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Introduction to Data Visualization

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This is a presentation I gave on Data Visualization at a General Assembly event in Singapore, on January 22, 2016. The presso provides a brief history of dataviz as well as examples of common chart and visualization formatting mistakes that you should never make.

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Introduction to Data Visualization

  1. 1. Stephen Tracy COMMUNICATINGWITH DATA An Introduction to DataVisualization linkedin.com/in/tracystephen @stephen_tracy analythical.com
  2. 2. AN INTRODUCTION
  3. 3. “You can have piles of facts and still fail to resonate. It’s not the information itself that’s important but the emotional impact of that information.” “[few] grasp how to use data to tell a meaningful story that resonates both intellectually and emotionally with an audience” Nancy Duarte – Writer, Speaker, CEO Daniel Waisberg - Analytics Advocate, Google
  4. 4. when most people think about dataviz, they think about this
  5. 5. 5 AN INTRODUCTION 4.3 2.5 3.5 4.5 2.4 4.4 1.8 2.8 2 2 3 5 0 2 4 6 Singapore Hong Kong Indonesia Philippines Volume 2013 2014 2015 58%23% 10% 9% 1st Qtr 2nd Qtr 3rd Qtr 4th Qtr 0 2 4 6 8 Category 1 Category 2 Category 3 Category 4 Category 5 Category 6 Category 7 Category 8 Category 9 Category 10 Volume Series 1 Series 2 Series 3 0 10 20 30 40 0 5 10 15 20 25 Time Occurrence but data visualization starts with the basics
  6. 6. 6 AN INTRODUCTION a primary goal of data visualization is to communicate information clearly and efficiently to users via the statistical graphics, plots, information graphics, tables, and charts selected data visualization the visual representation of data “the purpose of visualization is insight, not pictures” - Ben Shneiderman, computer scientist
  7. 7. 7 IMAGE CREDIT: JEFFVICTOR -WWW.JEFFVICTOR.COM
  8. 8. THE GOOD
  9. 9. 9 SOME HISTORY charles joseph minard Napoleon’s Russian campaign of 1812 Produced in 1869
  10. 10. 10 Minard’s map is notable for plotting 6 different data points on a single graphic
  11. 11. 11 LOCATION & DIRECTION SIZE OF ARMY DISTANCE TEMPERATURE ADVANCE RETREAT
  12. 12. 12 SOME HISTORY charles joseph minard Cattle distribution and consumption in France Produced in 1858
  13. 13. 13 Although this wasn’t the first use of the pie chart, Minard popularized it’s use with his graphic depiction of cattle volumes and distribution throughout France. Remember, this was hand drawn!
  14. 14. 14 VOLUME OF CATTLE LOCATION TYPE OF MEAT
  15. 15. 15 A BayArea (Redwood CityWharf) tide prediction diagram for each 24-hour day in the Month of June 2013 Source: http://www.informationisbeautifulawards.com/showcase/150-tide-predictions
  16. 16. 16 Thematic map that shows the distribution and biodiversity of NewYork City’s street trees based on the last tree census. Source: http://jillhubley.com/project/nyctrees/
  17. 17. 17 THE BAD
  18. 18. 18 what’s wrong with it? No Y axis Multi-axis not declared and labelled what is it? Chart shown by Rep Jason Chaffetz during Planned Parenthood hearing Watch it here - http://bit.ly/1UhTYoU X-axis spans 8 years, but chart only includes 2 years (2006 and 2013) Example 1 – Lying with data
  19. 19. 19 Example 1 – Lying with data Planned Parenthood – Abortions vs Cancer Screening Services Bar Chart | Single Axis | Vertical how to fix it? if you are comparing data between 2 non- adjacent years a bar chart would be a better choice here’s the same data in a bar chart, and on a single axis
  20. 20. 20 Example 1 – Lying with data Planned Parenthood – Abortions vs Cancer Screening Services how to fix it? Line Chart | Single Axis Better yet, if you retrieve the data for the missing years you can use a line chart to show the change over time here’s the same data in a line chart with the missing years (2007 – 2012) included. *Note, 2008 is missing as I couldn’t find the report for that year
  21. 21. 21 Example 1 – Lying with data Planned Parenthood – Abortions vs Cancer Screening Services how to fix it? And for good measure, here’s the same data represented using a multi axis chart, and with the axis’ properly labelled Line Chart | Multi Axis
  22. 22. 22 Example 1 – Lying with data Stacked Bar Chart | Horizontal Here’s a slightly different way to look at this data. The above is a stacked bar chart, which shows the % share of all services PP offers, not just Abortions and Cancer Screening. Notice that, as a % of total services, Abortions is constant at 3% every year. Read more about this chart on my blog - http://bit.ly/1nrbi0x how to fix it?
  23. 23. 23 Example 2 – Lying with data Line Chart | Single Axis what’s wrong with it? Y axis inflated, removes reader’s ability to see meaningful change in data what is it? national review (@NRO) chart depicting change in global average temperature over time See it here - http://bit.ly/23klTus Chart does not convey context. The increase in global average temp of just 2 degrees can have significant effects on our planet, so using 120 point scale removes important context and makes this chart impossible to read Average Global Temperature (Fahrenheit)
  24. 24. 24 Example 2 – Lying with data Figure 5. Average Global Temperature (Fahrenheit) - relative scale Line Chart | Single Axis how to fix it? Adjust the y-axis so it shows the full context of the data.
