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Three most common mistakes in data visualization

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Accompanying slides to my data visualization workshop.

https://gorelik.net/2018/05/01/i-will-host-a-data-visualization-workshop-at-israels-biggest-data-science-event/

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Three most common mistakes in data visualization

  1. 1. Three most common mistakes in data visualization 
 and how to avoid them Boris Gorelik, Ph.D.
 boris@gorelik.net
 http://gorelik.net https://github.com/bgbg/datascience_dataviz_workshop
  2. 2. Why?
  3. 3. Competition
  4. 4. Boris Gorelik, Ph.D.
 boris@gorelik.net
 http://gorelik.net
 http://data.blog WooCommerce, Jetpack, … Past Present
  5. 5. https://automattic.com/work-with-us/
  6. 6. Three most common data visualization mistakes A B C
  7. 7. Three most common data visualization mistakes A
  8. 8. Course Title Data-ink ratio Information layers
  9. 9. Course Title Data-ink ratio Information layers Gestalt principles
  10. 10. Science? Art?
 Matter of taste?
  11. 11. A Three most common data visualization mistakes
  12. 12. Attitude Three most common data visualization mistakes
  13. 13. Data visualization Explanatory Exploratory
  14. 14. Competition
  15. 15. 0 10,000 1 2 3 4 5 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000 Salaries (U.S. $) Female vs. Male Salary Distributions Pay Grades 110,000 0 10,000 1 2 3 4 5 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000 Salaries (U.S. $) Male vs. Female Salary Distributions Pay Grades 110,000 From "Show me the numbers” by Stephen C. Few
  16. 16. 987349790275647902894728624092406037070570279072 803208029007302501270237008374082078720272007083 247802602703793775709707377970667462097094702780 927979709723097230979592750927279798734972608027 From "Show me the numbers” by Stephen C. Few
  17. 17. From "Show me the numbers” by Stephen C. Few
  18. 18. From "Show me the numbers” by Stephen C. Few “Pre-attentive attributes”
  19. 19. From "Show me the numbers” by Stephen C. Few
  20. 20. Three most common data visualization mistakes A B C Attitude
 Evidence-based. Explanatory vs. Exploratory
  21. 21. Three most common data visualization mistakes B
  22. 22. Stimulus Sensory Organ EyeEyeEye Brain Perceptual Organ Iconic Memory Working Memory Long-term Memory Sensation (Physical Process) Perception (Cognitive Process) From "Show me the numbers” by Stephen C. Few
  23. 23. Stimulus Sensory Organ EyeEyeEye Brain Perceptual Organ Iconic Memory Working Memory Long-term Memory Sensation (Physical Process) Perception (Cognitive Process) From "Show me the numbers” by Stephen C. Few
  24. 24. Stimulus Sensory Organ EyeEyeEye Brain Perceptual Organ Iconic Memory Working Memory Long-term Memory Sensation (Physical Process) Perception (Cognitive Process) From "Show me the numbers” by Stephen C. Few
  25. 25. Stimulus Sensory Organ EyeEyeEye Brain Perceptual Organ Iconic Memory Working Memory Long-term Memory Sensation (Physical Process) Perception (Cognitive Process) From "Show me the numbers” by Stephen C. Few
  26. 26. Stimulus Sensory Organ EyeEyeEye Brain Perceptual Organ Iconic Memory Working Memory Long-term Memory Sensation (Physical Process) Perception (Cognitive Process) From "Show me the numbers” by Stephen C. Few “Pre-attentive attributes”
  27. 27. From "Show me the numbers” by Stephen C. Few color enclosure
  28. 28. Edward Tufte
 http://edwardtufte.com
 Data-ink ratio
 (signal-to-noise ratio)
  29. 29. Above all, show data
  30. 30. No data — no ink
  31. 31. Three most common data visualization mistakes B
  32. 32. Three most common data visualization mistakes Bullshit Cut the
  33. 33. Jean-luc Doumont
 http://www.principiae.be
 Information layers
 (Useful redundancy)
  34. 34. Data-ink ratio Information layers
  35. 35. Data-ink ratio Information layers No BS
  36. 36. Three most common data visualization mistakes B
  37. 37. Three most common data visualization mistakes Build
  38. 38. https://gorelik.net/2017/12/10/the-y-axis-doesnt-have-to-be-on-the-left/
  39. 39. https://gorelik.net/2017/12/10/the-y-axis-doesnt-have-to-be-on-the-left/
  40. 40. Three most common data visualization mistakes A B C Attitude
 Evidence-based.Explanatory vs. Exploratory BS & Build
 Remove, remove, remove. Use appropriate graph types.
  41. 41. Three most common data visualization mistakes C
  42. 42. I need a volunteer
  43. 43. *** ******* ****** **** ***** ***** ***** ****** ****** ****** ****** ****** ****** ********* ****** ****** *****
  44. 44. RED GREEN BLUE RED BLUE GREEN BLUE YELLOW RED RED BLUE GREEN GREEN YELLOW RED GREEN BLUE
  45. 45. RED GREEN BLUE RED BLUE GREEN BLUE YELLOW RED RED BLUE GREEN GREEN YELLOW RED GREEN BLUE
  46. 46. TEXT
  47. 47. Course Title “So what?” vs. “What?”
  48. 48. Three most common data visualization mistakes C
  49. 49. Three most common data visualization mistakes Conclusion
  50. 50. Three most common data visualization mistakes C Conclusions matter
 ”So what?” is more important than “what?”
  51. 51. Three most common data visualization mistakes A B C
  52. 52. Three most common data visualization mistakes A B C Attitude
 Evidence-based
 Explanatory vs. Exploratory
  53. 53. Three most common data visualization mistakes A B C BS & Build
 Remove, remove, remove.
 Use appropriate graph types.
  54. 54. Three most common data visualization mistakes A B C Conclusions matter
 ”So what?” is more important than “what?”
  55. 55. Three most common data visualization mistakes Boris Gorelik, Ph.D.
 boris@gorelik.net
 http://gorelik.net
  56. 56. Course Title Reading material https://gorelik.net
  57. 57. Course Title

Accompanying slides to my data visualization workshop. https://gorelik.net/2018/05/01/i-will-host-a-data-visualization-workshop-at-israels-biggest-data-science-event/

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