Graphics of large datasets: visualizing a million
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer
[2006]
|
| Schriftenreihe: | Statistics and computing
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturverzeichnis Seite 251-261 |
| Beschreibung: | xiii, 271 Seiten Illustrationen, Diagramme, Karten (überwiegend farbig) |
| ISBN: | 9780387329062 0387329064 |
Internformat
MARC
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| 245 | 1 | 0 | |a Graphics of large datasets |b visualizing a million |c Antony Unwin, Martin Theus, Heike Hofmann |
| 264 | 1 | |a New York, NY |b Springer |c [2006] | |
| 264 | 4 | |c © 2006 | |
| 300 | |a xiii, 271 Seiten |b Illustrationen, Diagramme, Karten (überwiegend farbig) | ||
| 336 | |b txt |2 rdacontent | ||
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| 500 | |a Literaturverzeichnis Seite 251-261 | ||
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| 650 | 4 | |a Statistik | |
| 650 | 4 | |a Statistics |x Graphic methods | |
| 650 | 4 | |a Computer graphics | |
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Datensatz im Suchindex
| _version_ | 1805083700459732992 |
|---|---|
| adam_text |
Contents
Introduction
. 1
1.1
Introduction
. 1
1.2
Data
Visualization.
4
1.3
Research
Literature .
7
1.4
How
Large
Is
a Large
Dataset?.
9
1.5
The Effects of Largeness
. 17
1.5.1
Storage
. 18
1.5.2
Quality
. 19
1.5.3
Complexity
. 20
1.5.4
Speed
. 20
1.5.5
Analyses
. 21
1.5.6
Displays
. 21
1.5.7
Graphical Formats
. 22
1.6
What Is in This Book
. 22
1.7
Software
. 23
1.8
What Is on the Website
. 24
1.8.1
Files and Code for Figures
. 24
1.8.2
Links to Software
. 24
1.8.3
Datasets
. 25
1.9
Contributing Authors
. 26
Part I Basics
2
Statistical Graphics
. 31
2.1
Introduction
. 31
2.2
Plots for Categorical Data
. 31
2.2.1 Barcharts
and Spineplots for Univariate
Categorical Data
. 32
2.2.2
Mosaic Plots for Multi-dimensional Categorical Data
33
2.3
Plots for Continuous Data
. 36
Contents
2.3.1 Dotplots, Boxplots,
and Histograms
. 36
2.3.2 Scatterplots, Parallel
Coordinates, and the
Grand
Tour. 39
2.4 Data
on Mixed Scales
. 44
2.5
Maps
.
47
2.6
Contour Plots and Image Maps
. 49
2.7
Time Series Plots
.
50
2.8
Structure Plots
.
51
Scaling Up Graphics
. 55
3.1
Introduction
. 55
3.2
Upscaling as a General Problem in Statistics
. 55
3.3
Area Plots
. 56
3.3.1
Histograms
. 57
3.3.2 Barcharts. 58
3.3.3
Mosaic Plots
. 60
3.4
Point Plots
. 62
3.4.1
Boxplots
. 62
3.4.2
Scatterplots
. 63
3.4.3
Parallel Coordinates
. 65
3.5
From Areas to Points and Back
. 67
3.5.1
α
-Blending and Tonal Highlighting
. 69
3.6
Modifying Plots
. 71
3.7
Summary
. 72
Interacting with Graphics
. 73
4.1
Introduction
. 73
4.2
Interaction
. 74
4.3
Interaction and Data Displays
. 75
4.3.1
Querying
. 75
4.3.2
Selection and Linking
. 77
4.3.3
Selection Sequences
. 78
4.3.4
Varying Plot Characteristics
. 82
4.3.5
Interfaces and Interaction
. 84
4.3.6
Degrees of Linking
. 86
4.3.7
Warnings and Redmarking
. 87
4.4
Interaction and Large
Datasets
. 88
4.4.1
Querying
. 88
4.4.2
Selection, Linking, and Highlighting
. 89
4.4.3
Varying Plot Characteristics for Large
Datasets
. 92
4.5
New Interactive Tasks
. 98
4.5.1
Subsetting
. 98
4.5.2
Aggregation and Recoding
. 99
4.5.3
Transformations
. 99
4.5.4
Weighting
.[[[. 99
Contents xi
4.5.5
Managing
Screen
Layout.101
4.6
Summary and Future Directions
.101
Part II Applications
5
Multivariate Categorical Data
—
Mosaic Plots
.105
5.1
Introduction
.105
5.2
Area-based Displays
.105
5.2.1
Weighted Displays and Weights in
Datasets
.107
5.3
Displays and Techniques in One Dimension
.107
5.3.1
Sorting and Reordering
.110
5.3.2
Grouping, Averaging, and Zooming
.
