Artwork by Allison Horst
Effectively communicating your work in a responsible, accessible and visually-pleasing way is often (if not, always) a central part of data science. This course will focus on the basic principles for effective communication through data visualization and using technical tools and workflows for creating and sharing data visualizations with diverse audiences.
By the end of this course, learners should be able to:
- Identify which types of visualizations are most appropriate for your data and your audience
- Prepare (e.g. clean, explore, wrangle) data so that it’s appropriately formatted for building data visualizations
- Build effective, responsible, accessible, and aesthetically-pleasing visualizations using the R programming language, and specifically
{ggplot2}+ ggplot2 extension packages - Write code from scratch and read and adapt code written by others
- Apply a DEI (Diversity, Equity & Inclusion) lens to the process of designing data visualizations
- Assess, critique, and provide constructive feedback on data visualizations
Visit the course page on the Bren Website.
Assignments are distributed using GitHub Classrooms via the eds240-winter-2024-org. Assignment keys also available in the classroom organization (private).
Found something that doesn't look quite right? Feel free to file an issue and include a concise, clear description, along with a link to the location on the website. Screenshots are always appreciated as well!
This work is licensed under a Creative Commons Attribution 4.0 International License