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Video
Effective use of Shiny modules in application development
As a Shiny application grows in scale, organizing code into reusable and streamlined components becomes vital to manage future enhancements and avoid unnecessary duplication.
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Empowering a data team with RStudio addins
RStudio addins provide a mechanism to extend RStudio in various ways. Addins can interact with the RStudio IDE through RStudio API. It can also provide users a graphical interface with...
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Getting it right: Writing reliable and maintainable R code
How can you tell that your scripts, applications, and package functions are working as expected? Are you sure that when you make changes in one part of the code, it won't break something in...
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Integrating React.js and Shiny
React.js is a thriving JavaScript library that eases encapsulating and sharing sophisticated component libraries. The React.js ecosystem is filled with components for doing everything from...
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Introducing mlflow
We introduce the R API for MLflow, which is an open source platform for managing the machine learning lifecycle. We demonstrate each component of the platform–Tracking, Projects, and...
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Introducing the gt package
With the gt package, anyone can make great-looking display tables. Though the package is still early in development, you can do some really great things with it right now!
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Introductory statistics with R: Easing the transition to software for beginner students
In this talk, we will present our approach to incorporating R and RStudio into a 10-week introductory statistics course for non-majors Cal Poly. Our primary contribution will be to...
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It depends: A dialog about dependencies
Software dependencies can often be a double-edged sword. On one hand, they let you take advantage of others' work, giving your software marvelous new features and reducing bugs.