I N T R O TO DATA V I S UA L I Z AT I O N Andrew Heiss, PhD - PowerPoint PPT Presentation

I N T R O TO DATA V I S UA L I Z AT I O N Andrew Heiss, PhD Brigham Young University September 19, 2018 @andrewheiss

P L A N F O R T O D A Y Why visualize data? Types of visualizations Aesthetics and design How do I do all this?

W H Y V I S U A L I Z E DATA ?

P R O V I N G T R U T H Theories are only stories until you have data.

A L L W E N E E D I S R A W D A T A No correlation!

J K L O L

D A T A I S N O T E N O U G H Theories are only stories until you have data. Data alone cannot tell stories or prove theories.

H U M A N S L O V E P A T T E R N S

W H Y V I S U A L I Z E D A T A ? Graphs let us see patterns in our data Sometimes graphs alone are sufficient for telling a story and drawing inference from data

P L O T S > R A W T A B L E S

P L O T S > R A W T A B L E S

P L O T S > R A W T A B L E S

P L O T S > R A W T A B L E S

P L O T S > R A W T A B L E S

! T H I S I S D I F F I C U LT ! Incompetence Deceit Complexity

W H AT M A K E S A G O O D V I S UA L I Z AT I O N ?

T H E W A R O F 1 8 1 2

T H E W A R O F 1 8 1 2 0 October 1 November 1 December 1 -5 -10 -15 ºC -20 -25 -30 -35

T H E W A R O F 1 8 1 2 Napoleon’s Grande Armée Died Survived

C H A R A C T E R I S T I C S O F G R A P H I C A L E X C E L L E N C E 1. “... the well-designed presentation of interesting data—a matter of substance, statistics, and design.” 2. Complex ideas communicated with clarity, precision, and efficiency. 3. That which gives the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space. 4. Nearly always multivariate. 5. Requires telling the truth about the data.

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T Y P E S O F V I S U A L I Z AT I O N S

T W O G E N E R A L T Y P E S Explanatory Exploratory Academic-ish Publishable Quick scatterplots, Consumable by the general histograms, other charts to public; Vox, NYT, Washington help understand your data Post, FiveThirtyEight, etc .

E X P L O R A T O R Y D A T A A N A LY S I S Find analytical insight in data (even causal inference ! )

E X P L A N A T O R Y D A T A A N A LY S I S Annotate and tell a story

W H I C H C H A R T T Y P E D O I U S E ?

A E S T H E T I C S A N D D E S I G N

F O U R C O R E D E S I G N P R I N C I P L E S Contrast Repetition Proximity Alignment

C O N T R A S T “If two items are not exactly the same, make them different. Really different. ” Don’t be a wimp.

T Y P O G R A P H I C C O N T R A S T Serif Lorem ipsum dolor sit amet Sans Serif Lo Lorem em ip ipsu sum do dolor s r sit am amet et Slab Serif Lorem ipsum dolor sit amet Lor orem ip ipsu sum dol olor or s sit ame amet Script Lo Lorem ip ipsu sum do dolor r sit sit am amet Decorative

C O L O R C O N T R A S T https://color.adobe.com/ http://colorbrewer2.org/ Scientific Colour-Maps viridis https://github.com/thomasp85/scico

R E P E T I T I O N “Repeat some aspect of the design throughout the entire piece.”

A L I G N M E N T “Every item should have a visual connection with something else on the page.”

P R O X I M I T Y “Group related items together.”

C R A P Contrast Repetition Alignment Proximity

C R A P A N D D A T A V I Z

H O W D O I D O A L L T H I S ?

S O F T W A R E Flexibility and power Barrier to entry (amount of coding required)

I N T R O TO DATA V I S UA L I Z AT I O N Andrew Heiss, PhD Brigham Young University September 19, 2018 @andrewheiss