Due: 13 April, 11:59 pm

Weight: This assignment is worth 0.5% of your final grade.

Purpose: The purpose of this assignment is to get a quick preview of shiny apps so that you’ll be more familiar with the overall structure of shiny apps prior to class.

Assessment: This assignment is graded using a check system:

  • ✔+ (110%): Reflection shows phenomenal thought and engagement with the course content. I will not assign these often.
  • ✔ (100%): Reflection is thoughtful, well-written, and shows engagement with the course content. This is the expected level of performance.
  • ✔− (50%): Reflection is hastily composed, too short, and/or only cursorily engages with the course content. This grade signals that you need to improve next time. I will hopefully not assign these often.

Notice that this is essentially a pass/fail or completion-based system. I’m not grading your writing ability, I’m not counting the exact number of words you write, and I’m not looking for encyclopedic citations of every single reading to prove that you did indeed read everything. I’m looking for thoughtful engagement, that’s all. Do good work and you’ll get a ✓.

For this week’s reflection, download and edit this template.


First, watch this 2-minute intro video to get a quick sense for what Shiny apps are:


Go to the RStudio Shiny Gallery and explore some of the Shiny apps to get a sense for what is possible with Shiny.


Read through this tutorial and follow along, filling out the code in the server.R and ui.R files to make the app shown in the article. When you’re done, you should be able to open the app.R file and click the “Run app” button. Your app should look the same as the final version of the app here.

Note: It’s best to wait to run the app.R file until you have finished the code in the ui.R or server.R files, otherwise you might get an error or a window that says “No UI defined”.


In your reflection, write about one of the Shiny apps you found most interesting in the RStudio Gallery and any other thoughts you might have about Shiny / interactivity, or something else that’s on your mind or something you’ve recently experienced related to class.

Knit and Submit

  • Knit your document to a html page.
  • Create a zip file of everything in your R Project folder.
  • Go to the “Assignment Submission” page on Blackboard and submit your zip file.

EMSE 4575: Exploratory Data Analysis (Spring 2021)
Wednesdays | 12:45 - 3:15 PM | Dr. John Paul Helveston | jph@gwu.edu |