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Effective Data Visualization

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We spend much of our time collecting and analyzing data. That data is only useful if it can be displayed in a meaningful, understandable way.


Yale professor Edward Tufte presented many ideas on how to effectively present data to an audience or end user.

In this session, I will explain some of Tufte's most important guidelines about data visualization and how you can apply those guidelines to your own data. You will learn what to include, what to remove, and what to avoid in your charts, graphs, maps and other images that represent data.

Published in: Data & Analytics
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Effective Data Visualization

  1. 1. David Giard Microsoft Technical Evangelist blog: DavidGiard.com tv: TechnologyAndFriends.com twitter: @DavidGiard Data Visualization The Ideas of Edward Tufte
  2. 2. @DavidGiard I II III IV x y x y x y x y 10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58 8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76 13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71 9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84 11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47 14.0 9.96 14.0 8.10 14.0 8.84 8.0 7.04 6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25 4.0 4.26 4.0 3.10 4.0 5.39 19.0 12.50 12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.59 7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91 5.0 5.68 5.0 4.74 5.0 5.72 8.0 6.89
  3. 3. @DavidGiard 0 5 10 0 10 20 I 0 5 10 0 10 20 II 0 5 10 0 10 20 III 0 5 10 0 10 20 IV
  4. 4. @DavidGiard Dr. Edward Tufte
  5. 5. @DavidGiard Graphical Excellence
  6. 6. @DavidGiard
  7. 7. @DavidGiard
  8. 8. @DavidGiard
  9. 9. @DavidGiard
  10. 10. @DavidGiard 500,000 100,000 10,000
  11. 11. @DavidGiard Graphical Integrity
  12. 12. @DavidGiard Blatant Lies Source: Fox News, Dec 2011 Reprinted by Washington Post
  13. 13. @DavidGiard $(11,014)$0 $(11,014)
  14. 14. @DavidGiard Lie
  15. 15. @DavidGiard Lie Factor ๐‘†๐‘–๐‘ง๐‘’ ๐‘‚๐‘“ ๐ธ๐‘“๐‘“๐‘’๐‘๐‘ก ๐‘†โ„Ž๐‘œ๐‘ค๐‘› ๐ผ๐‘› ๐บ๐‘Ÿ๐‘Ž๐‘โ„Ž๐‘–๐‘ ๐‘†๐‘–๐‘ง๐‘’ ๐‘‚๐‘“ ๐ธ๐‘“๐‘“๐‘’๐‘๐‘ก ๐ผ๐‘› ๐ท๐‘Ž๐‘ก๐‘Ž
  16. 16. @DavidGiard Lie Data Increase = 53% Graphical Increase = 783% Lie Factor=14.8
  17. 17. @DavidGiard Truth 0 5 10 15 20 25 30 1978 1979 1980 1981 1982 1983 1984 1985 Required Fuel Economy Standards: New cars built from 1978 to 1985
  18. 18. @DavidGiard Data Change = 125% Graphical Change = 406% Lie Factor=3.8
  19. 19. @DavidGiard Data Change = 554% Graphical Change = 27,000% Lie Factor=48.8
  20. 20. @DavidGiard
  21. 21. @DavidGiard
  22. 22. @DavidGiard Context
  23. 23. @DavidGiard 275 300 325 1955 1956 Connecticut Traffic Deaths, Before (1955) and After(1956) Stricter Enforcement by the Police Against Cars Exceeding Speed Limit Before stricter enforcement After stricter enforcement
