Presented by:

High Visibility: Using Data Visualization to Transform Data into Meaningful Information

Jeffrey A. Shaffer

Vice President, IT and Analytics, Unifund

Adjunct Professor, University of Cincinnati

www.DataPlusScience.com

@HighVizAbility

Welcome to Pie Charts Anonymous

Pie Charts

5 2 8 3 6 1 9 3 6 2 5 3 7 4 3 8 3 8 5 8 9 6 2 1 4 4 3 9 3 6 5 2 4 9 1 0 2 7 5 2 8 3 6 1 6 2 9 3 8 3 8 5 8 4 7 2 0 3 7 3 5 4 7 1 8 2 0 1 2 5 3 6 4 3 9 1 0 8 9 5 7 3 4 5 3 2 7 5 2 8 3 6 1 6 2 9 3 8 3 8 5 8 4 7 2 0 3 7 3 5 4 7 1 8 2 0 1 9 6 2 1 4 4 3 9 3 6 5 2 4 9 1 0 2 7 5 2 8 3 6 1 6 2 9 3 8 3 8 5 8 4 7 2 0 3 7 3 5 4 7 1 8 2 0 1 2 5 3 6 4 3 9 1 0 8 9 5 7 3 4 5 3 2 7 5 2 8 3 6 1 6 2 4 6 2 7 5 9 1 5 2 6 3 6

3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 7 7 7 7 7 7 7 77 7 7 7 7 7 7 7 7 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 0 0 0 0 0 0 0 0 0 0

This is how a Pie Chart Represents the Data

Try to quickly compare the totals of the digits.

3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 7 7 7 7 7 7 7 77 7 7 7 7 7 7 7 7 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 0 0 0 0 0 0 0 0 0 0

This is how a Pie Chart Represents the Data

Baseline moves based on previous # of DigitsRequires color encoding to differentiate

2222222222222222222222222222

55555555555555555555555

8888888888888888888888

6666666666666666666

444444444444444444

111111111111111111

This is how a Bar Chart Represents that Data

Easier comparison even without color encoding!

1. Don’t Use Pie Charts

If you must break Rule #1 then:

2. Make sure it adds up 100%

3. Only a few categories

4. Start at noon and move clockwise

5. Largest to Smallest Values

6. Add Labels for %

7. Avoid 3D

8. Keep it Simple

General Rules for Pie ChartsVisualization and Data Presentation

Show part-to-whole relationship (in lieu of Pie Charts)

100% Stacked Bar Chart

Source: The Wall Street Journal

=110%

Source:

American Collectors

Association

Girl Scout Cookie Sales

Source: www.wired.com/magazine/2011/08/st_datagirlscoutcookies

Photo: Celine Grouard“Save the Pies for Dessert”- Stephen Few

Pie Chart of Japan

Japan

Structure of Ass

Cheeks

Crack

Plumbers

Cheeks

Crack

Typical Structure of Ass

Redesigned Using a Sankey Diagram

A Pie Chart Redesign

Donut Charts

Avoid Donut Charts!

Source: P&G Annual Report 2012

http://annualreport.pg.com/annualreport2012/files/PG_2012_AnnualReport.pdf

• Worse than pie charts• What’s the order? And use of color?

Very Good Visualization

Source:

The Procter & Gamble Company Analyst Meeting

11/15/2013

• Target line• Time Series• Great

Message• Good use of

color

Source: P&G Annual Report 2012

http://annualreport.pg.com/annualreport2012/files/PG_2012_AnnualReport.pdf

• Time series on X-Axis• Use a Line Chart• Gradient color

• Hard to read• Compare 2012

Brazil vs. China• 23% label vs. 17%

• Country shapes• Russia looks like a

shark

• Beautiful Design Elements• Very Clean and Concise• Great Message• Good use of color

How many charts can you name?

Source: http://tinyurl.com/DVperiodictable

Available Visualization tools

Bar Chart - category comparison (with target line)

Line Chart - time series data

Flow Chart – process flow (also Swimlane diagram)

Bullet Graph – actual to target

Dot Plot or Strip Plot

Sparklines

Histogram

100% Stacked Bar Chart (with caution)

Scatter Plot – relationship/correlation

Box Plot – grouping with summaries

Area Chart (with caution)

Control Charts

What’s wrong with this chart?

#AskJPM

#AskJPM

Setting the Stage:

• JP Morgan suffered severe reputational damage from 2008

financial crisis

“When your company spends more money on legal fees and fines

than actual payroll, it's fair to say it's been a rough year.”

