Readings

Suggested readings & references will be shared here.

Ed announcements will be made when this document updates.

Week 5 & 6

HTML & CSS Resources

D3 Resources

D3 in Depth - Free Book on D3 with interactive examples.
Thinking with Joins - Classic post introducing the key concept of D3. Uses old syntax.
D3 Graph Gallery - Examples of how to do almost anything in D3.

Web Design

Design for Real Life (free book)
Example Style Guide

Week 4

Uncertainty

Visualizing Uncertainty, Fundamentals of Data Visualization: https://clauswilke.com/dataviz/visualizing-uncertainty.html
Visualizing Uncertainity as a Moral Imperative: https://www.mjskay.com/presentations/aalto2020-uncertainty.pdf

Narrative

NPR Training on Ledes: https://training.npr.org/2021/06/03/nut-graf-and-lead-duos-that-point-readers-in-the-right-direction/
Ideas of Other Article Formats beyond Lede/Nut: https://en.wikipedia.org/wiki/Article_structure.
Pulitzer-winning long form piece that CAPP Alum Aïcha Camara contributed to: https://chicagomissingpersons.com/who-goes-missing/

Week 2

Useful Context

For more on the science of color from the eye to the screen: https://jamie-wong.com/post/color/

In terms of relevance for this course, if you are going to buy one Tufte book I'd make it The Visual Display of Quantitative Information, with Envisioning Information a runner-up. The others are great as well, and you can often find bundles of all 4-5 together.

Buy direct from Graphics Press: https://www.edwardtufte.com/books/

Tools (from slides)

Vega Schemes: https://vega.github.io/vega/docs/schemes/
Contrast/theme exploration: https://schubert-da.github.io/dataviz-palette-tool/
Theme exploration for cartography: https://colorbrewer2.org/
Color-theory based theme creator: https://meodai.github.io/poline/
Theme creator w/ theme sharing: https://coolors.co
HSL/RGB picker: https://hslpicker.com/
Contast checker: https://webaim.org/resources/contrastchecker/
Colorblindness MacOS/iOS app: https://michelf.ca/projects/sim-daltonism/ or search "colorblindness" in your browser of choice.

Week 1

Useful Context

If you have never encountered "tidy" data or "grammar of graphics" these two papers by Hadley Wikham provide context that might be useful:

Tidy Data - https://vita.had.co.nz/papers/tidy-data.html
A layered grammar of Graphics - https://vita.had.co.nz/papers/layered-grammar.html

If you'd like a longer lecture on Altair after what we cover in class and starting with the user guide below,

Jake VanderPlas' PyCon 2018 Tutorial is a great place to start (Just note that in a few places the syntax has changed slightly, but key concepts are the same).

https://altair-viz.github.io/altair-tutorial/README.html

Essential Reading

The most important reading for this week will be to begin working your way through the Altair User Guide.

https://altair-viz.github.io/user_guide/data.html

The sections you should read (in the left sidebar):

Specifying Data (you can stop when you hit 'Generated Data')
Encodings
Encodings -> Channels (skim Channel Options)
Marks (skim a few of the mark guides, including Bar & Point)
Data Transformations (skim a few, including Regression)
Layered and Multi-View Charts
Customizing Visualizations

Using Altair's Documentation

Once you've read the above you have seen the core ideas of Altair.

The remaining sections are useful as reference, and as you use Altair you will find your way to them as you ask yourself questions like "how do I work with geospatial data" or "how can I combine these axes"?

The other common thing you will use the documentation for is "what arguments can I pass to this?"

For that, use the API Reference and find the class you're working with.

Example:

Let's say we want to adjust the color scheme, start with https://altair-viz.github.io/user_guide/generated/channels/altair.Color.html
Note that it can take a scale, and click to https://altair-viz.github.io/user_guide/generated/core/altair.Scale.html#altair.Scale