  24. 24. @DavidGiard
  25. 25. @DavidGiard 225 250 275 300 325 1951 1952 1953 1954 1955 1956 1957 1958 1959 Connecticut Traffic Deaths 1951-1959
  26. 26. @DavidGiard 6 8 10 12 14 16 1951 1952 1953 1954 1955 1956 1957 1958 1959 Traffic Deaths per 100,000 Persons in Connecticut, Massachusetts, Rhode Island, and New York 1951-1959 NY MA CT RI
  27. 27. @DavidGiard Principles of Graphical Integrity โ€ข Data Representations proportional to Data โ€ข #Dimensions in graph = #Dimensions in data โ€ข Real dollars, instead of deflated dollars โ€ข Provide context
  28. 28. @DavidGiard Data-Ink
  29. 29. @DavidGiard Data-Ink Ratio = ๐ท๐‘Ž๐‘ก๐‘Ž ๐ผ๐‘›๐‘˜ ๐‘‡๐‘œ๐‘ก๐‘Ž๐‘™ ๐ผ๐‘›๐‘˜
  30. 30. @DavidGiard Redundant Data
  31. 31. @DavidGiard 35.9
  32. 32. @DavidGiard 35.9
  33. 33. @DavidGiard Metadata
  34. 34. @DavidGiard 0 20 40 60 80 100 120 140 160 0 1 2 3 4 5 6
  35. 35. @DavidGiard 0 20 40 60 80 100 120 140 160 0 1 2 3 4 5 6
  36. 36. @DavidGiard 0 20 40 60 80 100 120 140 160 0 1 2 3 4 5 6
  37. 37. @DavidGiard 0 40 80 120 160 0 2 4 6
  38. 38. @DavidGiard 0 40 80 120 160 0 2 4 6
  39. 39. @DavidGiard 0 40 80 120 160 0 2 4 6
  40. 40. @DavidGiard
  41. 41. @DavidGiard
  42. 42. @DavidGiard
  43. 43. @DavidGiard
  44. 44. @DavidGiard
  45. 45. @DavidGiard Principles โ€ข Above all else, show the data โ€ข Maximize the Data-Ink ratio, within reason โ€ข Erase non-data-ink โ€ข Erase redundant data-ink โ€ข Revise and edit
  46. 46. @DavidGiard Vibrations
  47. 47. @DavidGiard Vibrations
  48. 48. @DavidGiard
  49. 49. @DavidGiard
  50. 50. @DavidGiard 0 5 10 15 20 25 30 35 40 45 50 55 60 PERCENTCRITICALARTICLES ISSUE AREAS INFLATION UNEMPLOYMENT SHORTAGES RACE CRIME GOVT. POWER CONFIDENCE WATERGATE COMPETENCE Linear (RACE)
  51. 51. @DavidGiard 0 5 10 15 20 25 30 35 40 45 50 55 60 PERCENTCRITICALARTICLES ISSUE AREAS
  52. 52. @DavidGiard INFLATION UNEMPLOYMENT SHORTAGES RACE CRIME GOVT.POWER CONFIDENCE WATERGATE COMPETENCE 0 5 10 15 20 25 30 35 40 45 50 55 60 PERCENTCRITICALARTICLES ISSUE AREAS
  53. 53. @DavidGiard CONFIDENCE WATERGATE GOVT.POWER CRIME COMPETENCE INFLATION RACE SHORTAGES UNEMPLOYMENT 0 5 10 15 20 25 30 35 40 45 50 55 60 PERCENTCRITICALARTICLES ISSUE AREAS
  54. 54. @DavidGiard Chart Junk and Ducks
  55. 55. @DavidGiard
  56. 56. @DavidGiard
  57. 57. @DavidGiard
  58. 58. @DavidGiard Worst. Graph. Ever.
  59. 59. @DavidGiard Year % Students < 25 1972 28.0 1973 29.2 1974 32.8 1975 33.6 1976 33.0
  60. 60. @DavidGiard Multifunctioning Graphical Elements
  61. 61. @DavidGiard
  62. 62. @DavidGiard
  63. 63. @DavidGiard
  64. 64. @DavidGiard Data Density
  65. 65. @DavidGiard Data Density ๐‘๐‘ข๐‘š๐‘๐‘’๐‘Ÿ ๐‘œ๐‘“ ๐‘’๐‘›๐‘ก๐‘Ÿ๐‘–๐‘’๐‘  ๐‘–๐‘› ๐‘‘๐‘Ž๐‘ก๐‘Ž ๐‘š๐‘Ž๐‘ก๐‘Ÿ๐‘–๐‘ฅ ๐ด๐‘Ÿ๐‘’๐‘Ž ๐‘œ๐‘“ ๐ท๐‘Ž๐‘ก๐‘Ž ๐บ๐‘Ÿ๐‘Ž๐‘โ„Ž๐‘–๐‘
  66. 66. @DavidGiard Low Data Density
  67. 67. @DavidGiard Low Data Density Number of entries = 4 Graph Area = 26.5 square inches Data Density = 4 ๐‘‘๐‘Ž๐‘ก๐‘Ž ๐‘’๐‘›๐‘ก๐‘Ÿ๐‘–๐‘’๐‘  26.5 ๐‘ ๐‘ž. ๐‘–๐‘›. =.15 data entries per sq. in.
