08 visualisation seminar ver0.2

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9GoldenRulesofDataVisualisa2on

Dr.BrianMacNamee

Retinal Variables

The Semiology of Graphics: Diagrams, Networks, Maps Jacques Bertin (1967)

Orientation

Color

Shape

Texture

Value

Size

Matplotlib Visualisation Gallery http://matplotlib.org/gallery.html

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NASA/Goddard Space Flight Center and the Advanced Visualization Laboratory at the National Center for Supercomputing Applications, B. Robertson, L. Hernquist

Peopleareverygoodatpa9erndetec2on1

Focusonthetaskathand2

Understandvisualpercep2on3

Priori2zefunc2onoverform4

Showallthedataandonlythedata5

Thinkcarefullyaboutcolour6

Thinkaboutthestoryyourdataistelling7

Knowyouraudience8

Trytocombinechartsandnumbers9

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PeopleAreVeryGoodatPa9ern

Detec2on

1

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WhichTreeIsBiggestOnThisSlide?

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A

B

C

D



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21/04/1612Show Me The Numbers, Stephen Few

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21/04/1614Show Me The Numbers, Stephen Few

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FocusOnTheTaskAtHand

2

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http://www.youtube.com/watch?v=vJG698U2Mvo

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“If you're going underground, why

do you need bother about geography? … Connections are

the thing”

Harry Beck

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LondonUndergroundMap

Data Exploration

versus

Data Presentation

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UnderstandVisualPercep2on

3

http://www.statista.com/chart/3199/the-most-successful-teams-in-the-six-nations/

1,098

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France' England' Wales' Ireland' Italy' Scotland'

1,098

Points Scored

2,061&1,899& 1,833&

1,688&

1,183& 1,098&

England& France& Ireland& Wales& Italy& Scotland&

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Datavisualisa9onisaboutmappingdatadimensionstovisualencodings

Team Points

England 2,061

France 1,899

Ireland 1,833

Wales 1,688

Italy 1,183

Scotland 1,098

England'

France'

Ireland'

Wales'

Italy'

Scotland'

France'

Wales'

Scotland'

England'

Ireland'

Italy'

2,061&1,899& 1,833&

1,688&

1,183& 1,098&

England& France& Ireland& Wales& Italy& Scotland&

Jacques Bertin (1918 - 2010)

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Retinal Variables

The Semiology of Graphics: Diagrams, Networks, Maps Jacques Bertin (1967)

Orientation

Color

Shape

Texture

Value

Size

William Cleveland

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Position

Length

Angle

Area

Colour Density

Interpretation Accuracy

Pattern

WhichSegmentIsBiggest?

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21.6%

28.8%

3.6%

29.7%

15.3%

1.0%


Priori2zeFunc2onOverForm

4

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David McCandless

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WhatcolourisassociatedwithfamilyinAsianculture?

Stephen Few

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WhatcolourisassociatedwithfamilyinAsianculture?

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“Be clear first and clever second. If you have to throw one of those out,

throw out clever.”

Jason Fried

“Be clear first and clever second. If you have to throw one of those out,

throw out clever.”

Jason Fried

Or: If your solution is not based on

bar charts and line charts, think carefully!

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ShowAllTheDataAndOnlyTheData

5

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Edward Tufte

data-ink ratio = data-ink

total ink used to print chart

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-

100,000

200,000

300,000

400,000

500,000

600,000

Independents FineGael FineFail SinnFein Labour

VotesbyPoli2calParty2014LocalElec2on

Independents

FineGael

FineFail

SinnFein

Labour

Removethecolourfromthebackground

-

100,000

200,000

300,000

400,000

500,000

600,000



Independents

FineGael

FineFail

SinnFein

Labour

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Removethecolourfromthechartbackground

-

100,000

200,000

300,000

400,000

500,000

600,000



Independents

FineGael

FineFail

SinnFein

Labour

Removethelegend

-

100,000

200,000

300,000

400,000

500,000

600,000



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Changetoabetter monochrome colour palette

-

100,000

200,000

300,000

400,000

500,000

600,000



Removethegridlines

-

100,000

200,000

300,000

400,000

500,000

600,000



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Removethever2calaxisbutaddindatalabels

479,267

404,173427,644

256,314

121,898



Removethechartborder

479,267

404,173427,644

256,314

121,898



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479,267

404,173427,644

256,314

121,898



Wehaveimprovedthedata-ink ratio and in doing so have vastly improved our visualisation

479,267

404,173 427,644

256,314

121,898



-100,000200,000300,000400,000500,000600,000


Independents

FineGael

FineFail

SinnFein

Labour

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* Andrew Freedman, NOAA: 2012 Hottest & 2nd-Most Extreme Year On Record, Climate Centralhttp://www.climatecentral.org/news/noaa-2012-was-warmest-and-second-most-extreme-year-on-record-15436

* Sophie J. Engle, How to Lie with Data Visualization (in R) http://sjengle.cs.usfca.edu/talks/how-to-lie-with-data-visualization-in-r

* Sophie J. Engle, How to Lie with Data Visualization (in R) http://sjengle.cs.usfca.edu/talks/how-to-lie-with-data-visualization-in-r

http://www.climatecentral.org/news/noaa-2012-was-warmest-and-second-most-extreme-year-on-record-15436

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ThinkCarefullyAboutColour

6

For more great illusion examples take a look at: http://web.mit.edu/persci/gaz/

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Available here: http://www.lottolab.org/Visual%20Demos/Demo%2015.html

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Cynthia Brewer

“[The RGB cube] is not the least bit perceptually scaled. In some parts of the cube a tiny step gives you a huge perceptual difference. In other parts it all looks the same.”