Ill
5.4
Mosaic Plots
.113
5.4.1
Combinatorics of Mosaic Plots
.114
5.4.2
Cases per Pixel and Pixels per Case
.116
5.4.3
Calibrating the Eye
.116
5.4.4
Gray-shading
.119
5.4.5
Rescaling Binsizes
.122
5.4.6
Rankings
.123
5.5
Summary
.123
6
Rotating Plots
.125
6.1
Introduction
.125
6.1.1
Type of Data
.126
6.1.2
Visual Methods for Continuous Variables
.127
6.1.3
Scaling Up Multiple Views for Larger
Datasets
.128
6.2
Beginning to Work with a Million Cases
.128
6.2.1
What Happens in GGobi, a Real-time System?
.128
6.2.2
Reducing the Number of Cases
.129
6.2.3
Density Estimation
.131
6.2.4
Screen Real Estate Indexing
.134
6.3
Software System
.135
6.4
Application
.137
6.4.1
Data Description
.137
6.4.2
Viewing a Tour of the Data
.137
6.4.3
Scatterplot Matrix
.138
6.5
Current and Future Developments
.140
6.5.1
Improving the Methods
.140
6.5.2
Software
.141
6.5.3
How Might These Tools Be Used?
.141
xii Contents
7 Multivariate
Continuous Data
— Parallel
Coordinates
143
7.1
Introduction
.143
7.2
Interpolations and
Inner Products .144
7.3
Generalized
Parallel
Coordinate Geometry
.145
7.4
A New Family of Smooth Plots
.149
7.5
Examples
.
I50
7.5.1
Automobile Data
.150
7.5.2
Hyperspectral Data: Dealing with Massive
Datasets
. 152
7.6
Detecting Second-Order Structures
.154
7.7
Summary
.155
8
Networks
.157
8.1
Introduction
.157
8.2
Layout Algorithms
.158
8.2.1
Simple Tree Layout
.159
8.2.2
Force Layout Methods
.161
8.2.3
Individual Node Movement Algorithms
.162
8.3
Interactivity
.162
8.3.1
Speed Considerations
.164
8.3.2
Interaction and Layout
.165
8.4
NicheWorks
.166
8.5
Example: International Calling Fraud
.167
8.6
Languages for Description and Layouts
.172
8.6.1
Defining a Graph
.172
8.6.2
Graph Specification via VizML
.173
8.7
Summary
.
I74
9
Trees
.177
9.1
Introduction
.
I77
9.2
Growing Trees for Large
Datasets
.178
9.2.1
Scalability of the CART Growing Algorithm
.179
9.2.2
Scalability of Pruning Methods
.181
9.2.3
Statistical Tests and Large
Datasets
.183
9.2.4
Using Trees for Large
Datasets
in Practice
.184
9.3
Visualization of Large Trees
.187
9.3.1
Hierarchical Plots
.187
9.3.2
Sectioned Scatterplots
.192
9.3.3
Recursive Plots
.
I95
9.4
Forests for Large
Datasets
.198
9.5
Summary
. 202
Contents xiii
10
Transactions
.203
10.1
Introduction
and Background
.203
10.2
Mice and Elephant Plots and Random Sampling
.205
10.3
Biased Sampling
.210
10.3.1
Windowed Biased Sampling
.211
10.3.2
Box
-Сох
Biased Sampling
.213
10.4
Quantile Window Sampling
.215
10.5
Commonality of Flow Rates
.221
11
Graphics of a Large
Dataset
.227
11.1
Introduction
.227
11.2
QuickStart Guide
Data Visualization for Large
Datasets
.228
11.3
Visualizing the Info Vis
2005
Contest
Dataset
.229
11.3.1
Preliminaries
.229
11.3.2
Variables
.230
11.3.3
First Analyses
.230
11.3.4
Multivariate Displays
.235
11.3.5
Grouping and Selection
.239
11.3.6
Special Features
.242
11.3.7
Presenting Results
.247
11.3.8
Summary
.249
References
.251
Authors
.263
Index
.267 |
| adam_txt |
Contents
Introduction
. 1
1.1
Introduction
. 1
1.2
Data
Visualization.
