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.
In this webinar, we'll cover strategies to create reproducible environments in R and the tools you need to implement them.
Upcoming RStudio WebinarsLearn More
What Every Data Scientist Should Know About Education - Greg Wilson
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 - Nathan Stephens
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 - Edgar Ruiz
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 - Carson Sievert
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 - Nathan Stephens
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 - Edgar Ruiz
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.
Usando R para la Ciencia de Datos - Using R for Data Science
La extracción de conocimiento mediante el análisis de datos es usualmente una tarea compleja y ardua. Las extensiones de R, llamadas paquetes, que son parte de lo que en inglés llamamos “tidyverse”.
The R-hub builder is an R package build and continuous integration service. It aims to simplify the R package development process: creating a package, building binaries and continuous integration.