Enhancing visualizations (typography & annotations)

Week 7

Wednesday February 18th, 2026

The words, 'I will find you' in two different typefaces. It's easy to perceive on as intimidating and the other as endearing.

Image soure: Typography for a better user experience

Pre-class Prep

A. Install required packages

install.packages("monochromeR") # a package for creating monochrome color palettes and easily converting rgba values to hex codes (and also some other useful functions)
install.packages("showtext") # for using fonts more easily in R graphs
install.packages("glue") # for string interpolation (aka helps us insert variables directly into text strings)
install.packages("ggtext") # improved text rendering support for ggplot2
install.packages("ggrepel") # ggplot2 extension to repel overlapping labels

B. Download Font Awesome fonts

We’ll learn how to use Font Awesome icons in our ggplots. To do so, you’ll need to download the Font Awesome font files and save them to your class repo. Do so by following these steps:

  1. Download Font Awesome fonts: Go to https://fontawesome.com/download and download the latest release available. Choose the Free For Desktop option.
  2. Unzip the downloaded file: You should see a folder inside called otfs/ – this contains three .otf files (aka OpenType font format files)
  3. Copy the three .otf files to your class repo: I recommend creating a fonts/ folder inside your root directory, and dropping all three of them in there (e.g. EDS-240-data-viz-examples/fonts/*.otf)

C. Download .qmd templates & review data wrangling code

  1. Download all necessary templates (links in the table below) and save them to a EDS-240-data-viz-examples/week7/ folder.

  2. Review setup / wrangling / base plot code and make note of any questions you might have. Due to time constraints, we won’t be live-coding our way through all code in class. However, we’ll reserve some time to answer any questions before we jump into data viz . Specifically:

    • Template 7 begins where we left off in creating our dumbbell plot (in the amounts / rankings lecture). Review the code under the ## Setup, ## Wrangle Data and ## Create plot sections to re-familiarize yourself. We’ll use this single template for both lectures and lab this week.

Lecture Materials

Lecture slides Code-along template Code-along key
Lecture 7.1: typography 7.1 & 7.2 + lab template 7.1 & 7.2 + lab key
Lecture 7.2: annotations we’ll use the same template, above we’ll use the same key, above

Pre-lab Prep

TODO
  • develop critique form that can be submitted to instructors & to peer

From here on out, we’ll be using lab sections to share drafts of final project data visualizations and receive feedback from peers. Please complete the following before coming to section:

A. Prepare your data viz slide

FPM #3, asks you to draft all three required visualizations that will become a part of your final project infographic. Find your assigned slide from the Google Slide deck (see table, under the Lab Materials section, below) and add the following:

  1. one of your three visualizations
  2. the question that you’re visualization helps to answer

The visualization you bring should meet the FPM #3 requirements (see part V under the Description section) – this should be a well-constructed, carefully thought-through and polished plot. You should be prepared to discuss your design choices and receive constructive feedback from your peers.

B. Read up on how to give / receive feedback

Giving, receiving and implementing feedback is an important part of any creative process (including building data visualizations!). Review the tips in the drop down, below:

The following tips were largely adapted from this LinkedIn article.

For giving feedback:

  • focus on the strengths / weakness of the visualization itself, not the person who created it
  • balance positive and negative feedback, and start with the positives!
  • stay objective when suggesting improvements (e.g. “This part might benefit from some clarity…”)
  • be specific (e.g. instead of saying, “This chart is confusing,” point out exactly what is unclear or misleading)
  • suggest actionable solutions and / or alternatives, rather than only problems or criticisms

For receiving feedback:

  • receiving feedback can be stressful – this is a very normal feeling!
  • listen carefully without disrupting / defending yourself
  • take notes, ask questions, and thank your feedback giver(s)
  • evaluate your feedback objectively to decide what to keep / reject / modify

For applying feedback:

  • prioritize feedback based on relevance, importance, and feasibility
  • create a plan and a timeline to implement
  • critically evaluate / compare your before and after versions
  • seek new feedback!

Please also read the following articles on critiquing data viz:

Lab Materials

Lab Slides Exercise instructions Exercise solutions
Lab 7 slides: peer feedback Google Slides NA

Assignment Reminders

Assignment Type Assignment Title Date Assigned Date Due
FPM Final Project Milestone #3 Wed 02/11/2026 Sun 02/22/2026, 11:59pm PT