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Various aspects of data visualization, including graphical excellence, representing data in 1-d, 2-d, and 3-d, and visualizing data in 4+ dimensions. It also covers the importance of visualization in data exploration and presentation, and discusses common pitfalls to avoid. Examples include visualizations of historical data and scientific data, as well as interactive tools like parallel coordinates and chernoff faces.
Typology: Slides
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Marley, 1885
© www.odt.org , from http://www.odt.org/Pictures/minard.jpg 5 , used by permission Docsity.com
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Seoul, South Korea
North Korea Notice how dark it is
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Bad Visualization:
Spreadsheet
Year Sales 1999 2, 2000 2, 2001 2, 2002 2, 2003 2,
Sales
2095
2100
2105
2110
2115
2120
2125
2130
1999 2000 2001 2002 2003
Sales
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Bad Visualization:
Spreadsheet with misleading Y –axis
Year Sales 1999 2, 2000 2, 2001 2, 2002 2, 2003 2,
Sales
2095
2100
2105
2110
2115
2120
2125
2130
1999 2000 2001 2002 2003
Sales
Y-Axis scale gives WRONG impression of big change
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8
528
833
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( 27. 5 18. 0 )
( 5. 3 0. 6 )
= = −
−
=
Tufte requirement: 0.95<Lie Factor<1.
(E.R. Tufte, “The Visual Display of Quantitative Information”, 2nd edition)
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the greatest number of ideas
in the shortest time with the least ink in the smallest space.
(E.R. Tufte, “The Visual Display of Quantitative Information”, 2nd edition)
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5
3
1
0 20
Mean
low Middle 50% high
Tukey box plot
Histogram
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price
mileage
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Lie Factor=14.
(E.R. Tufte, “The Visual Display of Quantitative Information”, 2nd edition)
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3-D image
(requires 3-D blue and red glasses)
Taken by Mars Rover Spirit, Jan 2004