Day 113 of Data Viz Learning #jfdi

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.

Code Learning:

Udacity Data Visualization and D3.js

2b Dimple.js lecture:

  • Dimple.js is framework that allows us to work at abstraction level charts rather than lower level visual codings such as shape and visual encoding.
  • Built on top D3 and designed for analysts to easily create charts and exposes native D3 objects as well.
  • D3 should be loaded before Dimple.js library in <head>

Back to Basics Front-End Web Dev on D3 (not doing takeaways since I just need to review and run through this – anything I need to memorize I do with pen and paper so it’ll REALLY sink in)

Reading and Learning Data Visualization Theoretically/Critically:

Reading Nathan Yau’s book Visualize This

301-310 Visualizing Spatial Relationships

Three Takeaways:

  • Putting together multiple smaller maps (omg maps small multiples!) can be a great way to see patterns in spatial data p. 303
  • To show differences – focus on changes in one map instead of slices of time.  Eg. show choropleth for metric of change in each country (Example given urbanization from 2005 to 2009 with darkest colors as change) p. 307
  • Map animations, eg walmart spreading like a virus, help make the data immediately more understandable, eg bubbles moving through time p 310
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