posit::conf 2023

by Colin Rundel

:spiral_calendar: September 17, 2023

:alarm_clock: 09:00 - 17:00

:hotel: Grand Hall L

:writing_hand: pos.it/conf

:link: pos.it/shiny-conf23

:octocat: posit-conf-2023/shiny-r-intro

Overview

Shiny is an R package that makes it easy to build interactive web apps straight from R. This workshop will start at the beginning: designing and creating user interfaces, learning and mastering the reactive model that connects your R code to the interface, and deploying apps publicly and privately. We will wrap up with some intermediate-level tools: debugging and modularizing your apps and implementing dynamic user interfaces. In the end, you’ll be a confident Shiny user, able to design interactive apps to achieve your purpose and produce a polished and professional implementation.

This workshop is for you if

  • are comfortable with the basics of R, such as writing functions, indexing vectors and lists, debugging simple errors, and working with data structures like data frames,

  • are interested in creating interactive web applications, and

  • have no or minimal experience with Shiny for R.

If you have a bit of experience, you’ll see things in a new way. If you don’t, we’ll get you started on the right footing.

Prework

There is nothing you will need to do before attending this workshop. We will be making use of Posit Cloud for all activities and exercises so you will just need to bring a laptop that is able to access the conference WiFi.

Schedule

Time Activity Materials
09:00 - 09:30 Welcome :notebook:
09:30 - 10:30 Intro to Shiny :notebook:
10:30 - 11:00 Coffee break  
11:00 - 12:30 Basic Reactivity :notebook:
12:30 - 13:30 Lunch break  
13:30 - 15:00 Observers & reactives :notebook:
15:00 - 15:30 Coffee break  
15:30 - 16:30 Theming & Publishing :notebook:
16:30 - 17:00 Wrap-up :notebook:

Instructor

Colin Rundel is Associate Professor of the Practice at Duke University in the department of Statistical Science where he has been teaching since 2012. His work focuses on teaching statistical computing to both undergraduate and graduate students in both R and Python. He has been teaching and using Shiny since 2015.

This work is licensed under a Creative Commons Attribution 4.0 International License.