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Storytelling through data

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How to use visual storytelling techniques on a dataset

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Storytelling through data

  1. 1. 1 STORYTELLING THROUGH DATA GARTNER QUANT IMMERSION, 11 OCT 2017
  2. 2. A DATA VISUALISATION CHALLENGE… You will see 3 questions. You have 30 seconds. Try it! Your timer starts now
  3. 3. 3 HOW MANY NUMBERS ARE ABOVE 100? 23 32 71 72 58 87 11 77 70 16 17 21 56 44 68 51 84 20 60 40 37 8 107 14 12 41 69 14 18 71 62 55 59 64 33 55 71 58 103 92 101 56 45 34 43 15 73 78 6 93 39 53 22 26 26 94 60 82 99 74 11 12 36 67 70 71 97 59 73 99 75 74 69 69 51 48 2 66 92 98 15 10 41 58 104 94 92 84 74 82 12 52 10 57 33 77 88 81 81 91 15 56 25 30 21 7 66 66 78 87 29 23 5 34 11 96 74 99 99 88 37 10 43 15 50 71 65 60 101 98 46 34 19 102 57 70 95 84 63 91 3 34 39 37 60 81 65 63 9 71 48 46 25 50 22 64 91 76 71 79 1
  4. 4. 4 HOW MANY NUMBERS ARE BELOW 10? 23 32 71 72 58 87 11 77 70 16 17 21 56 44 68 51 84 20 60 40 37 8 107 14 12 41 69 14 18 71 62 55 59 64 33 55 71 58 103 92 101 56 45 34 43 15 73 78 6 93 39 53 22 26 26 94 60 82 99 74 11 12 36 67 70 71 97 59 73 99 75 74 69 69 51 48 2 66 92 98 15 10 41 58 104 94 92 84 74 82 12 52 10 57 33 77 88 81 81 91 15 56 25 30 21 7 66 66 78 87 29 23 5 34 11 96 74 99 99 88 37 10 43 15 50 71 65 60 101 98 46 34 19 102 57 70 95 84 63 91 3 34 39 37 60 81 65 63 9 71 48 46 25 50 22 64 91 76 71 79 2
  5. 5. 5 WHICH QUADRANT HAS THE HIGHEST TOTAL? 23 32 71 72 58 87 11 77 70 16 17 21 56 44 68 51 84 20 60 40 37 8 107 14 12 41 69 14 18 71 62 55 59 64 33 55 71 58 103 92 101 56 45 34 43 15 73 78 6 93 39 53 22 26 26 94 60 82 99 74 11 12 36 67 70 71 97 59 73 99 75 74 69 69 51 48 2 66 92 98 15 10 41 58 104 94 92 84 74 82 12 52 10 57 33 77 88 81 81 91 15 56 25 30 21 7 66 66 78 87 29 23 5 34 11 96 74 99 99 88 37 10 43 15 50 71 65 60 101 98 46 34 19 102 57 70 95 84 63 91 3 34 39 37 60 81 65 63 9 71 48 46 25 50 22 64 91 76 71 79 3
  6. 6. A DATA VISUALISATION CHALLENGE… We’ll answer the same questions again. But with simple visual cues. See how long it takes. Your timer starts now
  7. 7. 7 23 32 71 72 58 87 11 77 70 16 17 21 56 44 68 51 84 20 60 40 37 8 107 14 12 41 69 14 18 71 62 55 59 64 33 55 71 58 103 92 101 56 45 34 43 15 73 78 6 93 39 53 22 26 26 94 60 82 99 74 11 12 36 67 70 71 97 59 73 99 75 74 69 69 51 48 2 66 92 98 15 10 41 58 104 94 92 84 74 82 12 52 10 57 33 77 88 81 81 91 15 56 25 30 21 7 66 66 78 87 29 23 5 34 11 96 74 99 99 88 37 10 43 15 50 71 65 60 101 98 46 34 19 102 57 70 95 84 63 91 3 34 39 37 60 81 65 63 9 71 48 46 25 50 22 64 91 76 71 79 HOW MANY NUMBERS ARE ABOVE 100? 1