4
1.3
Research
Literature .
7
1.4
How
Large
Is
a Large
Dataset?.
9
1.5
The Effects of Largeness
. 17
1.5.1
Storage
. 18
1.5.2
Quality
. 19
1.5.3
Complexity
. 20
1.5.4
Speed
. 20
1.5.5
Analyses
. 21
1.5.6
Displays
. 21
1.5.7
Graphical Formats
. 22
1.6
What Is in This Book
. 22
1.7
Software
. 23
1.8
What Is on the Website
. 24
1.8.1
Files and Code for Figures
. 24
1.8.2
Links to Software
. 24
1.8.3
Datasets
. 25
1.9
Contributing Authors
. 26
Part I Basics
2
Statistical Graphics
. 31
2.1
Introduction
. 31
2.2
Plots for Categorical Data
. 31
2.2.1 Barcharts
and Spineplots for Univariate
Categorical Data
. 32
2.2.2
Mosaic Plots for Multi-dimensional Categorical Data
33
2.3
Plots for Continuous Data
. 36
Contents
2.3.1 Dotplots, Boxplots,
and Histograms
. 36
2.3.2 Scatterplots, Parallel
Coordinates, and the
Grand
Tour. 39
2.4 Data
on Mixed Scales
. 44
2.5
Maps
.
47
2.6
Contour Plots and Image Maps
. 49
2.7
Time Series Plots
.
50
2.8
Structure Plots
.
51
Scaling Up Graphics
. 55
3.1
Introduction
. 55
3.2
Upscaling as a General Problem in Statistics
. 55
3.3
Area Plots
. 56
3.3.1
Histograms
. 57
3.3.2 Barcharts. 58
3.3.3
Mosaic Plots
. 60
3.4
Point Plots
. 62
3.4.1
Boxplots
. 62
3.4.2
Scatterplots
. 63
3.4.3
Parallel Coordinates
. 65
3.5
From Areas to Points and Back
. 67
3.5.1
α
-Blending and Tonal Highlighting
. 69
3.6
Modifying Plots
. 71
3.7
Summary
. 72
Interacting with Graphics
. 73
4.1
Introduction
. 73
4.2
Interaction
. 74
4.3
Interaction and Data Displays
. 75
4.3.1
Querying
. 75
4.3.2
Selection and Linking
. 77
4.3.3
Selection Sequences
. 78
4.3.4
Varying Plot Characteristics
. 82
4.3.5
Interfaces and Interaction
. 84
4.3.6
Degrees of Linking
. 86
4.3.7
Warnings and Redmarking
. 87
4.4
Interaction and Large
Datasets
. 88
4.4.1
Querying
. 88
4.4.2
Selection, Linking, and Highlighting
. 89
4.4.3
Varying Plot Characteristics for Large
Datasets
. 92
4.5
New Interactive Tasks
. 98
4.5.1
Subsetting
. 98
4.5.2
Aggregation and Recoding
. 99
4.5.3
Transformations
. 99
4.5.4
Weighting
.[[[. 99
Contents xi
4.5.5
Managing
Screen
Layout.101
4.6
Summary and Future Directions
.101
Part II Applications
5
Multivariate Categorical Data
—
Mosaic Plots
.105
5.1
Introduction
.105
5.2
Area-based Displays
.105
5.2.1
Weighted Displays and Weights in
Datasets
.107
5.3
Displays and Techniques in One Dimension
.107
5.3.1
Sorting and Reordering
.110
5.3.2
Grouping, Averaging, and Zooming
.
Ill
5.4
Mosaic Plots
.113
5.4.1
Combinatorics of Mosaic Plots
.114
5.4.2
Cases per Pixel and Pixels per Case
.116
5.4.3
Calibrating the Eye
.116
5.4.4
Gray-shading
.119
5.4.5
Rescaling Binsizes
.122
5.4.6
Rankings
.123
5.5
Summary
.123
6
Rotating Plots
.125
6.1
Introduction
.125
6.1.1
Type of Data
.126
6.1.2
Visual Methods for Continuous Variables
.127
6.1.3
Scaling Up Multiple Views for Larger
Datasets
.128
6.2
Beginning to Work with a Million Cases
.128
6.2.1
What Happens in GGobi, a Real-time System?
