event before and we’re feeling both nervous and excited. We will make rstudio::global() our most inclusive and global event, making the most of the freedom from geographical and economic constraints that comes with an online event. Read more →

Sparklyr 1.3 is now available, featuring integration of Spark higher-order functions, and data import/export in Avro and in user-defined serialization formats. Read more →

No single platform meets all the analytic needs of every organization. To avoid productivity-sapping complexity and underutilized infrastructure, encourage Interoperability so that your data scientists can access everything they need from their native tools. Read more →

A place for Python applications For data science teams looking to promote data-driven decision making within an organization, interactive applications built in R and Python are often the gold standard. These interactive tools, built by data science teams, are powerful when put in the hands of the right people, but they don’t do much good at all if they only run locally. R users who build Shiny applications hit this roadblock, and so do Python users working with tools like Dash, Bokeh, and Streamlit. Read more →

After evaluating 220 submissions from 183 unique Shiny developers this year, RStudio is proud to finally announce the winners of the 2020 Shiny Contest. Read more →