Webinars and videos are presented on a variety of subjects. We will cover packages, products (both Open Source & Commercial), have guest presenters, as well as general Q&A “Office Hour” recordings. All materials will be made available and at no cost. Our GitHub webinar repository for all webinars: https://github.com/rstudio/webinars.
A Gentle Introduction to Tidy Statistics in R
R is a fantastic language for statistical programming, but making the jump from point and click interfaces to code can be intimidating for individuals new to R.
Upcoming RStudio WebinarsLearn More
RStudio Cloud in the Classroom
Much has been written in the statistics and data science education literature about pedagogical tools and approaches to provide a practical computational foundation for students.
In this webinar, we'll cover strategies to create reproducible environments in R and the tools you need to implement them.
What Every Data Scientist Should Know About Education
Thousands of programmers teach coding, web design, robotics, and other skills in the workplace or after-school programs and bootcamps, but most have never been taught how to teach well.
Best Practices for Administering RStudio in Production
Most organizations are unfamiliar with the R programming language. As a result they often struggle to onboard and manage R in production. In this webinar we introduce the RStudio Quickstart...
Programación con R
Hay ocasiones que, cuando trabajamos en un análisis en R, necesitamos dividir nuestros datos en grupos, y después tenemos que correr la misma operación sobre cada grupo.
Accessing and responding to Plotly events in Shiny
For several years now, the Plotly package has provided an `event_data()` function for accessing click, hover and drag event information in Shiny. This functionality provides a powerful way to build...
Make PowerPoint Presentations with R Markdown
This webinar demonstrates how to create feature rich PowerPoint presentations from R Markdown and how to use these presentations to share insights, visualizations, Shiny apps, and more.
Convenient analysis with broom - Alex Hayes
In this webinar I’ll demonstrate how to use to broom to work with many models at once.
Reproducible Finance with R - Jonathan Regenstein
In this webinar, we will create and code a real (but simple) portfolio analysis in order to explore R's data import, wrangling, and visualization tools in the world of investment management.
Introduction to the RStudio Package Manager - Sean Lopp
This webinar will introduce RStudio Package Manager, a new product to organize R packages across teams, departments, and organizations.
Help me help you. Creating reproducible examples - Jenny Bryan
What is a reprex? It’s a reproducible example. Making a great reprex is both an art and a science and this webinar will cover both aspects.
Load testing Shiny - Alan Dipert
shinyloadtest and shinycannon are two new tools that work together to help you answer the question: how many users can my app support?
R, RStudio 1.2 & Python a love story - Sean Lopp
We'll discuss R’s history of interoperability and the philosophy of Reticulate, the Reticulate-powered features in RStudio 1.2, and talk through a case study of a reticulated Shiny app
How to Work with List Columns - Garrett Grolemund
This webinar breaks down one of the most esoteric concepts in the tidyverse: list columns.
Plumbing APIs with plumber - Jeff Allen
Plumber is an open-source R package that converts your existing R code into a web API; this enables you to leverage your R code from other platforms or programing languages.
Comunicando resultados con R
Professional R tooling and integration - Nathan Stephens
Many organizations do not officially recognize R as a standard or integrate R with IT managed systems. Yet these same organizations employ data science teams that use R on a daily basis.
Debugging techniques in RStudio
Fortunately, there are excellent tools built into R and RStudio that can make debugging easier.
Scaling Shiny apps with asynchronous programming
Asynchronous programming offers a way to offload certain classes of long-running operations from the main R thread, such that Shiny apps can remain responsive.