.128
6.2.2
Reducing the Number of Cases
.129
6.2.3
Density Estimation
.131
6.2.4
Screen Real Estate Indexing
.134
6.3
Software System
.135
6.4
Application
.137
6.4.1
Data Description
.137
6.4.2
Viewing a Tour of the Data
.137
6.4.3
Scatterplot Matrix
.138
6.5
Current and Future Developments
.140
6.5.1
Improving the Methods
.140
6.5.2
Software
.141
6.5.3
How Might These Tools Be Used?
.141
xii Contents
7 Multivariate
Continuous Data
— Parallel
Coordinates
143
7.1
Introduction
.143
7.2
Interpolations and
Inner Products .144
7.3
Generalized
Parallel
Coordinate Geometry
.145
7.4
A New Family of Smooth Plots
.149
7.5
Examples
.
I50
7.5.1
Automobile Data
.150
7.5.2
Hyperspectral Data: Dealing with Massive
Datasets
. 152
7.6
Detecting Second-Order Structures
.154
7.7
Summary
.155
8
Networks
.157
8.1
Introduction
.157
8.2
Layout Algorithms
.158
8.2.1
Simple Tree Layout
.159
8.2.2
Force Layout Methods
.161
8.2.3
Individual Node Movement Algorithms
.162
8.3
Interactivity
.162
8.3.1
Speed Considerations
.164
8.3.2
Interaction and Layout
.165
8.4
NicheWorks
.166
8.5
Example: International Calling Fraud
.167
8.6
Languages for Description and Layouts
.172
8.6.1
Defining a Graph
.172
8.6.2
Graph Specification via VizML
.173
8.7
Summary
.
I74
9
Trees
.177
9.1
Introduction
.
I77
9.2
Growing Trees for Large
Datasets
.178
9.2.1
Scalability of the CART Growing Algorithm
.179
9.2.2
Scalability of Pruning Methods
.181
9.2.3
Statistical Tests and Large
Datasets
.183
9.2.4
Using Trees for Large
Datasets
in Practice
.184
9.3
Visualization of Large Trees
.187
9.3.1
Hierarchical Plots
.187
9.3.2
Sectioned Scatterplots
.192
9.3.3
Recursive Plots
.
I95
9.4
Forests for Large
Datasets
.198
9.5
Summary
. 202
Contents xiii
10
Transactions
.203
10.1
Introduction
and Background
.203
10.2
Mice and Elephant Plots and Random Sampling
.205
10.3
Biased Sampling
.210
10.3.1
Windowed Biased Sampling
.211
10.3.2
Box
-Сох
Biased Sampling
.213
10.4
Quantile Window Sampling
.215
10.5
Commonality of Flow Rates
.221
11
Graphics of a Large
Dataset
.227
11.1
Introduction
.227
11.2
QuickStart Guide
Data Visualization for Large
Datasets
.228
11.3
Visualizing the Info Vis
2005
Contest
Dataset
.229
11.3.1
Preliminaries
.229
11.3.2
Variables
.230
11.3.3
First Analyses
.230
11.3.4
Multivariate Displays
.235
11.3.5
Grouping and Selection
.239
11.3.6
Special Features
.242
11.3.7
Presenting Results
.247
11.3.8
Summary
.249
References
.251
Authors
.263
Index
.267 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Unwin, Antony Theus, Martin 1967- Hofmann, Heike |
| author_GND | (DE-588)1078769265 (DE-588)115198180 |
| author_facet | Unwin, Antony Theus, Martin 1967- Hofmann, Heike |
| author_role | aut aut aut |
| author_sort | Unwin, Antony |
| author_variant | a u au m t mt h h hh |
| building | Verbundindex |
| bvnumber | BV022299128 |
| callnumber-first | Q - Science |
| callnumber-label | QA276 |
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| callnumber-search | QA276.3 |
| callnumber-sort | QA 3276.3 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | SK 850 ST 320 |
| ctrlnum | (OCoLC)890526910 (DE-599)BVBBV022299128 |
| dewey-full | 519.5028566 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5028566 |
| dewey-search | 519.5028566 |
| dewey-sort | 3519.5028566 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Mathematik |
| discipline_str_mv | Informatik Mathematik |
| format | Book |
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| id | DE-604.BV022299128 |
| illustrated | Illustrated |
| index_date | 2024-07-02T16:54:28Z |
| indexdate | 2024-07-20T07:52:43Z |
| institution | BVB |
| isbn | 9780387329062 0387329064 |
| language | English |
