Data scientists who work with R look to Shiny as the web framework of choice for moving analytical power into the hands of their bosses, clients, and the public at large. The reason? Shiny apps let the non-coders of the world control the visualization of complex data sets so they can explore, analyze and model on their own. Taught by RStudio master instructor Garrett Grolemund, this video details how Shiny combines the computational power of R and …
Introduction to Shiny
Video description
Data scientists who work with R look to Shiny as the web framework of choice for moving analytical power into the hands of their bosses, clients, and the public at large. The reason? Shiny apps let the non-coders of the world control the visualization of complex data sets so they can explore, analyze and model on their own. Taught by RStudio master instructor Garrett Grolemund, this video details how Shiny combines the computational power of R and the interactivity of the web to produce highly interactive reports and visualizations. Part one offers a detailed description of Shiny and how to use it build an app. Part two covers reactive programming and why it differs from functional programming, the paradigm that guides most of R. Part three outlines the Shiny UI and the toolsets it offers to customize the appearance of a Shiny app. This video is optimized for the intermediate level R coder.
Learn to build, test, and deploy Shiny web apps from start to finish
Explore the RStudio IDE, the Shiny file structure, and the three must-have lines of Shiny code
Discover how Shiny apps instantly and automatically respond to user inputs
Master the fundamentals of reactive programming, the coding paradigm that makes Shiny possible
Understand render*() functions, reactive expressions, observers, plots, and more
Explore the tools R coders with or without HTML skills use to modify the look of Shiny apps
Learn to host your Shiny app over any network
Garrett Grolemund is all about the R. He is a Data Scientist with RStudio, one of the largest contributors of content and software related to the open source R language. He is Editor-in-Chief of the Shiny development center at shiny.rstudio.com. He wrote the popular lubridate R package; the R focused O'Reilly Media titles Hands-On Programming with R, R for Data Science (co-author), and Expert Data Wrangling with R; and has three Rs in his name.
Tell the Server How to Assemble Outputs From Inputs
Create Reactivity
Your First App Recap
File Structure
Share Your App
Reactive Programming
Vocabulary
Reactive Programming
Display Output with render*() Functions
Build Reusable Objects with reactive()
Prevent Reactions with isolate()
Delay Reactions with eventReactive()
Trigger Side Effects with observeEvent()
Maintain State with reactiveValues()
Observers versus Reactive Expressions, Part 1: Side Effects
Observers versus Reactive Expressions, Part 2: The Key to Shiny
Schedule Reactions with invalidateLater()
Track Data with reactivePoll() and reactiveFileReader()
Interactive Visualizations
Avoid Repetition
Understanding UI
Shiny UI
htmlTemplate()
R Functions to Write HTML
Panels
Layers
Formatting
Raw Input
Where now?
Resources
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