Data Visualization Introduction Process Why Not Design Principles Resources Why Tools Ben Thompson ben.thompson@kingcounty.gov WSLGAA, March 20, 2012 1 Me Data visualization Introductions 2
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Data Visualization Recipe Visualization 5 6
7 Data as Table INDEX 1980=100 OECD country municipal waste generation, 1980 2030 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 GDP OECD 100 113 129 146 163 193 219 249 277 306 337 Population OECD Total municipal waste generation 100 104 108 112 116 121 124 128 130 132 134 100 112 126 142 158 165 178 191 203 215 228 What is the message? 8
Data as visual 9 Data as visual Data from the International Federation of Health Plans Surveyed 20 procedures, drug costs, and health spending as a % of GDP Presented in a report with 26 separate column charts Does anyone care about this comparison when presented solely by procedure? 10
http://www.washingtonpost.com/wp-srv/special/business/high-cost-of-medical-procedures-in-the-us/ 11 12
Process Find Characterize Data Audience Who are they Knowledge Level Pick Test Visualization Create Report 13 Audience Who is your audience? What is their level of knowledge/expertise in this subject? How are they going to interact with the graphic: Web only, hard copy, mobile devices? 14
Only You Can Prevent Bad Charts 15 16
Extremepresentation.com 17 Chart Chooser http://www.juiceanalytics.com/chart chooser/ 18
Guidelines Match Data to Format Line Charts Track progress over time (trends) Time on the x axis and quantities on the y axis Bar Charts Show relationships between groups or for a single group over time Pie Charts Show composition of a whole 19 Chart Design Principles Computer Ownership 1997 2003 70 60 50 40 30 20 10 0 Households (millions) 37 18 Presence of Computer 42 26 47 34 51 42 Internet Access 56 59 62 50 53 55 1997 1998 1999 2000 2001 2002 2003 Computer Ownership 1997 2003 Households (millions) Avoid Fancy Formatting Use color sparingly to make points in your graph Don t use 3D effects or charts Presence of Computer 1997 1998 1999 2000 2001 2002 2003 37 42 47 51 56 59 62 Internet Access 18 26 34 42 50 53 55 20
Chart Design Principles Avoid Chart Junk Skip effects Remove gridlines and borders when possible Reduce data label overload Eliminate meaningless trend lines 21 Chart Design Principles In 2003, almost 90% of households owning a computer were online, up from almost 50% in 1997 Households (millions) Presence of Computer 1997 1998 1999 2000 2001 2002 2003 37 42 47 51 56 59 62 Internet Access 18 26 34 42 50 53 55 Use Data Tables Data tables can replace data labels without cluttering chart Use Meaningful Titles Chart title can prime reader with what they should be looking for 22
Chart Design Principles Beware of Pie Charts Tempting to use when separating a population Most effective when there are limited number of groups (3 5) Bar chart can be more effective 23 Pie Chart Formating 2nd largest Largest Segment 3rd largest 4th largest 24
Chart Design Principles Replace Complex Chart With Several Simple Charts 25 Sparklines Proposed by Tufte as small high resolution graphics or word graphs 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Blue Jays 80 78 86 67 80 87 83 86 75 85 81 Orioles 63 67 71 78 74 70 69 68 64 66 69 Rays 62 55 63 70 67 61 66 97 84 96 91 Red Sox 82 93 95 98 95 86 96 95 95 89 90 Yankees 95 103 101 101 95 97 94 89 103 95 97 Free Plug-in for Excel 2003/2007 - Sparklines-excel.blogspot.com or Tinygraphs 26
Chart Design Principles Sometimes a Table is the Best Answer 27 Table Guidelines Only use when you have a really large or really small amount of data Minimize grid lines and alternating gray shading Use thin rules after three to five entries, based on the width of the table Use shading to highlight important column of data or entry Round off all figures to same number of places Align whole numbers flush to the right Table guidelines from Dona Wong, Wall Street Journal Guide to Information Graphics 28
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Data Visualization Checklist Can I substitute a table with a graphic? What type of visualization makes sense given my data and message? Does my graphic make sense to a cold reader? Does the graphic assume knowledge that my audience lacks? Have I used 3D in my graphic? Does my chart make sense in grayscale? Do I have unnecessary gridlines or borders? Is my data labeled logically such that it minimizes the amount of work by the reader? Would a data table be appropriate? Do I have a meaningful title? Do I really want to use a pie chart? If so, is it formatted logically? Does it make sense to separate one complex chart into several simpler chart? Was a table really the right answer? If so, have I formatted my table to focus on the data and not the formatting? 31 Data Visualization Tools Intuitive Many Eyes Tableau Public Google Fusion Tables www 958.ibm.com/software/data/cognos/manyeyes/ www.tableausoftware.com/public www.google.com/fusiontables/home/ Non Intuitive Graphiz GGOBI Gephi http://www.graphviz.org/ http://www.ggobi.org/ http://gephi.org/ 32
Other Resources Books Free Manual The Wall Street Journal Guide to Information Graphics by Dona Wong Now You See It: Simple Visualization Techniques for Quantitative Analysis by Stephen Few Visualizing Information for Advocacy http://tacticaltech.org/visualisingadvocacy 33 Other Resources Institutional Data Management at Berkeley Summer Series 2010: Turning Data into Information http://idmg.berkeley.edu/summerseries.html Data Therapy MIT Website with some interesting webinars http://datatherapy.wordpress.com/ Data Viz Improving visualization for the public sector http://www.improving visualisation.org/ Tableau Software Which chart or graph is right for you? 10 Chart Design Principle http://peltiertech.com/wordpress/tenchart design principles guest post/ http://www.tableausoftware.com/learn/whitepapers/which chart orgraph is right for you 34
Interesting Examples Economist Daily Chart http://www.economist.com/blogs/graphicdetail Washington Post Wonk Blog Graphs http://www.washingtonpost.com/2011/02/25/abjfuej_category.html?blo gid=ezra klein&tag=graphs The Data Mine from CQ http://media.cq.com/blog/ Modern Data Visualization Approaches http://www.smashingmagazine.com/2007/08/02/data visualizationmodern approaches/ Interesting and Clever Charts http://www.informationisbeautiful.net/ 35 36