So, not only is it possible to learn modules early, it may actually be decidedly easier than the alternative depending on your frame of mind. Shiny’s tendency toward monolithic scripts and lack of function-based thinking in introductory materials felt so unlike normal R programming. If you already are an R user who likes to think and write functions and understand Shiny basics (i.e. reactivity), then modules for certain types of tasks (discussed at the end of this post) are an excellent way to up your game.

Outside of work, Emily can be found sharing more code and ideas about analytics on her website, Twitter ( and GitHub ( modules are often taught as an advanced topic, but they can also be a great way for novice Shiny developers to start building more complex applications. Emily is a Senior Analytics Manager at Capital One where she leads a team building internal analytical tools including R packages, datamarts, and Shiny apps. This post by Emily Riederer is the winning entry in our recent Call for Documentation contest.

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