  8. 8. 8 HOW MANY NUMBERS ARE BELOW 10? 23 32 71 72 58 87 11 77 70 16 17 21 56 44 68 51 84 20 60 40 37 8 107 14 12 41 69 14 18 71 62 55 59 64 33 55 71 58 103 92 101 56 45 34 43 15 73 78 6 93 39 53 22 26 26 94 60 82 99 74 11 12 36 67 70 71 97 59 73 99 75 74 69 69 51 48 2 66 92 98 15 10 41 58 104 94 92 84 74 82 12 52 10 57 33 77 88 81 81 91 15 56 25 30 21 7 66 66 78 87 29 23 5 34 11 96 74 99 99 88 37 10 43 15 50 71 65 60 101 98 46 34 19 102 57 70 95 84 63 91 3 34 39 37 60 81 65 63 9 71 48 46 25 50 22 64 91 76 71 79 2
  9. 9. 9 WHICH QUADRANT HAS THE HIGHEST TOTAL? 3 23 32 71 72 58 87 11 77 70 16 17 21 56 44 68 51 84 20 60 40 37 8 107 14 12 41 69 14 18 71 62 55 59 64 33 55 71 58 103 92 101 56 45 34 43 15 73 78 6 93 39 53 22 26 26 94 60 82 99 74 11 12 36 67 70 71 97 59 73 99 75 74 69 69 51 48 2 66 92 98 15 10 41 58 104 94 92 84 74 82 12 52 10 57 33 77 88 81 81 91 15 56 25 30 21 7 66 66 78 87 29 23 5 34 11 96 74 99 99 88 37 10 43 15 50 71 65 60 101 98 46 34 19 102 57 70 95 84 63 91 3 34 39 37 60 81 65 63 9 71 48 46 25 50 22 64 91 76 71 79
  10. 10. DRAW FOCUS TO PRIORITIES THIS IS ONE OF THE REASONS TO VISUALIZE DATA
  11. 11. 11 CRICKET FASTEST SCORERS “ I’ve always been curious… who among India’s prolific one-day run-getters had the best strike rate? Sachin? Sehwag? What about the rest of the world?
  12. 12. 12 LET’S TAKE ONE DAY CRICKET DATA Country Player Runs ScoreRate MatchDate Ground Versus Australia Michael J Clarke 99* 93.39 30-06-2010The Oval England Australia Dean M Jones 99* 128.57 28-01-1985Adelaide Oval Sri Lanka Australia Bradley J Hodge 99* 115.11 04-02-2007Melbourne Cricket Ground New Zealand India Virender Sehwag 99* 99 16-08-2010Rangiri Dambulla International Stad. Sri Lanka New Zealand Bruce A Edgar 99* 72.79 14-02-1981Eden Park India Pakistan Mohammad Yousuf 99* 95.19 15-11-2007Captain Roop Singh Stadium India West Indies Richard B Richardson 99* 70.21 15-11-1985Sharjah CA Stadium Pakistan West Indies Ramnaresh R Sarwan 99* 95.19 15-11-2002Sardar Patel Stadium India Zimbabwe Andrew Flower 99* 89.18 24-10-1999Harare Sports Club Australia Zimbabwe Alistair D R Campbell 99* 79.83 01-10-2000Queens Sports Club New Zealand Zimbabwe Malcolm N Waller 99* 133.78 25-10-2011Queens Sports Club New Zealand Australia David C Boon 98* 82.35 08-12-1994Bellerive Oval Zimbabwe Australia Graeme M Wood 98* 63.22 11-01-1981Melbourne Cricket Ground India England Ian J L Trott 98* 84.48 20-10-2011Punjab Cricket Association Stadium India India Yuvraj Singh 98* 89.09 01-08-2001Sinhalese Sports Club Ground Sri Lanka Ireland Kevin J O'Brien 98* 94.23 10-07-2010VRA Ground Scotland Kenya Collins O Obuya 98* 75.96 13-03-2011M.Chinnaswamy Stadium Australia Netherlands Ryan N ten Doeschate 98* 73.68 01-09-2009VRA Ground Afghanistan New Zealand James E C Franklin 98* 142.02 07-12-2010M.Chinnaswamy Stadium India Pakistan Ijaz Ahmed 98* 112.64 28-10-1994Iqbal Stadium South Africa South Africa Jacques H Kallis 98* 74.24 06-02-2000St George's Park Zimbabwe
  13. 13. 13 Against which countries are higher averages scored? Which countries’ players score more per match?
