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Want to make your data visualizations sing? Email [email protected]
What Chart to Use and When: Basic Best Practices for Data Visualizations
How to find your inner Stephen Few, Edward Tufte, Ben Fry, & Avinash Kaushik
Bruce E. Segal For Philadelphia Tableau User Group
July 2011 Meeting
To make your data visualizations sing, email [email protected] © Bruce E. Segal, 2012 All Rights Reserved
We are overwhelmed by information …. Computers speed the process of handling information,
but they don't tell us what the information means or how to communicate its meaning to decision makers
–Steven Few
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Introduction What Chart to Use and When–Basic Data Visualization Best Practices
Goals for this Presentation:
What I Want You to Remember When You Leave The Room: 1.Tell A Story. This means we have to think about the data and look at
different charts and graphs.
2.Information Dense Presentations... Lead Viewers to Ask Questions
(but wait my viewers want answers)
3.Use a Hammer with Nails. So Use a Line Graph with Time Data… When to use line charts, bar charts, pie charts, heat maps & scatter plots.
4.Be the Hero. Show the Zero. (Use the full Y axis.)
5.Always Add Internal and External Benchmarks. They add context and
validation.
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The Archetypes. The Touch Stones For Data Visualization Menard’s Napoleon’s March across Europe
Tells Story. Clear + Dense Info. Data Integrity.
1.Look at financial pages – Edward Tufte tip. Those folks use density to solve
the problem of conveying lots of information, clearly, and in small space.
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What to Use and When
First look at ALL the data. It’s easy to think selecting part of it is more focused
or simpler. Instead it blinds you into making wrong decisions.
Get the tooth, the hole tooth and nutting but the two.
“‘Three blind analysts and a data warehouse.’ Business people struggle
every day to make sense of data, stumbling blindly, touching only
small parts of the information, and coming away with a narrow and
fragmented understanding of what it means. Conventional BI tools make it unnecessarily difficult to explore data from multiple perspectives, so analysts
tend to pursue only a limited set of predetermined questions. It is simply too
time consuming to explore the data thoroughly, allowing fresh discoveries to
lead them to comprehensive and free-flowing exploration. Without the ability
to examine data from multiple perspectives simultaneously, many of the meaningful relationships that exist in our data will remain hidden.”
–Stephen Few
http://www.perceptualedge.com/articles/Whitepapers/Three_Blind_Men.pdf
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What to Use and When
Line Graphs to show trends and changes over time.
Cycle Graphs special form of line graph to evaluate seasonality over time.
Bar Graphs to compare across types.
Bar Graphs to show distribution.
Pie charts to show distribution – in only one instance. 99% and 1&
Scatter Plots to show relationship or lack of relationship between two numbers.
And many others not covered here.
Juice Analytics Chart Chooser http://labs.juiceanalytics.com/chartchooser.html
Line graphs for time series
Spark lines (sizzle lines)–Tufte’s invention
Bar graphs for comparisons
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Cycle Charts: http://www.exceluser.com/dash/cycleplot1.htm
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Scatter Plots for Relationships and Trend Lines!!
Go to scatter plot example of Search Phrase on conversion rate.
Failure to use a trend line in a scatter plot contributed to the Shuttle
Challenger fuel tank explosion. http://www.datavis.ca/gallery/missed.php
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Histograms – Distro Curves – Bell curves and why they matter a few years after high school
http://www.isixsigma.com/tools-templates/normality/tips-recognizing-and-
transforming-non-normal-data/
Before: Raw Data
After: Fitting the Raw Data to a Normal Curve (Many steps omitted.)
Want to make your data visualizations sing? Email [email protected]
Want to make your data visualizations sing? Email [email protected]
External Benchmarks: An example
Use grey for benchmark. Note use of conclusion in title. Note use of financial combo of line over bar
graph. Note pane lines in center graphs. I might create confusion w 2 diff’t color scales for %.
If audience wants, put .tbw on screen to show how to set pane lines.
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Bad Graphs Examples & Why:
Graphs Gone Wild, Chart Porn, Chart Junk. Dishonest Graphs (Not to zero.
Double axis – hides the reality of the data)
Klout’s line graphs: When does a 5 point drop on a
scale of 100 look huge?
When Klout misleads you?
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Resources:
The Touch Stones Plus Some Others
Stephen Few:
http://www.perceptualedge.com/ His discussion forum
http://www.perceptualedge.com/discussion.htm
Edward Tufte
http://www.edwardtufte.com/tufte/index
Avinash Kaushik: Book, Blog – Occum’s Razor http://www.kaushik.net/avinash/digital-marketing-analytics-crimes-
against-humanity/
Jakob Nielsen
Naomi Robbins http://www.nbr-graphs.com/examples
Great example of charts used to tell stories
Okay Cupid Blog: http://blog.okcupid.com/ http://blog.okcupid.com/index.php/your-race-affects-whether-people-
write-you-back/
Uber: Used crime data to predict when to send cabs into a service area.
http://blog.uber.com/2011/04/11/uberdata-the-hidden-cost-of-cabs/
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Extreme Presentation Method: http://www.extremepresentation.com/
Data Visualization Sources
Examples of bad graphs http://www.datavis.ca/gallery/missed.php
Why Infographics are misleading
Dis-InfoGraphics or
http://www.informationisbeautiful.net/ How to do infographics right as per Stephen Few. You can present
information and data that’s engaging, informative and beautiful. Few do.
http://biblogg.no/2012/02/15/data-blooms-in-beauty-and-truth/
What Charts To Use When and Why
Alan Smithee, great examples of charts to use and when
http://www.alansmitheepresents.org/
Great info about which graph to use and when. Juice Analytics http://chartchooser.juiceanalytics.com/
More great info on which chart to use when:
http://www.add-knowledge.com/
Want to make your data visualizations sing? Email [email protected]
Tableau’s what graph to use when .pdf http://www.tableausoftware.com/learn/whitepapers/which-chart-or-graph-
is-right-for-you
Miller Samuel, the NYT chart company
http://www.millersamuel.com/ Sparklines, Beanlines and more oh my
http://sparklines-excel.blogspot.com/
An example of Cohort Analysis:
http://www.mininglabs.com
Use Histograms and data transformation to id the true outliers http://www.isixsigma.com/tools-templates/normality/tips-recognizing-
and-transforming-non-normal-data/