- Carreen Winters, Head of Corporate Practice, US Public

Relations Firm MWW

“JPM’s marketing wizards decided to set up a Q&A on Twitter with

superstar banker Jimmy Lee at the same time the bank was being

hit with a $13 billion fine for its transgressions during the financial

crisis. ”

- Paul Argenti, Professor of Corporate Communications, Tuck

School of Business at Dartmouth

#AskJPM

Over 45,000 Tweets in 48 hours

#AskJPM #AskJPM

Data sourceUgly data requiring extensive text cleansing.

“@WaLLzOfGlOrY: Chase is the worst bank ever―Ã- ½Ã±ˆÃ ½Ã±ˆÃ ½Ã±ˆ naw just your account... My shit A-1 à½Ã±•Ã ½Ã±Œ

I put a thousand in my bank account last night. I just looked and it says I have $147 à½Ã±• Don't à½Ã±• play à½Ã±• à½Ã±• with me chaseà½Ã±•Ã ½Ã±•Ã ½Ã±•Ã- ½Ã±•Ã ½Ã±•Ã ½Ã±• don't play.

Not in Bmore “@Quiet_Nature: We do RT @NaomiDimpleS: Setting up an account at M&T bank thanks to Maryland not having Chase banks.―

A Simple Scoring Model Right skewed due to the industry we are studying.

“Lost Luggage” Problem• People don’t Tweet positive sentiment about the

banks (similar to lost luggage)• Dataset is skewed – much more negative• Therefore hard to predict positive sentiment

Scatter Plot with Box Plot Axis

Dot PlotsMeasuring Position Along a Common Axis

“Killing the paired bar chart” by Jon Schwabish

Dot PlotsMeasuring Position Along a Common Axis

“Killing the paired bar chart” by Jon Schwabish

http://policyviz.com/killing-the-paired-bar-chart/

Dot PlotsMeasuring Position Along a Common Axis

“Killing the paired bar chart” by Andy Cotgreave

http://gravyanecdote.com/uncategorized/killing-the-paired-bar-chart/

Dot PlotsMeasuring Position Along a Common Axis

“Killing the paired bar chart” by Andy Cotgreave

http://gravyanecdote.com/uncategorized/killing-the-paired-bar-chart/

Example RedesignBy Cole Nussbaumer

www.StorytellingwithData.com

Example RedesignBy Cole Nussbaumer

www.StorytellingwithData.com

Note: Cole changed the scale

A Redesign of her RedesignHard to distinguish between competitors (color)

A Redesign of her RedesignWho’s the best? Who’s the worst?

A Redesign of her Redesign A Redesign of her Redesign

A Redesign of her Redesign A Redesign of her Redesign

Visualization and Data Presentation

Poor Choices:

• Wrong Chart Type for the data

• 3D chart

• Use of gradient and shadows

• Rotated Text

• Hard to Read

• Over use of gridlines

• Over use of axis and data labels

• Bad Color Choices

This material is proprietary to Unifund Group Debt Investors, LLC

(Unifund). It may not be replicated or transmitted in whole or part

without express consent of Unifund.

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This material is proprietary to Unifund Group Debt Investors, LLC (Unifund). It may not

be replicated or transmitted in whole or part without express consent of Unifund.

Visualization and Data Presentation

Poor Choice:

Example from iDashboards.com

Visualization and Data Presentation

Poor Choice:

Example from iDashboards.com

Visualization and Data Presentation

Poor Choice:

Visualization and Data Presentation

Even a bad 3D Pie Chart is better:

Visualization and Data Presentation

Better Choice:

Visualization and Data Presentation

Best Approach:

Visualization and Data Presentation

Acceptable use of the Pyramid:

Maslow’s Hierarchy of Needs

Visualization and Data Presentation

Poor Choices:

• Avoid Pyramids, Funnels and Cones

• Cluttered Dashboard

– Too Much Information (Crammed on One Page)

– Lots of Scroll

• Over use of Graphs

• Gauges

• Flashing Cells

• Wrong Message or No Message at all

The Data Visualization Experts

Visualization and Data Presentation

Best Practices:

• Books on Data Visualization

– Jacques Bertin

• Semiology of Graphics

– Edward Tufte

• The Visual Display of Quantitative Information

• Envisioning Information

– Stephen Few

• Information Dashboard Design

• Show Me the Numbers

• Now You See it

20th Century

Jacques Bertin(1918-2010)

