Continue your exploration in code with Skills Lab 4 which includes the very important Tutorial 11. Please try to complete all remaining tutorials under Skills Lab 4 at Labs.
If you are having trouble, you may optionally elect to engage AI assistants. If that is of interest, check out the bonus Lesson 26 on using AI.
No video for this lesson.
Sketching with data.
Apply coding skills with data. Builds on previous lessons in creative coding and visual representation through completion of Skills Lab 4, particularly Tutorial 11 on data resources.
This lecture focuses on practical application of coding skills with data. Building on previous lessons (Lectures 8 and 9) on sketching in code, this lesson adds the crucial element of working with actual data and prepares students for upcoming lessons on formalizing glyphs and empirical evidence regarding encoding devices.
Students learn to work with data in code using Sketchingpy and apply visual encoding principles to data-driven graphics.
Students complete the remaining tutorials in Skills Lab 4, with special emphasis on Tutorial 11.
Mention of the reading assignment introducing William Cleveland's work.
This lesson continues the Primitives section of the course, where students learn about perception and cognitive science principles for visualization using Sketchingpy and Matplotlib.
[1] A. Pottinger and Sketchingpy Contributors, "Sketchingpy," Sketchingpy Project, 2025. Available: https://sketchingpy.org/
[2] A. Pottinger and Sketchingpy Contributors, "Sketchingpy Online Sketchbook," Sketchingpy Project, 2025. Available: https://editor.sketchingpy.org/
[3] D. Miller, "How William Cleveland Turned Data Visualization Into a Science," Priceonomics. Available: https://priceonomics.com/how-william-cleveland-turned-data-visualization/
This lesson is part of Interactive Data Science and Visualization and is released under a CC-BY-NC 4.0 license.