Parameterize an R Markdown report using Shiny components — yml_params • ymlthis
R Markdown lets you add dynamic parameters to your report using the params YAML field (see the R Markdown book for examples); parameterized reports are also used in RStudio Connect. The values of these variables can be called inside your R Markdown document using params$field_name. There are several ways to change the values of the parameters: manually change the YAML, use the params argument in rmarkdown::render(), or knit with parameters, which launches a Shiny app to select values for each. yml_params() accepts any number of named R objects to set as YAML fields. You can also pass argume...
The first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages.
Overview Administering RStudio server products often requires you to test changes to your environment, but testing changes can be problematic in production. For example, upgrading R can disrupt dev...
Package Manager 1.1.0 - No Interruptions | RStudio Blog
No interruptions. That was our team’s goal for RStudio Package Manager 1.1.0 - we set out to make R package installation fast enough that it wouldn’t interrupt your work. More and more data scientists use Linux environments, whether to access extra horsepower during development or to run production code in containers. Unfortunately, the rise in Linux environments has seen a corresponding increase in package installation pain. For Windows and Mac OS, CRAN provides pre-compiled binary packages that install almost instantly, but the same binaries are not available on Linux.
Scaling and Performance - Tuning Applications in Shiny Server Pro – RStudio Support
Shiny Server Pro allows you to scale Shiny applications to support multiple simultaneous users. The scaling is accomplished by setting 3 arguments in the configuration file (/etc/shiny-server/shiny...