  14. 14. 14 Which player scores the most per ball? The player with the highest strike rate is an obscure South African whose name most of us have never heard of. In fact, this list is filled with players we have never heard of.
  15. 15. 15 ODI STRIKE RATES OF THE WORLD We want to see the prioritised performance. That is, what is the strike rate of the established players? LINK
  16. 16. 16 Rs 7,700 cr
  17. 17. 17 Dr Udayakumar 382 IPC cases Pushparayan 380 IPC cases
  18. 18. SURFACE HIDDEN INSIGHT THIS IS ONE OF THE REASONS TO VISUALIZE DATA
  19. 19. 19 100YEARSOFINDIA’SWEATHER 1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2001 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec LINK
  20. 20. 20 RESTAURANT FOUND AN UNUSUAL DIP IN SALES A restaurant chain had data for every single transaction made over a few years. Plotting this as a time series showed them nothing unusual. However, the same data on a calendar map reveals a very different story. Specifically, at the bottom left point-of-sale terminal, sales dips on every Wednesday. At the bottom right point-of-sale terminal, sales rises on every Wednesday (almost as if to compensate for the loss.) It turns out that the manager closes the bottom-left counter every Wednesday afternoon due to shortage of staff, assuming that it results in no loss of sales. There is, however, a net loss every Wednesday. A similar visual helped a telecom company identify specific days on which their competitors’ market share rose significantly, enabling them to negate the strategy. Communicating data visually is the most effective way to a shared understanding
  21. 21. 21
  22. 22. 22 68% correlation between AUD & EUR Plot of 6 month daily AUD - EUR values Block of correlated currencies … clustered hierarchically
  23. 23. ALLOW CONSISTENT INTERPRETATION THIS IS ONE OF THE REASONS TO VISUALIZE DATA
  24. 24. 24 CONSISTENT CONCLUSIONS FROM DATA Stock market crash? Doesn’t look so bad.. This gives the right perspective Source: http://www.cc.gatech.edu/~stasko/7450/index.html The same dataset can lead to very different conclusions. Visualizations freeze the rendering of data, allowing a consistent (and hopefully correct) interpretation.
  25. 25. 25 WINNING PARTIES In the 2004 election to Lok Sabha there were 1,351 candidates from 6 National parties, 801 candidates from 36 State parties, 898 candidates from officially recognised parties and 2385 Independent candidates. The Congress (INC) won 145 seats in the 2004 elections. BJP won 138, coming a close second. The constituencies where each party won is shown here. Party BJP BSP CPM INC RJD SP
  26. 26. 26 Party BJP BSP CPM INC RJD SPWINNING PARTIES In the 2004 election to Lok Sabha there were 1,351 candidates from 6 National parties, 801 candidates from 36 State parties, 898 candidates from officially recognised parties and 2385 Independent candidates. The Congress (INC) won 145 seats in the 2004 elections. BJP won 138, coming a close second. The constituencies where each party won is shown here.
  27. 27. WHAT SHOULD I TALK ABOUT NOW? I’VE ALWAYS HAD A PROBLEM DETERMINING AUDIENCE INTEREST
  28. 28. We have internal information. Getting information from outside is our challenge. There’s no way of doing that. – Senior Editor Leading Media Company “
  29. 29. 29 INDIA’S RELIGIONS LINK
  30. 30. 30 AUSTRALIA’S RELIGIONS LINK
  31. 31. 31 LINK
  32. 32. 32 WHAT DO PEOPLE LOOKING FOR IN VISUALIZATION? USA India data visualization tools data visualization software data visualization examples data visualization jobs data visualization tools data visualization techniques data visualization examples data visualization software Tools & Software Techniques & Examples
  33. 33. WHAT TOOLS SHOULD YOU USE? THIS IS ONE OF THE MOST FREQUENT QUESTIONS I’M ASKED
  34. 34. 34 DATA SCIENCE TOOLS Alteryx Amazon EC2 Azure ML BigQuery Birst Caffe Cassandra Cloud Compute Cloudera Cognos CouchDB D3 Decision tree ElasticSearch Excel Gephi ggplot2 Hadoop HP Vertica IBM Watson Impala Julia Jupyter Notebook Kafka Kibana Kinesis Lambda Logstash MapR MapReduce Matplotlib Microstrategy MongoDB NodeXL Pandas Pentaho Pivotal PowerPoint Qlikview R R Studio Random Forest Redis Redshift Regression Revolution R S3 SAP Hana SAS Spark Spotfire SPSS SQL Server Stanford NLP Storm SVM Tableau TensorFlow Teradata Theano Thrift Torch Weka Word2Vec The tool does not matter. A person’s skill with the tool does. Pick the person. Let them pick the tool.
