I’m doing some form of data visualization learning for 180 days because I need to #JFDI. See post explaining how and why I’m doing this.
- Note to self. Time to start winding down and giving self set time split up in a few mornings and evenings a week now that I’m settled into my new life in NY and can’t run off adrenaline anymore.
- Try to split into 50/50 learning of design and code/technical work.
- Since I code or use a tool like Tableau everyday at work, I’m learning toward learning about design and visual theory if I have to get one thing done a day. This is everything from decomposing (see previous posts) data visualizations that live in the world to reading various literature, everything from style guides to dense theory about data visualization.
Reading and Learning Data Visualization Theoretically/Critically:
“You Section” p. 13-25
- Overlapping matrixes are an interesting leverage of grouping and scales but can be confusing without contrasting annotations and color choices.
- Choice of shadow and annotations to show a fluid process gives an otherwise static image movement
- Use of a layered bar graph can be more textured/useful/convey more data with a zoom-in showing a matrix of dots to break down the lines that are less visible