Visual Data Insights Using SAS ODS Graphics
A Guide to Communication-Effective Data Visualization
(Sprache: Englisch)
Intermediate user level
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Intermediate user level
Klappentext zu „Visual Data Insights Using SAS ODS Graphics “
SAS ODS graphics users will learn in this book how to visually understand and communicate the significance of data to deliver images for quick and easy insight, with precise numbers. Many charts or plots require the viewer to run the eye from a bar end or plot point to some point on an axis, and then to interpolate between tick marks to estimate the value. Some design choices can lead to wrong conclusions or mistaken impressions. Graphic software relies on defaults to deliver something if you make a minimal effort, but that something is not likely to be exactly what you want.
Visual Data Insights Using SAS ODS Graphics provides examples using experience-based design principles. It presents examples of bar charts, pie charts, and trend lines or time series plots, the graph types commonly used in business, other organizations, and the media for visual insight into data. Newer graphs are also included: dot plots, needle plots, waterfall charts, butterfly charts, heat maps, bubble plots, step plots, high-low plots, and donut charts. In addition, there are basic tools of statistics: scatter plots, box plots, histograms, fit and confidence plots, and distributions.
Author LeRoy Bessler introduces unique creations, including sparsely annotated time series, maximally informative bar charts, better box plots, histograms based on interesting atypical rationales, and much more.
The examples use SAS sample data sets as input. Any SAS user can experiment with the code presented to see what else is possible, or adapt it to repurpose the design and apply it with a customized version of that code.
What You'll Learn
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Who This Book Is For
SAS software users who want to understand their data and/or visually deliver their results
- Create graphs that are easily and quickly interpreted, and without ambiguity
- Supply precise data values that are correct on the graph and correctly associated with the graphic visual elements
- Take advantage of widely applicable (but not necessarily available elsewhere) design examples
- Avoid bad practices that are encouraged by poor examples elsewhere
- Get past sub-optimal designs and results that are built into software defaults
- Take advantage of less familiar capabilities available in the software
Who This Book Is For
SAS software users who want to understand their data and/or visually deliver their results
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Inhaltsverzeichnis zu „Visual Data Insights Using SAS ODS Graphics “
Introduction About this book
Part I: Design Principles
Chapter 1: Principles of Communication-Effective Graphic Design
A. Joseph Pulitzer on Communication (principles for Press are universally applicable)B. Accelerate/Facilitate Visual Data Insights with Simplicity
C. The Effects of Needless Complexity
D. Simplicity
E. Elegance
F. Sparse Image Focuses AttentionG. Sparse Graph more easily, more quickly interpreted
H. Whenever possible, make graph title a headline
I. Text readability-often wrongly assumed by graph creators
J. Is what the creator sees what the viewer sees?
K. How assure text readability
L. We read horizontally
M. Axis LabelsN. Image Plus Precise Numbers-Both Are Necessary
O. Annotation or On-Image Table
P. Sparse Line Annotation
Q. Y Axis for Time Series Plots
R. Ranking and Subsetting InformationS. Scrolling on Web Graphs
T. Maximizing Information Delivery in Titles and Subtitles
U. 3D
Chapter 2: Principles of Communication-Effective Use of Color
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A. When and Why Color: Communication, Not Decoration
B. Benefits of Boring Black and White
C. Contrast with Background
D. Always Bad Backgrounds1) Image Backgrounds (continuous tone color)
2) Color Gradient Backgrounds
3) Textured Backgrounds
E. Visual Dominance
F. Other Choices for Text EmphasisG. Monitor Color vs HardCopy Color
H. Consistency
I. Purpose/Significance Assumed Even If Unintended
J. Color-Coding
K. Thickness of Lines and TextL. Size of Plot Markers and Legend Color Blocks
M. Maximum Number of Distinguishable Shades of One Hue
N. Other Tips
O. Color Control with ODS Graphics Attribute Maps
P. Multi-Line Plot That Obviates Need for a Legend
Part II: Widely Applicable Examples You Can Use
Chapter 3: Technical Introduction
A. Outer Structure of ODS Graphics Code in Examples
B. Inner Structure of ODS Graphics Code in Examples
C. Text Parts of ODS Graphics Images
D. Borders
E. From Defaults through Customization for a Simple Example
F. What Follows
Chapter 4: Charts for Data in Categories
A. Getting Your Charts In Order
B. Pie Charts 1) The Perils of Pie Charts
a) 3D Pie Charts are ALWAYS misleading
b) Labels Can Collide If All Outside
c) Labels Can Be Hard To Read If Inside If Insufficient Color Fill Contrast
d) Slices Too Small To Be Seen Are Not Necessarily a Problem
e) Reason to Avoid the OTHER Collective Pie Slice