  68. 68. @DavidGiard High Data Density 181 Numbers per square inch
  69. 69. @DavidGiard High Data Density 1,000 Numbers per square inch
  70. 70. @DavidGiard Small Multiples
  71. 71. @DavidGiard Small Multiples
  72. 72. @DavidGiard Small Multiples
  73. 73. @DavidGiard Small Multiples
  74. 74. @DavidGiard Tufteโ€™s Graphs โ€ข Sparkline โ€ข Slope Graph
  75. 75. @DavidGiard Sparklines
  76. 76. @DavidGiard Sparklines
  77. 77. @DavidGiard Slope Graph
  78. 78. @DavidGiard Slope Graph Source: The Atlantic, June 30, 2012
  79. 79. @DavidGiard Takeaways โ€ข Maintain Graphical Integrity โ€ข Maximize Data-Ink Ratio, within reason โ€ข Avoid Chartjunk and Ducks โ€ข Use Multifunctioning Graphical Elements, if possible โ€ข Keep Labels with data โ€ข Maximize Data Density
  80. 80. @DavidGiard
  81. 81. @DavidGiard 00 -5 -9 -21 -11 -20 -24 -30 -26 Temperature ( C ) 10/10 10/18 10/24 11/9 11/14 11/20 11/28 12/1 12/6 12/7 100,000 96,000 55,000 37,000 24,000 50,000 25,000 20,00012,00010,000 # Troops 10/10 10/18 10/24 11/9 11/14 11/20 11/28 12/1 12/6 12/7 040 90 145 180 250 275300 320 365 Distance Traveled (km) 10/10 10/18 10/24 11/9 11/14 11/20 11/28 12/1 12/6 12/7
  82. 82. @DavidGiard 0 20,000 40,000 60,000 80,000 100,000 120,000 10/10 10/12 10/14 10/16 10/18 10/20 10/22 10/24 10/26 10/28 10/30 11/1 11/3 11/5 11/7 11/9 11/11 11/13 11/15 11/17 11/19 11/21 11/23 11/25 11/27 11/29 12/1 12/3 12/5 12/7 #Troops Date Troops Troops
  83. 83. @DavidGiard 0 20,000 40,000 60,000 80,000 100,000 120,000 10/10 10/12 10/14 10/16 10/18 10/20 10/22 10/24 10/26 10/28 10/30 11/1 11/3 11/5 11/7 11/9 11/11 11/13 11/15 11/17 11/19 11/21 11/23 11/25 11/27 11/29 12/1 12/3 12/5 12/7 #Troops Date Troops Troops
  84. 84. @DavidGiard 0 20,000 40,000 60,000 80,000 100,000 120,000 10/10 10/12 10/14 10/16 10/18 10/20 10/22 10/24 10/26 10/28 10/30 11/1 11/3 11/5 11/7 11/9 11/11 11/13 11/15 11/17 11/19 11/21 11/23 11/25 11/27 11/29 12/1 12/3 12/5 12/7 #Troops Date Troops
  85. 85. @DavidGiard 0 20,000 40,000 60,000 80,000 100,000 120,000 10/10 10/12 10/14 10/16 10/18 10/20 10/22 10/24 10/26 10/28 10/30 11/1 11/3 11/5 11/7 11/9 11/11 11/13 11/15 11/17 11/19 11/21 11/23 11/25 11/27 11/29 12/1 12/3 12/5 12/7 #Troops Date
  86. 86. @DavidGiard 0 20,000 40,000 60,000 80,000 100,000 120,000 10/10 10/17 10/24 10/31 11/7 11/14 11/21 11/28 12/5 #Troops Date
  87. 87. @DavidGiard -35 -30 -25 -20 -15 -10 -5 0 0 20,000 40,000 60,000 80,000 100,000 120,000 10/10 10/17 10/24 10/31 11/7 11/14 11/21 11/28 12/5 Temperature(Celsius) #Troops Date Troops Temperature
  88. 88. David Giard Microsoft Technical Evangelist blog: DavidGiard.com tv: TechnologyAndFriends.com twitter: @DavidGiard
  89. 89. @DavidGiard Video of Presentation tinyurl.com/DataVizTechEd tinyurl.com/DataVizITCamp
  90. 90. @DavidGiard
  91. 91. @DavidGiard

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