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Building Effective Data Visualizations
Kate M. WatkinsSenior Economist
Colorado Legislative Council StaffNCSL Fiscal Analyst Forum
October 6, 2016
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Image from EURUSD FX Blog:
http://eurusd-fx.blogspot.com/2011/09/proportion-of-eur-by-country-based-on.html
Missing title
Missing source information
Missing labels
Poor resolution
Unpleasant colors
3D?
4Charles Joseph Minard (1869), reproduced in Tufte’s (2001) The Visual Display of Quantitative Information
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Best Practices for Effective Data Visualization
1) Ask: Who? What? Why?
2) Know the data
3) Tell a (true) story
4) Create an analytical tool
5) Strive for ‘graphical excellence’
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Colorado Online Tax Handbookhttp://leg.colorado.gov/agencies/legislative-council-staff/colorado-online-tax-handbook
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Who is your target audience?
What are the goals of the visualization?
– Explanatory: lead your audience to a conclusion
– Exploratory: let your audience explore
What are you trying to communicate? And why?
1) Ask…
Novice Working Knowledge ExpertIntroduction Briefing In-Depth Analysis
AudienceFormat
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2) Know the data
• Become an expert
• Anticipate questions,
know the answers,
build answers into the visualization
• Pilot test your visualizations
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3) Tell a story with data
Charles Joseph Minard (1869), reproduced in Tufte’s (2001) The Visual Display of Quantitative Information
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3) Tell a (true) story with data
• Don’t lie with graphics
From Darrell Huff’s (1954) How to Lie with Statistics. Illustrations by Irving Geis.
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3) Tell a (true) story with data
• Don’t lie with graphics
• Let the data speak for itself
From Darrell Huff’s (1954) How to Lie with Statistics. Illustrations by Irving Geis.
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4) Create an analytical tool
• Provide enough information for replication
– Cite data sources and note data transformations
and anomalies
• Build in supplemental materials
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4) Create an analytical tool
• Provide enough information for replication
– Cite data sources and note data transformations
and anomalies
• Build in supplemental materials
• Provide the data itself
Novice Working Knowledge ExpertIntroduction Briefing In-Depth Analysis
AudienceFormat
14Charles Joseph Minard (1869), reproduced in Tufte’s (2001) The Visual Display of Quantitative Information
5) Strive for ‘graphical excellence’ (Tufte)
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5) Strive for ‘graphical excellence’ (Tufte)
• Eliminate ‘chart junk’
• Maximize the data-ink ratio
Data-ink ratio = Ink used on data
Total ink used
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5) Strive for ‘graphical excellence’ (Tufte)
• Eliminate ‘chart junk’
• Maximize the data-ink ratio
Sparkline
Data-ink ratio = Ink used on data
Total ink used
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5) Strive for ‘graphical excellence’ (Tufte)
• Eliminate ‘chart junk’
• Get rid of the grid
Image reproduced from Tufte (2001: 113).
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5) Strive for ‘graphical excellence’ (Tufte)
• Eliminate ‘chart junk’
• Get rid of the grid
Colorado State Demography Office, October 2015 projections.
300,000 200,000 100,000 0 100,000 200,000 300,000
0 to 4
5 to 9
10 to 14
15 to 19
20 to 24
25 to 29
30 to 34
35 to 39
40 to 44
45 to 49
50 to 54
55 to 59
60 to 64
65 to 69
70 to 74
75 to 79
80 to 84
85 to 89
90 to 94
95 to 99
100+ Male Female
20162018
Colorado Population by Age and Sex
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5) Strive for ‘graphical excellence’ (Tufte)
Image reproduced from Tufte (2001: 117).
• Eliminate ‘chart junk’
• No ducks allowed
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• The modern duck
5) Strive for ‘graphical excellence’ (Tufte)
Image reproduced from the Professional Business Development website (pbi-now.com).
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5) Strive for ‘graphical excellence’ (Tufte)
• Draw the reader in with color
Charles Joseph Minard (1869), reproduced in Tufte’s (2001) The Visual Display of Quantitative Information
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Best Practices: Color
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2) Be aware of the emotion and culturally-specific
connotations of color
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5) Strive for ‘graphical excellence’ (Tufte)
• Draw the reader in with color
• Be aware of red-green colorblindness
Image from: http://enchroma.com/test/instructions/
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Kate M. Watkins
kate.watkins@state.co.us
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