data 101: introduction to data visualization

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Data Visualization Data 101 May 10th, 2016 Data 101. David Newbury — @workergnome 1

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Data VisualizationData 101May 10th, 2016

Data 101. David Newbury — @workergnome 1

David NewburyProfessional nerd artist

@workergnomewww.workergnome.com

Data 101. David Newbury — @workergnome 2

What We're Doing Today:

—(Brief) History of Data Visualization—(Tiny) Theory of Visualization—(Nerdy) Overview of Concepts—(Fake) Data Exploration—(Incomplete) Overview of Tools

Data 101. David Newbury — @workergnome 3

What We're not Doing Today:

—Writing Code—Thinking about Mapping—Worrying about Data Provenance

Data 101. David Newbury — @workergnome 4

Which is biggest?

15012, 8271, 30193, 1189, 9913, 16000, 92481, 49801, 100407, 2910, 3809, 8018, 61528, 18083, 38691, 1800

Data 101. David Newbury — @workergnome 5

Which is biggest?

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Which is biggest?

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Why?Data 101. David Newbury — @workergnome 8

(Brief)History ofData Visualization

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Tabula Peutingeriana, 5th century CE

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Rene Descartes, 1600s

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Joseph Priestly, New Chart of History (1769)

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William Playfair, (1786 & 1801)

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John Snow, London Cholera Map (1854)

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Cholera Map

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Florence Nightingale, War Deaths (1855)

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Charles Minard, March on Moscow (1862)

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More recent history.

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Edward Tufte

The Visual Display of Quantitative Information.

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New York Times

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(tiny)

Theory of Visualization

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Dataviz is constructed reality.You are telling a story, not (just) stating facts.

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data artas opposed to

data visualization

as opposed to

statistical graphicsData 101. David Newbury — @workergnome 29

StatisticalGraphicsHow do I create Statistical Graphs in SAS 9.1.3 without Proc Gplot. UCLA: Statistical Consulting Group.http://www.ats.ucla.edu/stat/sas/notes2/Data 101. David Newbury — @workergnome 30

Data Art

Dear Data Giorgia Lupi & Stefanie Posavec.http://www.dear-data.com

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Two Uses1). help people grasp things outside their reach

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Two Uses1). help people grasp things outside their reach

2.) tell stories

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explanatory visualization work

as opposed to

exploratory visualizations

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Dataviz is constructed reality.Do you care how true your story is?

Do you care how accurate your story is?

Are you trying to teach, entertain, or convince?

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(Nerdy)Overview of Concepts

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What can you visualise?

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Potential Subjects.

subways, sheep, the solar system,shoes, sleep, skyline,snow, supermarket, sausages,school,the sea, spiders,staircases, syrup, soap,sawmills, stereos...

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Potential Subjects.

subways, sheep, the solar system,shoes, sleep, skyline,snow, supermarket, sausages,school,the sea, spiders,staircases, syrup, soap,sawmills, stereos...

...and other things that begin with S.

Data 101. David Newbury — @workergnome 43

Dimension and Scopeare about choosing what to focus on.

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Scope

Out of the infinite stories about any subject, which parts are you going to choose?

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Possible Scopes

All trains in a dayAll the rides that I've been on this yearMy train this morningAll of the stops in the cityEach lineEvery train stop in the past 50 years

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Dimension

Which bits of information about a subjectare you going to focus on?

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Possible Dimensions

number of carsduration of ridedate of a ridedifferent linesnumber of stopscost per ridenumber of stops per daytime between stopsData 101. David Newbury — @workergnome 48

What does yourdata look like?

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Types of Data

DatesNumbersGeo CoordinateStringsCategories

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Types of Data

number of cars - Numericduration of ride - Numericdate of a ride - Datedifferent lines - Categorynumber of stops - Numericcost per ride - Categorynumber of stops per day - Numerictime between stops - NumericData 101. David Newbury — @workergnome 51

Two (related ides):

Categories & measures

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Categories are Discrete Things

Measures are for Counting

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number of cars - Measureduration of ride - Measuredate of a ride - Measuredifferent lines - Categoriesnumber of stops - Measurecost per ride - Categoriesnumber of stops per day - Measuretime between stops - Measurecleanliness - Categories

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A hidden dimension:

David, Daniel, Dawn, Danique

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A hidden dimension:

David (1), Daniel (2), Dawn (3), Danique (4)

Position of the item in the group.

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(Fake)Data Exploration

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TRY IT.Data 101. David Newbury — @workergnome 58

Choose one.

subways, sheep, the solar system,shoes, sleep, skyline,snow, supermarket, sausages,school,the sea, spiders,staircases, syrup, soap,sawmills, stereos...

...and other things that begin with S.

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NowWhat?

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We need to map our datafrom a domainto a range.

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Domain

number of cars - 1...8duration of ride - 30 sec...2 hoursdate of a ride - - 24ft...200ftdifferent lines - Red line, Blue line, Green line, Silver Line, Yellow Linenumber of stops - **2..20cost per ride - "$2.50, $1.75, $3.00, $0.00"number of stops per day - ??...???Data 101. David Newbury — @workergnome 62

Range

Domain is the possible input values

Range is the possible output values

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Data3, 7, 10, 6, 2Position of the item in the group.

Domain[0-10][1-5]

RangeX: 400px Y: 800px

MappingX: item position Y: numeric value Data 101. David Newbury — @workergnome 64

Data3, 7, 10, 6, 2Position of the item in the group.

AreaData 101. David Newbury — @workergnome 65

Data3, 7, 10, 6, 2Position of the item in the group.

ColorData 101. David Newbury — @workergnome 66

Data3, 7, 10, 6, 2Position of the item in the group.

MultiplesDimensions

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Dataval1: 3, 7, 10, 6, 2val2: 5, 8, 1, 8, 3val3: Cat, Dog, Cat, Cat, DogPosition of the item in the group.

MappingX: item position Y: val1 Size: val2 Color: val3

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Dimensions beyond X and Y.

ColorSizeShapeLabelsPatternsIconsAnything Else You Can Imagine

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TRY IT.Data 101. David Newbury — @workergnome 70

FinishingTouches

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Measures get AxisCategories get Headers

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Labels

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Axis

Category AxisNumber AxisDate AxisLog axis

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Legends

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TRY IT.Data 101. David Newbury — @workergnome 76

Review

DimensionsScope

DomainRange

CategoriesMeasures

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(Incomplete)

Overview of Tools

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Thank You.

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