  25. 25. 25 what’s wrong with it? Too much non-data ink Poor chart labeling what is it? Chart shown by Fox News that shows Average Annual economic growth in the USA. Unequal time intervals Example 3 – Deceptive Visualization
  26. 26. 26 Example 3 – Deceptive Visualization how to fix it? Strip away all unnecessary formatting (e.g. data ink) See more here - http://bit.ly/2eIpC18
  27. 27. 27 Example 3 – Deceptive Visualization
  28. 28. 28 Example 3 – Deceptive Visualization
  29. 29. 29 THE UGLY
  30. 30. 30 Example 4 – The parts don’t add up to a whole Pie Chart what’s wrong with it charted values different from actual values data labels in legend instead of on chart what is it? Infographic about U.S. lifestyle trends
  31. 31. 31 Example 4 – The parts don’t add up to a whole Pie Chart what’s wrong with it charted values different from actual values data labels in legend instead of on chart what is it? Infographic about U.S. lifestyle trends
  32. 32. 32 Example 4 – The parts don’t add up to a whole Pie Chart how to fix it? The reason this happened was because the author didn’t have a firm grasp of the dataset and how it was structured. For example, a pie chart would actually work here if the data series was inverted so each chart represents a year and is broken down by the desire states, instead of the other way around.
  33. 33. 33 Example 5 – Wrong chart Tree Map what is it? what’s wrong with it infographic about millennials and brunch box proportions aren’t accurate wrong choice of chart, data isn’t hierarchical box proportions aren’t accurate
  34. 34. 34 Example 5 – Wrong chart Tree Map how to fix it? Always ensure you choose the right chart that enables you to accurately and meaningfully present your data. Here’s a hand resource which helps you select the right chart based on what you’re attempting to show (i.e. distribution, composition, comparison, etc). Also, when constructing your charts don’t ever eyeball scale, proportion or distance. If you create charts manually by hand you run the risk of misrepresenting the data
  35. 35. 35 Example 6 – Confusing chart Radial Bar Chart what is it? what’s wrong with it Infographic on JD.com sales and growth missing important visual cues rings shouldn’t go 360 degrees
  36. 36. 36 Example 6 – Confusing chart Radial Bar Chart how to fix it? Make sure you chart is intuitive and easy to read, and never sacrifice readability for creative flare. For radial bar charts follow the basic formatting rules; don’t design the chart so the rings go a full 360 degrees and clearly label your data.
  37. 37. 37 Example 7 – Charts within charts Pie Chart what’s wrong with it how to fix it? charts within charts convoluted datapoints and interpretation don’t embed charts within charts don’t make data needlessly confusing. If it’s difficult to interpret your not finished Read more about how to fix this chart: http://bit.ly/1nxbZ8t
  38. 38. 38 Example 8 – Meaningless visualization what’s wrong with it how to fix it? bubble size has no relation to value inside unintentional Venn diagram gives data new meaning Always think about how your design choices impact the interpretation of your data and design with purpose Read more about how to fix this chart: http://bit.ly/1nxbZ8t
  39. 39. 39 Example 8 – Meaningless visualization what’s wrong with it Too many variables on a single chart (e.g. year, response state, % of respondents)
  40. 40. DATAVIZ PRINCIPLES
  41. 41. 41 choose the right charts one
  42. 42. 42
  43. 43. 43 follow basic chart formatting rules two
  44. 44. 44 bad
  45. 45. 45 good
  46. 46. 46 good always include axis titles add figure labels and use a descriptive title always include a legend Use colours effectively start with zero axis baseline and only adjust if it helps to provide useful context, and so long as it’s truthful
  47. 47. 47 make your charts intuitive three
  48. 48. 48 conduct a readability test Find some people to look at your chart or infographic Let them look at it for 10 seconds Ask them 2 questions “What was the underlying dataset about?” “What conclusion or conclusion(s) did you take away from it?” 1. 2. 3. If anyone didn’t understand what the data was about, you need to rethink your design. If their conclusions are not aligned with your intended message or their conclusions are wildly different across your test audience, you’ve got more work to do.
  49. 49. 49 context is everythingfour
  50. 50. 50 would you buy this stock?
  51. 51. 51 Blackberry (BBRY) Stock – 5 Year Performance how about now?
  52. 52. 52 design with purposefive
  53. 53. 53 Don’t just fill a dashboard or report with meaningless charts. Every chart and graphic should have a specific purpose… and should be formatted correctly
  54. 54. 54 make the complex simple six
  55. 55. 55 When it comes to visualizing data, your goal should always be to make the complex simple. If your chart looks like this, you have failed
  56. 56. 56 don’t use too much non-data ink seven
  57. 57. 57
  58. 58. 58 make it beautifuleight
  59. 59. 59 make it beautifulseven
  60. 60. PRACTICAL STEPS
  61. 61. 61 LESSONS some resources Flowing Data – Basic Rules for Making Charts - http://bit.ly/1nqd3v7 Visage: Data Viz 101 - http://bit.ly/1ncO4dK National Geographic – Spotting Charts that Lie - http://bit.ly/1Guozac Analythical - My Blog! – analythical.com
  62. 62. linkedin.com/in/tracystephen @stephen_tracy analythical.com THANKYOU

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