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Data Visualization
Data 101
May 10th, 2016
Data 101. David Newbury — @workergnome 1
David NewburyProfessional nerd artist
@workergnome
www.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?
Data 101. David Newbury — @workergnome 6
Which is biggest?
Data 101. David Newbury — @workergnome 7
Why?
Data 101. David Newbury — @workergnome 8
(Brief)
History of
Data Visualization
Data 101. David Newbury — @workergnome 9
Tabula Peutingeriana, 5th century CE
Data 101. David Newbury — @workergnome 10
Data 101. David Newbury — @workergnome 11
Rene Descartes, 1600s
Data 101. David Newbury — @workergnome 12
Joseph Priestly, New Chart of History (1769)
Data 101. David Newbury — @workergnome 13
William Playfair, (1786 & 1801)
Data 101. David Newbury — @workergnome 14
Data 101. David Newbury — @workergnome 15
Data 101. David Newbury — @workergnome 16
John Snow, London Cholera Map (1854)
Data 101. David Newbury — @workergnome 17
Cholera Map
Data 101. David Newbury — @workergnome 18
Florence Nightingale, War Deaths (1855)
Data 101. David Newbury — @workergnome 19
Charles Minard, March on Moscow (1862)
Data 101. David Newbury — @workergnome 20
More recent history.
Data 101. David Newbury — @workergnome 21
Data 101. David Newbury — @workergnome 22
Edward Tufte
The Visual Display of
Quantitative Information.
Data 101. David Newbury — @workergnome 23
Data 101. David Newbury — @workergnome 24
New York Times
Data 101. David Newbury — @workergnome 25
Data 101. David Newbury — @workergnome 26
(tiny)
Theory
of Visualization
Data 101. David Newbury — @workergnome 27
Dataviz is constructed reality.
You are telling a story, not (just) stating facts.
Data 101. David Newbury — @workergnome 28
data art
as opposed to
data visualization
as opposed to
statistical graphics
Data 101. David Newbury — @workergnome 29
Statistical
Graphics
How 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
Data 101. David Newbury — @workergnome 31
Two Uses1). help people grasp things outside their reach
Data 101. David Newbury — @workergnome 32
Two Uses1). help people grasp things outside their reach
2.) tell stories
Data 101. David Newbury — @workergnome 33
explanatory visualization work
as opposed to
exploratory visualizations
Data 101. David Newbury — @workergnome 34
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?
Data 101. David Newbury — @workergnome 35
Data 101. David Newbury — @workergnome 36
Data 101. David Newbury — @workergnome 37
Data 101. David Newbury — @workergnome 38
Data 101. David Newbury — @workergnome 39
(Nerdy)
Overview of Concepts
Data 101. David Newbury — @workergnome 40
What can you visualise?
Data 101. David Newbury — @workergnome 41
Potential Subjects.
subways, sheep, the solar system,
shoes, sleep, skyline,
snow, supermarket, sausages,
school,the sea, spiders,
staircases, syrup, soap,
sawmills, stereos...
Data 101. David Newbury — @workergnome 42
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 Scope
are about choosing
what to focus on.
Data 101. David Newbury — @workergnome 44
Scope
Out of the infinite stories about any subject,
which parts are you going to choose?
Data 101. David Newbury — @workergnome 45
Possible Scopes
All trains in a day
All the rides that I've been on this year
My train this morning
All of the stops in the city
Each line
Every train stop in the past 50 years
Data 101. David Newbury — @workergnome 46
Dimension
Which bits of information about a subject
are you going to focus on?
Data 101. David Newbury — @workergnome 47
Possible Dimensions
number of cars
duration of ride
date of a ride
different lines
number of stops
cost per ride
number of stops per day
time between stops
Data 101. David Newbury — @workergnome 48
What does your
data look like?
Data 101. David Newbury — @workergnome 49
Types of Data
Dates
Numbers
Geo Coordinate
Strings
Categories
Data 101. David Newbury — @workergnome 50
Types of Data
number of cars - Numeric
duration of ride - Numeric
date of a ride - Date
different lines - Category
number of stops - Numeric
cost per ride - Category
number of stops per day - Numeric
time between stops - Numeric
Data 101. David Newbury — @workergnome 51
Two (related ides):
Categories & measures
Data 101. David Newbury — @workergnome 52
Categories are Discrete Things
Measures are for Counting
Data 101. David Newbury — @workergnome 53
number of cars - Measure
duration of ride - Measure
date of a ride - Measure
different lines - Categories
number of stops - Measure
cost per ride - Categories
number of stops per day - Measure
time between stops - Measure
cleanliness - Categories
Data 101. David Newbury — @workergnome 54
A hidden dimension:
David, Daniel, Dawn, Danique
Data 101. David Newbury — @workergnome 55
A hidden dimension:
David (1), Daniel (2), Dawn (3), Danique (4)
Position of the item in the group.
Data 101. David Newbury — @workergnome 56
(Fake)
Data Exploration
Data 101. David Newbury — @workergnome 57
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.
Data 101. David Newbury — @workergnome 59
Now
What?Data 101. David Newbury — @workergnome 60
We need to map our data
from a domain
to a range.
Data 101. David Newbury — @workergnome 61
Domain
number of cars - 1...8
duration of ride - 30 sec...2 hours
date of a ride - - 24ft...200ft
different lines - Red line, Blue line, Green line, Silver
Line, Yellow Line
number of stops - **2..20
cost 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
Data 101. David Newbury — @workergnome 63
Data
3, 7, 10, 6, 2
Position of the item in the group.
Domain
[0-10]
[1-5]
Range
X: 400px
Y: 800px
Mapping
X: item position
Y: numeric value
Data 101. David Newbury — @workergnome 64
Data
3, 7, 10, 6, 2
Position of the item in the group.
Area
Data 101. David Newbury — @workergnome 65
Data
3, 7, 10, 6, 2
Position of the item in the group.
Color
Data 101. David Newbury — @workergnome 66
Data
3, 7, 10, 6, 2
Position of the item in the group.
Multiples
Dimensions
Data 101. David Newbury — @workergnome 67
Data
val1: 3, 7, 10, 6, 2
val2: 5, 8, 1, 8, 3
val3: Cat, Dog, Cat, Cat, Dog
Position of the item in the group.
Mapping
X: item position
Y: val1
Size: val2
Color: val3
Data 101. David Newbury — @workergnome 68
Dimensions beyond X and Y.
Color
Size
Shape
Labels
Patterns
Icons
Anything Else You Can Imagine
Data 101. David Newbury — @workergnome 69
TRY IT.
Data 101. David Newbury — @workergnome 70
Finishing
Touches
Data 101. David Newbury — @workergnome 71
Measures get Axis
Categories get Headers
Data 101. David Newbury — @workergnome 72
Labels
Data 101. David Newbury — @workergnome 73
Axis
Category Axis
Number Axis
Date Axis
Log axis
Data 101. David Newbury — @workergnome 74
Legends
Data 101. David Newbury — @workergnome 75
TRY IT.
Data 101. David Newbury — @workergnome 76
Review
Dimensions
Scope
Domain
Range
Categories
Measures
Data 101. David Newbury — @workergnome 77
(Incomplete)
Overview of Tools
Data 101. David Newbury — @workergnome 78
Data 101. David Newbury — @workergnome 79
Data 101. David Newbury — @workergnome 80
Data 101. David Newbury — @workergnome 81
Data 101. David Newbury — @workergnome 82
Data 101. David Newbury — @workergnome 83
Data 101. David Newbury — @workergnome 84
Thank You.
Data 101. David Newbury — @workergnome 85

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