  35. 35. I’M FAMILIAR WITH EXCEL I TURN TO IT AS A FIRST CHOICE FOR ALMOST EVERYTHING
  36. 36. 36 LINK
  37. 37. 37 LINK
  38. 38. 38 LINK
  39. 39. 39 Profits Made: Over the last 6 years, you would have beaten a 10% Inflation about 82% of the time and lost out about 18% of the time. So, mostly, you would have made money on Cipla with an average return of 14.9%. Highest Returns: An average return of 14.1% has been observed when held for a period of one year. with a maximum of 79.6% if sold in Dec 2009, after being held for a year. And a maximum of 486.9% if sold at the end of Nov 2007 after holding for a month. The highest stock price was Rs 414 in Nov/Dec 2012. -50% +50%returns WHEN TO INVEST This visual shows the returns from buying Cipla’s stock on any given month, and selling it in another. The color of each cell is the return (red is low, green is high) if you had invested in the stock in a given month and sold it on another. For example this mild red is the slightly negative return if you had bought Cipla stock in Mar 2011 (the row) and sold it in Jun 2011 (the column). Link
  40. 40. 40 LINK
  41. 41. 41 LINK
  42. 42. I’M FAMILIAR WITH POWERPOINT IT’S ALSO A TOOL MOST OF OUR CLIENTS USE
  43. 43. 43 BJP INC JD(S) IND BJP sweep INC majority 80,000 voters (Shivajinagar) 170,000 voters (Bangalore South) KARNATAKA ASSEMBLY ELECTIONS: WINNING PARTIES (2008)
  44. 44. 44
  45. 45. 45 PORTFOLIO PERFORMANCE VISUAL Worldwide$288.0mn A: Accelerate$68.9mn B: Build$77.2mn C: Cut down$141.9mn Worldwide: $288 mn The visualization shows the market opportunities across various countries to identify areas of focus. This chart has been built as an interactive-app to present the key findings, while letting user click-through and drill-down to a custom view across 4 different levels. LINK
  46. 46. 46 LINK
  47. 47. TOOLS DO HELP, OF COURSE FOR SOME THINGS, YOU NEED THE RIGHT PLATFORM
  48. 48. 48 How does Mahabharata, one of the largest epics with 1.8 million words lend itself to text analytics? Can this ‘unstructured data’ be processed to extract analytical insights? What does sentiment analysis of this tome convey? Is there a better way to explore relations between characters? How can closeness of characters be analyzed & visualized? VISUALISING THE MAHABHARATA
  49. 49. 49 Recruiting top quality developers is always a problem. We decided to use an algorithmic approach and pulled out the social network of developers on Github (a social network for open source code). In this visualization, each circle is a person. The size of the circle represents the number of followers. Larger circles have more followers (but not in proportion – it’s a log scale.) The circle’s color represents the city the programmer’s live in. This visual is a slice showing the tale of two cities: Bangalore and Singapore Two people are connected if one follows the other. This leads to a clustering of people in the form of a network. Here, you can see that Bangalore and Singapore are reasonably well connected cities. Bangalore has more developers, but Singapore has more popular ones (larger circles). However, the interaction between Bangalore and Singapore are few and far between. But for a few people across both cities, like: … etc. Sudar, Yahoo! Anand C, Consultant Kiran, Hasgeek Anand S, Gramener Mugunth, Steinlogic Honcheng, buUuk Sau Sheong, HP Labs Lim Chee Aung Bangalore Singapore 1 follower 100 followers A follows B (or) B follows A Most followed in Bangalore Most followed in Singapore Ciju Cherian Lin Junjie Amudhi Sebastian There are, of course, a number of smaller independent circles – people who are not connected to others in the same city. (They may be connected to people in other cities.) Apart from this, there are a few small networks of connected people – often people within the same company or start-up – who form a community of their own. THE SOCIAL TALE OF TWO CITIES: BANGALORE & SINGAPORE
