Since its first release over eight years ago, the R community has progressively created amazing web-based applications with the Shiny package. In practically every R conference or user meetup, we see amazing examples of how Shiny is changing the …
Data science can be slow. A single round of statistical computation can take several minutes, hours, or even days to complete. The targets R package keeps results up to date and reproducible while minimizing the number of expensive tasks that …
Data science can be slow. A single round of statistical computation can take several minutes, hours, or even days to complete. The targets R package keeps results up to date and reproducible while minimizing the number of expensive tasks that …
Developing Shiny applications that meet design goals, easily deploy to multiple platforms, and contain easily maintainable components (all while adhering to best practices) is typically a difficult endeavor. Until recently, there has not been a tool …
Machine learning workflows can be difficult to manage. A single round of computation can take several hours to complete, and routine updates to the code and data tend to invalidate hard-earned results. You can enhance the maintainability, hygiene, …
Recent advances in the Shiny ecosystem boost the scale and scope of serious enterprise-wide web applications. More specifically, it is entirely possible to utilize key features of Shiny Server Professional and additional R packages such as shinyjs, …
The drake package is a general-purpose workflow manager for data-driven tasks in R, with applications in the pharmaceutical industry ranging from tailored medicine to clinical trial simulation and beyond. Drake rebuilds intermediate data objects when …