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Edward Tufte

“... avoiding catastrophe becomes the first principle in bringing color to information: above all, do no harm.”

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When using colour with numeric data use

monochromatic palettes

When using colour with categorical data use colour blindness safe palletes

Use colour palettes from ColorBrewer (www.colorbrewer2.org)

ThinkAboutTheStoryYourData

IsTelling

7

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Florence Nightingale

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Charles Joseph Minard

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Jonathan Corum

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KnowYourAudience

8W

eb T

raffi

c

Day

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26# 27# 28#

23#20#

15# 16#

Monday# Tuesday# Wednesday# Thursday# Friday# Saturday# Sunday#

Web

$Traffic$

Day$

Julie Steele

"How do the people I'm presenting the data to absorb information the best?"

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TrytoCombineChartsandNumbers

9

x1 y1 10 8.04 8 6.95

13 7.58 9 8.81

11 8.33 14 9.96 6 7.24 4 4.26

12 10.84 7 4.82 5 5.68

x2 y2 10 9.14 8 8.14

13 8.74 9 8.77

11 9.26 14 8.10 6 6.13 4 3.1

12 9.13 7 7.26 5 4.74

x3 y3 10 7.46 8 6.77

13 12.74 9 7.11

11 7.81 14 8.84 6 6.08 4 5.39

12 8.15 7 6.42 5 5.73

x4 y4 8 6.58 8 5.76 8 7.71 8 8.84 8 8.47 8 7.04 8 5.25

19 12.5 8 5.56 8 7.91 8 6.89

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x1 y1 10 8.04 8 6.95

13 7.58 9 8.81

11 8.33 14 9.96 6 7.24 4 4.26

12 10.84 7 4.82 5 5.68

x2 y2 10 9.14 8 8.14

13 8.74 9 8.77

11 9.26 14 8.10 6 6.13 4 3.1

12 9.13 7 7.26 5 4.74

x3 y3 10 7.46 8 6.77

13 12.74 9 7.11

11 7.81 14 8.84 6 6.08 4 5.39

12 8.15 7 6.42 5 5.73

x4 y4 8 6.58 8 5.76 8 7.71 8 8.84 8 8.47 8 7.04 8 5.25

19 12.5 8 5.56 8 7.91 8 6.89

Foursetsofdatawiththesamecorrela9oncoefficientof0.816

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"a computer should make both

calculations and graphs"

Frank Anscombe (1918 - 2001)

Peopleareverygoodatpa9erndetec2on1

Focusonthetaskathand2

Understandvisualpercep2on3

Priori2zefunc2onoverform4

Showallthedataandonlythedata5

Thinkcarefullyaboutcolour6

Thinkaboutthestoryyourdataistelling7

Knowyouraudience8

Trytocombinechartsandnumbers9

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Data Visualization Using Immersive Virtual Reality Tools Cioc, Alexandru; Djorgovski, S. G.; Donalek, C.; Lawler, E.; Sauer, F.; Longo, G.

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Jacques Bertin

Edward Tufte

Cynthia Brewer

Stephen Few

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Cleveland

Mackinley

David McCandless

Steele/Illinsky

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References

§  LondonUndergroundMap,HarryBeckwww.vam.ac.uk/vasta9c/microsites/1331_modernism/highlights_19.html

§  ColoursinCultures,DavidMcCandlesswww.informa9onisbeau9ful.net/visualiza9ons/colours-in-cultures/

§  OurIrresis9bleFascina9onwithAllThingsCircular,StephenFewwww.perceptualedge.com/ar9cles/visual_business_intelligence/our_fascina9on_with_all_things_circular.pdf

§  WhatAboutColorBlindness?,MaureenStonewww.stonesc.com/wordpress/2010/05/what-about-color-blindness/

§  Graphicalpercep9on:Theory,experimenta9on,andapplica9ontothedevelopmentofgraphicalmethods,WSCleveland,RMcGill,JournaloftheAmericanSta9s9calAssocia9onwww.researchgate.net/publica9on/229099907_Graphical_percep9on_Theory_experimenta9on_and_applica9on_to_the_development_of_graphical_methods

UseToolsThatMakeItEasyToDoThingsRight

9

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Jock MacKinlay

USINGVISUALENCODINGSEFFECTIVELY

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UsingVisualEncodingsEffec2vely§ Thesearesomethingsyoushouldthinkabouttohelpchoosingappropriatevisualencodings

– Usethemosteasilyinterpretedencodingforthemostimportantvariable

– Respectnaturalordering– Ensuresufficientdis9nctvalues– Choosedefaultsoverinnova9veformats– Takeaccountofreaders’context

HansRosling(Legend!)§ NowthatwehavetalkedaboutencodingstakealookatthisscreenshotfromHansRoslinganddiscusstheencodingsused

– Howmanydatadimensionsarevisuallyencoded?– Howisimportanceorderingused?

The tool and data that Rosling uses is available at: www.gapminder.org

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MakingDataCompelling

Year Temp 1895 50.54 1896 52.12 1897 51.58 1898 51.46 1899 51.10 1900 52.86 1901 51.94 1902 51.70

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Jacques Bertin

http://www.statista.com/chart/3199/the-most-successful-teams-in-the-six-nations/

08 visualisation seminar ver0.2

Science