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A lightning quick An Andrew Heiss, Ph PhD Brigham Young University introduction to data West Coast Nonprofit Data Conference visualization April 27, 2018 Plan for today Why visualize data? Types of visualizations Aesthetics and design


  1. A lightning quick An Andrew Heiss, Ph PhD Brigham Young University introduction to data West Coast Nonprofit Data Conference visualization April 27, 2018

  2. Plan for today Why visualize data? Types of visualizations Aesthetics and design How do I do all this? Take a sad plot and make it better

  3. talks.andrewheiss.com/wcnpd18

  4. Why visualize data?

  5. Theories are only stories until you have some data. Data alone cannot tell stories or prove theories.

  6. Never trust summary statistics alone

  7. Humans are visual creatures @FacesPics

  8. The War of 1812 (the European one) Long distance!

  9. The War of 1812 (the European one) Very cold! 0 01-Oct 01-Nov 01-Dec -5 -10 -15 -20 -25 -30 -35

  10. The War of 1812 (the European one) Very sad! Napoleon’s Grande Armée Died Survived

  11. Characteristics of graphical excellence 1. “... the well-designed presentation of interesting data—a matter of substance, statistics, and design.” 2. Complex ideas communicated with clarity, precision, and efficiency. 3. That which gives the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space. 4. Nearly always multivariate. 5. Requires telling the truth about the data.

  12. What makes Minard’s graph so great?

  13. We forget this!

  14. Types of visualizations

  15. Exploratory visualizations Academic-ish Quick scatterplots, histograms, other charts to help understand your data Explanatory visualizations Publishable Consumable by the general public; Vox, NYT, Washington Post, FiveThirtyEight, etc .

  16. Exploratory Explanatory

  17. Exploratory data analysis Visualize every variable individually

  18. Exploratory data analysis Visualize relationships between each variable

  19. Explanatory data analysis Annotate and tell a story

  20. Explanatory data analysis Annotate and tell a story

  21. Which chart type do I use? datavizcatalogue.com

  22. Dataviz gotchas: multiple y-axes

  23. Dataviz gotchas: multiple y-axes

  24. Dataviz gotchas: multiple y-axes It’s okay if both axes measure the same thing

  25. Dataviz gotchas: truncated y-axes

  26. Truncation is okay sometimes! …when small movements matter

  27. Truncation is okay sometimes! …when zero values are impossible

  28. Truncation is okay sometimes! …but never on bar charts!

  29. Aesthetics and design

  30. Fonts Nice sans serif fonts; move away from Arial Design principles Co Contrast Re Repeti titi tion Al Alignment Pr Proxi ximity

  31. Colors Be aware of colorblind users!

  32. Choose universally accessible palettes

  33. How do I do all this?

  34. Flexibility Fl an and power Ba Barri rrier er to en entry ry (a (amount of coding req required red)

  35. Take a sad plot and make it better

  36. talks.andrewheiss.com/wcnpd18

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