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Shiny Contest Grand Prize Winner, Marcin Dubel, explains his process for building a Shiny video game

Make your code reviewer comentless with these 5 Tips on How to Write Clean R Code - From basic comments to best programming practices.

Nobody likes a slow and unmaintainable Shiny dashboard. You should refactor yours right away.

This article will show you how to speed up R Shiny by pushing actions to the browser. You will learn how to omit the server bottleneck with updateInput, leverage CSS classes, and take advantage of JavaScript actions for smoother Shiny performance.

In this talk you’ll learn tools and best practices for making clean, reproducible R code in a working environment ready to be shared and productionized. We cover the benefits of version control, plumber, RStudio Connect, and many other tools.

Have you considered adding AI/ML to your organization's operations? AI models can significantly reduce costs when they are implemented properly, but can end up in "purgatory" with the wrong approach. Here's how to properly implement AI models.

"So we sat down with the project manager on the client side, re-ordered the priorities, estimated additional work and were able to start coding on the very same day."

The city of Poznań wanted to know why it didn't rate highly with tourists. So they gave loads of data to a gathering of developers to gain some insight. TL;DR: we learned a lot from the hackathon & won the thing. R Shiny gave us a slight edge. :)

Describes the best practices for setting automated test architecture for R Shiny apps. Automate and test early and often with unit tests, user interface tests, and performance tests.

For advanced R Shiny applications, R6 classes help you organize your code. The Hows and Whys of using object-oriented programming (OOP) in Shiny applications...

Two methods for keeping your Shiny app organized while avoiding hardcoding. Also, a tip for adding multiple languages (internationalization) to your app.

The WhyR Conference was held in Warsaw in 2019. I enjoyed the workshops and keynotes on Natural Language Processing (NLP), geocomputation, spatial analysis, random forests, text analysis, quanteda, data scientist's responsibilities