  50. 50. 50 SERVICE REQUEST WORKFLOW
  51. 51. THE MEDIUM & AUDIENCE MATTER ALIGN THE STORY TO WHO WILL CONSUME IT AND HOW
  52. 52. 52 GRAMENER AND CNN-IBN COVERED THE 2014 GENERAL ELECTIONS 19 M VIDEO 3 M VIDEO MediaMicrosoft
  53. 53. 53 GRAMENER & TIMES NOW COVERED THE 2016 STATE ELECTIONS Media 3 M VIDEO 4 M VIDEO Continued… PlatformMicrosoft
  54. 54. 54 HOW SEATS WERE RE-DISTRIBUTED ACROSS PARTIES THIS CHORD DIAGRAM WAS THE MOST USED VISUAL DURING THE SHOW LINK MediaContinued…
  55. 55. 55 WHERE DID THE MOST NUMBER OF CANDIDATES CONTEST? Media LINK Continued…
  56. 56. 56 WE DESIGN OUR OWN WALLS TOO… Design
  57. 57. 57Public SectorVisualizationPlatform
  58. 58. 58Design
  59. 59. 59 VIJAY KARNATAKA’S PUBLICATION ON CANDIDATE WEALTH LINK Media Based on candidate declarations, Karnataka 2013 Continued… Microsoft
  60. 60. 60 IMPACT OF THE BUDGET ON STOCK PRICES LINK Financial ServicesNarrativesMediaPublic SectorFinancePlatform
  61. 61. 61 WORLD BANK: INNOVATION, TECHNOLOGY & ENTREPRENEURSHIP Does access to new Technology facilitate Innovation? Does it facilitate Entrepreneurship? The Global Information Technology Report findings tell us that "innovation is increasingly based on digital technologies and business models, which can drive economic and social gains from ICTs...". We were curious about whether the data on TCData360 could tell a story about influential factors on innovation and entrepreneurship. With over 1800 indicators, we focused on the Networked Readiness Index, as it has indicators on entrepreneurship, technology, and innovation. LINK SocietyPlatform
  62. 62. … BUT CONTENT IS KING KEEP THE STORY AT THE FOREFRONT
  63. 63. 63 PREDICTING MARKS EDUCATION “ What determines a child’s marks? Do girls score better than boys? Does the choice of subject matter? Does the medium of instruction matter? Does community or religion matter? Does their birthday matter? Does the first letter of their name matter?
  64. 64. 64 TN CLASS X: ENGLISH 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
  65. 65. 65 TN CLASS X: SOCIAL SCIENCE 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
  66. 66. 66 TN CLASS X: MATHEMATICS 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
  67. 67. 67 ICSE 2013 CLASS XII: TOTAL MARKS
  68. 68. 68 PERFORMANCE DRIVERS Do girls score more than boys, or is it the other way around? Gender is a known driver of performance. Girls generally score higher. There is considerable variation across subjects, however. The differences in sciences is minimal. But languages, commerce and economics give girls a significant edge. There is also a correlation between girls’ dropout ratio and their over-performance – indicating perhaps that the smarter girls tend to stay back in school. Subject Girs higher by Girls Boys Physics 0 119 119 Chemistry 1 123 122 English 4 130 126 Computers 6 137 131 Biology 6 129 123 Mathematics 11 123 112 Language 11 152 141 Accounting 12 138 126 Commerce 13 127 114 Economics 16 142 126 WHO SCORES MORE? BOYS OR GIRLS?