• French cartographer and theorist

• Author of many scientific maps, articles, and other papers on semiology, the study of signs, and how we process visual information

• 1967 – Published Sémiologie Graphique(Semiology of Graphics), asserting that our visual perception follows rules that can be followed

Images used under the Wikipedia Creative Commons license. http://www.wikipedia.com

20th Century

John Tukey(1915-2000)

• American statistician

• Introduced the box plot in Exploratory Data Analysis, published in 1977

• Exploratory Data Analysis (EDA) emphasized presentation of the main characteristics of a data set in a visual, easy to understand form, without using a statistical model or hypothesis10

Images used under the Wikipedia Creative Commons license. http://www.wikipedia.com

20th Century

Visualization techniques used in EDA include:

• Box plot

• Histogram

• Pareto chart

• Scatter plot

Images used under the Wikipedia Creative Commons license. http://www.wikipedia.com

Tukey’s advocacy for EDA encouraged the development of software for statistical computing like S, which inspired S-Plus and R.10

Sample box plot.

Sample histogram.

Sample scatter plot.

Contemporary Practitioners

Edward R. Tufte(b. 1942)

• American statistician, sculptor, and Professor Emeritus of Political Science, Statistics, and Computer Science, Yale University

• Widely recognized expert in the fields of information design and visual literacy11

• Credited as a pioneer in teaching the fundamental skills required for visual communication3

Edward Tufte photo from http://www.edwardtufte.com/bboard/images/0003mW-10280.jpg

Contemporary Practitioners

Edward R. Tufte(b. 1942)

Published The Visual Display of Quantitative Information (1983)

• Shows examples of both “glories” and “lapses” in presentation

• Provides “a language for discussing graphics and a practical theory of data graphics”

Tufte also invented sparklines to show trends and variations along a particular

measurement.Example of Tufte’s sparklines,as implemented on Google Analytics.

Visualization and Data Presentation

Visualization Expert:

• Edward Tufte

– Remove Chart Junk (unnecessary or confusing visual elements in charts and graphs)

– Data-Ink Ratio (The non-erasable core of a graphic)

• Data-Ink vs. Total Ink

• Tufte’s Five Laws of Data-Ink:

1. Above all else show the data.

2. Maximize the data-ink ratio

3. Erase non-data-ink.

4. Erase redundant data-ink.

5. Revise and edit.

Visualization and Data Presentation

Tufte Style Chart:

0

2

4

6

8

10

Jan Feb Mar Apr May Jun Jul

Visualization and Data Presentation

In this case a bar chart may actually be better:

Visualization and Data Presentation

Tufte Style Scatterplot:

Contemporary Practitioners

William S. Cleveland

• Professor of Statistics and Courtesy Professor of Computer Science at Purdue University; previously worked at Bell Labs

• Authored over 100 papers/publications including Visualizing Data (1993) andThe Elements of Graphing Data(1994), to enhance awareness and provide examples of effective data presentation

• Initial developer of trellis charts, which make visualization possible in data sets with multiple variables

William S. Cleveland photo from http://www.stat.purdue.edu/~wsc/

Trellis Chart Example

Graphic from http://peltiertech.com/WordPress/trellis-plot-alternative-to-stacked-bar-chart/

Contemporary Practitioners

Stephen FewProlific writer and author with a focus on designing simple information displays that are effective and communicative.

Books include:

• Show Me The Numbers (2004)

• Now You See It (2009)

• Information Dashboard Design, 2nd ed. (2013)

Several of Few’s studiesand examples will be usedin this class.

Few’s biography retrieved from http://www.perceptualedge.com/about.php www.BigBookofDashboards.com

Visualization and Data Presentation

Other Guidelines:

• Gridlines – minimize axis units and mute them

• Remove chart borders

• Extra Labels

• Axis Scale Format

• Text Alignment

– Avoid rotated text

• Tufte – Minimalists

• Few - Fundamentalist

Make sure to connect online and stay in touch:

Follow on Twitter:@HighVizAbility

Connect with us on LinkedIn:www.linkedin.com/in/jeffreyshaffer/

Websites:www.dataplusscience.com/workshop.htmlwww.dataplusscience.com/http://makingdatameaningful.com/

Facebook:https://www.facebook.com/DataPlusScience

Email:JeffreyShaffer@gmail.com