| lccn | 2006922760 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015509144 |
| oclc_num | 890526910 |
| open_access_boolean | |
| owner | DE-20 DE-384 DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-703 DE-824 DE-B16 DE-11 DE-355 DE-BY-UBR |
| owner_facet | DE-20 DE-384 DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-703 DE-824 DE-B16 DE-11 DE-355 DE-BY-UBR |
| physical | xiii, 271 Seiten Illustrationen, Diagramme, Karten (überwiegend farbig) |
| publishDate | 2006 |
| publishDateSearch | 2006 |
| publishDateSort | 2006 |
| publisher | Springer |
| record_format | marc |
| series2 | Statistics and computing |
| spelling | Unwin, Antony Verfasser (DE-588)1078769265 aut Graphics of large datasets visualizing a million Antony Unwin, Martin Theus, Heike Hofmann New York, NY Springer [2006] © 2006 xiii, 271 Seiten Illustrationen, Diagramme, Karten (überwiegend farbig) txt rdacontent n rdamedia nc rdacarrier Statistics and computing Literaturverzeichnis Seite 251-261 Infographie Statistique - Méthodes graphiques Statistik Statistics Graphic methods Computer graphics Computergrafik (DE-588)4010450-3 gnd rswk-swf Umfang (DE-588)7583293-8 gnd rswk-swf Datensatz (DE-588)4011133-7 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Grafische Darstellung (DE-588)4129552-3 gnd rswk-swf Datensatz (DE-588)4011133-7 s Umfang (DE-588)7583293-8 s Grafische Darstellung (DE-588)4129552-3 s DE-604 Statistik (DE-588)4056995-0 s Computergrafik (DE-588)4010450-3 s 1\p DE-604 Theus, Martin 1967- Verfasser (DE-588)115198180 aut Hofmann, Heike Verfasser aut Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015509144&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Unwin, Antony Theus, Martin 1967- Hofmann, Heike Graphics of large datasets visualizing a million Infographie Statistique - Méthodes graphiques Statistik Statistics Graphic methods Computer graphics Computergrafik (DE-588)4010450-3 gnd Umfang (DE-588)7583293-8 gnd Datensatz (DE-588)4011133-7 gnd Statistik (DE-588)4056995-0 gnd Grafische Darstellung (DE-588)4129552-3 gnd |
| subject_GND | (DE-588)4010450-3 (DE-588)7583293-8 (DE-588)4011133-7 (DE-588)4056995-0 (DE-588)4129552-3 |
| title | Graphics of large datasets visualizing a million |
| title_auth | Graphics of large datasets visualizing a million |
| title_exact_search | Graphics of large datasets visualizing a million |
| title_exact_search_txtP | Graphics of large datasets visualizing a million |
| title_full | Graphics of large datasets visualizing a million Antony Unwin, Martin Theus, Heike Hofmann |
| title_fullStr | Graphics of large datasets visualizing a million Antony Unwin, Martin Theus, Heike Hofmann |
| title_full_unstemmed | Graphics of large datasets visualizing a million Antony Unwin, Martin Theus, Heike Hofmann |
| title_short | Graphics of large datasets |
| title_sort | graphics of large datasets visualizing a million |
| title_sub | visualizing a million |
| topic | Infographie Statistique - Méthodes graphiques Statistik Statistics Graphic methods Computer graphics Computergrafik (DE-588)4010450-3 gnd Umfang (DE-588)7583293-8 gnd Datensatz (DE-588)4011133-7 gnd Statistik (DE-588)4056995-0 gnd Grafische Darstellung (DE-588)4129552-3 gnd |
| topic_facet | Infographie Statistique - Méthodes graphiques Statistik Statistics Graphic methods Computer graphics Computergrafik Umfang Datensatz Grafische Darstellung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015509144&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT unwinantony graphicsoflargedatasetsvisualizingamillion AT theusmartin graphicsoflargedatasetsvisualizingamillion AT hofmannheike graphicsoflargedatasetsvisualizingamillion |