Developing charts (and some data wrangling)

Lecture 07

Dr. Benjamin Soltoff

Cornell University
INFO 3312/5312 - Fall 2026

September 17, 2026

Announcements

Announcements

Source: American Association of University Professors (AAUP)

Learning objectives

  • Review common methods for data wrangling and tidying
  • Redesign a visualization for improved clarity
  • Sketch a visualization
  • Define and implement grammar of graphics for a chart

Data wrangling with {dplyr}

Image credit: @allison_horst

Data tidying with {tidyr}

Stylized text providing an overview of Tidy Data. The top reads "Tidy data is a standard way of mapping the meaning of a dataset to its structure. - Hadley Wickham." On the left reads "In tidy data: each variable forms a column; each observation forms a row; each cell is a single measurement." There is an example table on the lower right with columns "id", "name" and "color" with observations for different cats, illustrating tidy data structure.

Illustration credit: Tidy Data for reproducibility, efficiency, and collaboration

Application exercise

Improve a sad plot

Draft a new chart

Instructions

Sketch a chart that highlights the decline in tenure-track faculty.

  • What type of geom would you use?
  • Scales? Guides?
  • Labels?

Include sufficient level of detail to communicate your design choices for implementation.

08:00

Peer critique

Instructions

Swap with a peer and critique their design choices. Apply at least two of Cairo’s qualities of great visualizations.

  • Truthful
  • Functional
  • Beautiful
  • Insightful
  • Enlightening

Effective critiques

Critiques are not just about tearing down someone else’s work. They are about providing constructive feedback (both positive and negative) that helps the creator improve their work.

08:00

Revise your chart

Instructions

On the back of the page, sketch a revised version of your chart based on the feedback you received.

  • New geom(s)?
  • New scales or guides?
  • Improved labels?

Define the chart’s grammar of graphics

What are the variables and aesthetic mappings? What geoms would you use? What scales and guides would you include?

10:00

Implement your design

Instructions

  • Go to the course GitHub org and find your ae-06 (repo name will be suffixed with your GitHub name).
  • Clone the repo in Positron, run renv::restore() to install the required packages, open the Quarto document in the repo, and implement your your proposed chart.

Tip

  • Tidy the data set
  • Transform or calculate new variables (if necessary)
20:00

Wrap up

Recap

  • Data is often messy and needs to be transformed and reshaped for effective communication
  • {dplyr} contains functions for transforming data
  • {tidyr} contains functions for reshaping data
  • Design choices are crucial to effective storytelling with data
  • There is not inherently one “right” choice, but some choices are more effective than others