Block Builder Links - GitHub Pages · Set Theory Bijection (one visual attribute, one data...
Transcript of Block Builder Links - GitHub Pages · Set Theory Bijection (one visual attribute, one data...
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Tableau License for Students
GitHub Student Pack
Block Builder
data
Administrative
a0, a1 due
1X Y
2X Y
3X Y
4X Y
MeanVariance
Correlation
Anscombe’s Quartet: Raw Data
1X Y
2X Y
3X Y
4X Y
MeanVariance
Correlation
Anscombe’s Quartet: Raw Data
1X Y
2X Y
3X Y
4X Y
MeanVariance
Correlation
Anscombe’s Quartet: Raw Data
1X Y
2X Y
3X Y
4X Y
MeanVariance
Correlation
Anscombe’s Quartet: Raw Data
1X Y
2X Y
3X Y
4X Y
MeanVariance
Correlation
Anscombe’s Quartet: Raw Data
Tableau
typical vis design
Key question: how to map data to visuals?
Set Theory
Bijection (one visual attribute, one data attribute)
Surjection (multiple visual attribute to one data attribute)
Injection (One to one mapping, but not all data elements are mapped)
Data Vars > Visual Vars ?
What happens when
Visual Vars > Data Vars ?
What happens when
Data Attributes
nominal
Non-ordered and non-numeric
AKA categorical data
[‘apple’, ‘pear’, ‘banana’]
ordinal
Ordered, not necessarily numeric
[1st, 3rd, 5th, 7th]
[‘G’, ‘PG’, ‘PG-13’, ‘R’] PG -> R
1st -> 3rd
ordinal
Ordered, not necessarily numeric
[1st, 3rd, 5th, 7th]
[‘G’, ‘PG’, ‘PG-13’, ‘R’] PG -> R
1st -> 3rd
length is not meaningful
interval
Ordered, numeric, not ratio-able
[‘Jan 12’, ‘Jan 20’]
[’17°’, ‘44°’, ‘23°’, ‘30°’]
Jan 12/Jan 20 = ???
23° / 30° = ???
ratio
Ordered, numeric, ratio-able (has a “true” 0)
[1, 3, 5, 7]
[ 5’8”, 6’1”, 5’4” ]
Ratio / Interval (Q)
Ordinal
Nominal
Q -> O[0-100] —> [A, B, C, D, F]
transforms
Ratio / Interval (Q)
Ordinal
Nominal
Q -> O[0-100] —> [A, B, C, D, F]
O -> N[A, B, C, D, F] -> [B, C, F, D, A]
transforms
Ratio / Interval (Q)
Ordinal
Nominal
Q -> O[0-100] —> [A, B, C, D, F]
O -> N[A, B, C, D, F] -> [B, C, F, D, A]
N -> O[“Jack”, “Alex” ] -> [“Alex”, “Jack”]
transforms
transforms
Ratio / Interval (Q)
Ordinal
Nominal
Q -> O[0-100] —> [A, B, C, D, F]
O -> N[A, B, C, D, F] -> [B, C, F, D, A]
N -> O[“Jack”, “Alex” ] -> [“Alex”, “Jack”]
O -> Q“Alex”+”Jack” -> 7 ???
Interval
OrdinalNominal
operations
== != > < <= >=
+ -Ratio
/ *
Interval
OrdinalNominal
operations
== != > < <= >=
+ -Ratio
/ *
consider a distance function…
Attribute TypesCategorical
OrderedOrdinal
Quantitative
structure
Tables
Attributes (columns)
Items (rows)
Cell containing value
Networks
Link
Node (item)
Trees
Fields (Continuous)
Attributes (columns)
Value in cell
Cell
Multidimensional Table
Value in cell
Grid of positions
Geometry (Spatial)
Position
Dataset Types
Tables
Attributes (columns)
Items (rows)
Cell containing value
Networks
Link
Node (item)
Trees
Fields (Continuous)
Attributes (columns)
Value in cell
Cell
Multidimensional Table
Value in cell
Grid of positions
Geometry (Spatial)
Position
Dataset Types
Tables
Attributes (columns)
Items (rows)
Cell containing value
Networks
Link
Node (item)
Trees
Fields (Continuous)
Attributes (columns)
Value in cell
Cell
Multidimensional Table
Value in cell
Grid of positions
Geometry (Spatial)
Position
Dataset Types
time
record #
Tables
Attributes (columns)
Items (rows)
Cell containing value
Networks
Link
Node (item)
Trees
Fields (Continuous)
Attributes (columns)
Value in cell
Cell
Multidimensional Table
Value in cell
Grid of positions
Geometry (Spatial)
Position
Dataset Types
sample
record #
Why?
How?
What?
Datasets
What?Attributes
Dataset Types
Data Types
Data and Dataset Types
Dataset Availability
Static Dynamic
Tables
Attributes (columns)
Items (rows)
Cell containing value
Networks
Link
Node (item)
Trees
Fields (Continuous)
Geometry (Spatial)
Attributes (columns)
Value in cell
Cell
Multidimensional Table
Value in cell
Items Attributes Links Positions Grids
Attribute Types
Ordering Direction
Categorical
OrderedOrdinal
Quantitative
Sequential
Diverging
Cyclic
Tables Networks & Trees
Fields Geometry Clusters, Sets, Lists
Items
Attributes
Items (nodes)
Links
Attributes
Grids
Positions
Attributes
Items
Positions
Items
Grid of positions
Position
Tables
Attributes (columns)
Items (rows)
Cell containing value
Networks
Link
Node (item)
Trees
Fields (Continuous)
Attributes (columns)
Value in cell
Cell
Multidimensional Table
Value in cell
Grid of positions
Geometry (Spatial)
Position
Dataset Types
data shapes the algorithm space
data shapes the visual space
Further ReadingStevens, Stanley Smith. "On the theory of scales of measurement." (1946).
Visual Attributes
Bertin, Semiologie Graphique, ‘67
(pay attention to your how you judge these differences)
Position (Common Scale)
-scatterplots -bar charts -line charts -???
Position (Un-aligned Scale)
-stacked bars -stacked area -???
Use design elements to compensate!
Angle
Volume
Accurate encoding does not ensure accurate perception!
Luminance and Saturation— really the same?
Identity
Spatial Region
Hue bad for magnitude:
Hue is great for identity:
Hue bad for magnitude:
Shape
Demiralp et al., 2014
Shape
Demiralp et al., 2014
Motion
(huge attention grabber, use with caution)
Data Vars > Visual Vars ?
What happens when
Visual Vars > Data Vars ?
What happens when
Lab: Data Deconstruction
A2:Visualization, 10 ways