  69. 69. 69 The marks shoot up for Aug borns … and peaks for Sep-borns 120 marks out of 1200 explainable by month of birth An identical pattern was observed in 2009 and 2010… … and across districts, gender, subjects, and class X & XII. “It’s simply that in Canada the eligibility cut-off for age-class hockey is January 1. A boy who turns ten on January 2, then, could be playing alongside someone who doesn’t turn ten until the end of the year—and at that age, in preadolescence, a twelve-month gap in age represents an enormous difference in physical maturity.” -- Malcolm Gladwell, Outliers SUN SIGNS Based on the results of the 20 lakh students taking the Class XII exams at Tamil Nadu over the last 3 years, it appears that the month you were born in can make a difference of as much as 120 marks out of 1,200. June borns score the lowest
  70. 70. 70 This is a dataset (1975 – 1990) that has been around for several years, and has been studied extensively. Yet, a visualization can reveal patterns that are neither obvious nor well known. For example, • Are birthdays uniformly distributed? • Do doctors or parents exercise the C-section option to move dates? • Is there any day of the month that has unusually high or low births? • Are there any months with relatively high or low births? Very high births in September. But this is fairly well known. Most conceptions happen during the winter holiday season Relatively few births during the Christmas and Thanksgiving holidays, as well as New Year and Independence Day. Most people prefer not to have children on the 13th of any month, given that it’s an unlucky day Some special days like April Fool’s day are avoided, but Valentine’s Day is quite popular More births Fewer births … on average, for each day of the year (from 1975 to 1990) LET’S LOOK AT 15 YEARS OF US BIRTH DATA
  71. 71. 71 THE PATTERN IN INDIA IS QUITE DIFFERENT This is a birth date dataset that’s obtained from school admission data for over 10 million children. When we compare this with births in the US, we see none of the same patterns. For example, • Is there an aversion to the 13th or is there a local cultural nuance? • Are holidays avoided for births? • Which months have a higher propensity for births, and why? • Are there any patterns not found in the US data? Very few children are born in the month of August, and thereafter. Most births are concentrated in the first half of the year We see a large number of children born on the 5th, 10th, 15th, 20th and 25th of each month – that is, round numbered dates Such round numbered patterns a typical indication of fraud. Here, birthdates are brought forward to aid early school admission More births Fewer births … on average, for each day of the year (from 2007 to 2013)
  72. 72. 72 THIS ADVERSELY IMPACTS CHILDREN’S MARKS It’s a well established fact that older children tend to do better at school in most activities. Since many children have had their birth dates brought forward, these younger children suffer. The average marks of children “born” on the 1st, 5th, 10th, 15th etc. of the month tend to score lower marks. • Are holidays avoided for births? • Which months have a higher propensity for births, and why? • Are there any patterns not found in the US data? Higher marks Lower marks … on average, for children born on a given day of the year (from 2007 to 2013) Children “born” on round numbered days score lower marks on average, due to a higher proportion of younger children
  73. 73. VISUALIZATION DESIGN TECHNIQUES THE GRAMMAR OF GRAPHICS
  74. 74. 74 Source: Designing Data Visualizations by Noah Iliinsky and Julie Steele (O’Reilly). Copyright 2011 Julie Steele and Noah Iliinsky, 978-1-449-31228-2. Position is the most powerful encoding. The eye and brain are naturally wired to detect mis-alignment of the smallest order 1 Colour, when used in context, is powerful. We can detect miniscule changes or variations in colour when comparing an element with neighbouring elements. This is what makes true colour (32-pixel colour, i.e. 4 billion) a necessity in computer graphics 2 Size is a useful differentiator. The eye can detect moderate size variations at moderate distances. Size also has a natural interpretation: that of priority. 3 Several other encodings are possible Aesthetics such as angle, shadows, shapes, patterns, density, labelling, enclosures, etc. can each be used to map data. 4 VISUAL ENCODINGS VARY IN THEIR EFFECTIVENESS
  75. 75. 75 POSITION IS EVERYTHING Absolute & relative departure time (continuous) Absolute & relative arrival time (continuous) Absolute & relative length of trip (continuous) Stopovers (binary) Absolute & relative stopover duration (continuous) Absolute & relative stopover start & stop time (continuous) Sort order (ranked) Source: http://hipmunk.com
  76. 76. 76 THE CONCEPT OF NATURAL ORDERING Source: European Soil Bureau. Copyright © 1995–2011, European Union. http://eusoils.jrc.ec.europa.eu/ Colour is not ordered
  77. 77. 77 BETTER USE OF COLOUR Source: http://mapsof.net/uploads/static-maps/topographic_(altitude)_map_tamil_nadu.png
  78. 78. 78 A DEFINITIVE HIERARCHY OF ENCODINGS EXISTS
  79. 79. WHERE TO LEARN MORE? REFERENCES
  80. 80. 80 BOOKS BY EDWARD TUFTE
  81. 81. GRAMENER.COM/DEMO/ MORE EXAMPLES TO EXPLORE

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