Bring Data to Life: Create Interactive Apps with Shiny in R

Discover how to transform your data into interactive web applications with Shiny, a powerful R package designed for creating dynamic user interfaces. In this hands-on workshop, you'll learn how to build and customize Shiny apps, create reactive data visualizations using packages like ggplot2 and plotly, and deploy your apps online. Whether you're new to programming or an R user looking to expand your skills, this workshop will guide you step-by-step through the process of turning static data into engaging, interactive experiences. The workshop will be led by CCIDM’s Marketing Analytics specialist, Jarrod Griffin, who is also a student in the Master of Science in Digital Marketing.  

Learning Outcomes 

Understand Shiny App Structure: Participants will learn the fundamental architecture of Shiny apps and how to structure code using ui.R/server.R or app.R. 
Implement Reactive Programming: Attendees will gain the skills to create dynamic, interactive Shiny applications using reactive values and expressions. 
Build Interactive Data Visualizations: Participants will learn to incorporate and customize interactive plots with packages like ggplot2 and plotly for responsive data visualization. 
Deploy Shiny Apps on Various Platforms: Attendees will be able to deploy Shiny apps to platforms such as shinyapps.io and shinylive, making the apps accessible online. 
Secure Shiny Applications: Participants will learn about securing Shiny apps, including implementing authentication and understanding best practices for protecting sensitive data.

Workshop Preparation:

Accessing R and RStudio

To get the most out of this workshop, please ensure you have access to both R and RStudio. You can do this by either downloading and installing them to your computer or by setting up a free Posit Cloud account.

Options for Accessing R & RStudio:

Posit Cloud (online option) - Get started here
Install R & RStudio on Windows - Watch this tutorial
Install R & RStudio on macOS - Watch this tutorial

Introduction to R & RStudio (Optional)

While not required, we encourage you to watch the following workshop beforehand if you can set aside an hour.

Introduction to R and RStudio

During the Workshop:


5:50: https://posit.cloud/ 

8:42:
packages <- c("shiny",  
              "tidyverse",  
              "shinydashboard",  
              "plotly",  
              "DT") 

missing_packages <- packages[!packages %in% installed.packages()[, "Package"]] 
if (length(missing_packages) > 0) { 
  install.packages(missing_packages) 
}

14:45:
library(shiny)

ui <-  

server <- function(input, output) { 

} 

# Run the application  
shinyApp(ui = ui, server = server) 

23:15:
library(shiny)
library(tidyverse)
library(shinydashboard)
library(plotly)
library(DT)

post_data.df <- read_csv("https://raw.githubusercontent.com/jsgriffin96/shiny_r_workshop/refs/heads/main/data/Post%20Data.csv") %>% 
  mutate(across(c("Date", "Revenue"), ~ str_extract(.x, "\\d+"))) %>% 
  mutate(across(c("Date", "Revenue"), as.numeric)) %>% 
  mutate(Post_Type = factor(Post_Type, levels = c("Featured Product", "Announcement", "Event Showcase", "Employee of the Week"))) %>% 
  arrange(Date)

30:25:
selectInput("post_type", "Post Type:", choices = unique(post_data.df$Post_Type), multiple = TRUE),

35:07:
box(title = "Total Conversions per Day",  
    status = "primary",  
    solidHeader = TRUE,  
    collapsible = TRUE,  
    width = 12, 
    plotlyOutput("conversionsTimeSeries"))

41:49:
filtered_df <- reactive({ 
  req(input$post_type) 

  post_data.df %>% 
    filter(Post_Type %in% input$post_type) 
})

Complete Code and Presentation:

https://github.com/jsgriffin96/shiny_r_workshop

Bring Data to Life: Create Interactive Apps with Shiny in R