2) Pie Chart Alternatives a) Default Colors vs Better Background for Inside-Of-Slice Labels
b) All Inside Labels
c) All Outside Labels for Name/Category, Value, Percent
d) Label Collisions Problem
e) Collision Problem Solved
f) Maximally Informative CallOut Labels
g) Default Legend h) Maximally Informative Legend
i) The Ineffable Incontrovertible Insightful Power of Simplicity: The Pac-Man Pie Chart-the Extremes of Other C. Donut Charts
D. Horizontal Bar Charts
1) Default Chart
2) Easy Bar Annotation
3) Adding Percent of Total Measurement
4) Key Design Principles
a) Ranking; Show Them What's Important
b) Subsetting: Let Part Stand for the Whole5) The Maximally Informative Horizontal Bar Chart
6) Interlinked Subsets Images Only
7) A Tall Horizontal Bar Chart: The Complement of a Subset
8) "Nested" Bar Charts (Web Charts)
9) Clustered Bar Chart
10 Dot Chart
11 When to use alphabetical order for bar labels
12 ButterFly Chart
E. Vertical Bar Charts 1) Basic
2) Alternative to the Always Unsatisfactory Stacked Bar Chart
3) Bar Over Bar (Overlay) Chart
4) Needle Plot
5) WaterFall Charts
F. Panels of Bar Charts
G. Other Charts Data with a Single Categorical Key
1) Series Chart with Block Chart 2) Needle Plot with Block Chart
H. Single Categorical Key But Two Measurement Variables: Vertical Bar Chart with Overlaid Line Chart I. Charts for Two Categorical Keys
1) Bubble Chart
2) Heat Map
a) Default
b) Improved
c) Alternative with Simpler Code
Chapter 5: Plots for Time-Dependent DataA. Best Use of Vertical Axis Space
B. CurveLabels vs Legend
C. Single-Line Plots
1) Simple
2) Band Plot
3) With Band As OverLay "Companion" to Highlight Part of Plotted Area
D. All the ways to present a v e r y l o n g plot
E. Multiple Line Plots Concurrently Displayed
1) Overlaid
2) Overlaid and Using Line Color Control
3) Overlaid and Using Data Labels and, to Eliminate Need for Legend, Curve Labels
4) Overlaid and Using XAxis Table, No Legend or CurveLabels Needed
5) In a PanelF. The Ineffable Incontrovertible Insightful Power of Simplicity: Annotated SparseLines
1) Single
2) Stacked or Paneled
G. Spark Tables - SparkLines Used in a Table
H. Other Ways To Present Time Series Data 1) Needle Plot
2) Step Plot
3) High-Low Open-Close Plot for Virtual Multi-Line Plot
I. Vertical Bar Charts to Show Date/Time Dependence
J. Animation To Show Time Evolution
K. Other Alternatives to Providing Numbers
1) Limiting Labels to Y Values by Using Needle Plot to Get to X axis precisely 2) Use DropLines to Both Axes
3) Using TEXT Statements
4) Using ODS Graphics Annotation [LIGHT HERE, a usage example is provided for the US By-State Population Map]
L. When all on-image annotation methods are infeasible, or declined
1) Web Graph Linked to Excel Table and Back 2) Graph and Table Composite in Excel WorkSheet
3) Graph and Table Composite in PowerPoint Slide
4) Graph and Table Composite in Word Document
5) Graph and Table Composite in PDF File
Chapter 6: Looking for Relationships between Two Variables
A. Scatter Charts 1) SGSCATTER with PLOT Statement vs SGPLOT with SCATTER Statement
2) Annotation with DataLabels
3) Highly Informative DataLabels
4) DropLines Instead of DataLabels
5) Annotation with the TEXT Statement 6) PROC SGSCATTER Panel of One Y Variable vs Two X Variables
7) PROC SGSCATTER Panel of Two Y Variables vs One X Variable 8) PROC SGSCATTER Panel of Three Y Variables vs One X Variable
9, 10, 11) Use PROC SGPANEL and SCATTER statement to create above examples-possibly retain just this solution
12} Overlay of Two Scatter Plots for Different Values of a Categorical Variable (e.g., Gender) to See Correlations and Differences in the y-x Relationship
13) SGPANEL of two Gender-Specific SCATTER plots for data in Item 12
13) Horizontal or Vertical Panel of the Above Overlay with the Two Individual Scatter Plots as Companion Images for Clarity 15) Annotated Scattter Plot using SGPLOT and SCATTER Statement
16) Add x values to annotation and suppress the superfluous axis
17) Replace y,x annotation with names of people whose data is plotted
18) Maximal annotation with Name, y, x
19) SGPANEL other examples TBD, maybe none
B. Fit and Confidence Plots
1) Introduction
2) ELLIPSE
3) Linear Regression Plot
4) Cubic Regression Plot
5) LOESS Fit 6) SPLINE
7) Penalized B-Spline Plot
C. VLINE Plus VBAR on the Same Chart
Chapter 7: Distribution of a Single Variable
A. Histogram 1) Basic
2) With Density Plot3) With Fringe Plot
B. Density Plot with Fringe Plot
C. Box Plots
Chapter 8: Maps for Data with Geographic Keys
A. Examples for various types of unit area
1) By Country 2) By State
3) By County
4) By Point Location, such as City
B. Rationales for Range Setting for the Measurement Reported
C. Automating implementation of the rationale D. Annotating the map for maximal information communication
E. The "For Color" Map Problem Solved-Color Coding for Maps F. What to do for a unit area that is too tiny to be readily visible
Part III: Other Features
Chapter 9: Ways to Enhance Your Graph
A. Attribute Maps B. Reference Lines
C. Inserting Text with INSET and TEXT Statements
Chapter 10: Other Ways To Deliver Data VisualizationA. Graph and Table Composite in Excel WorkSheet
B. Graph and Table Composite in & Other Examples in PowerPoint Slides C. Graph and Table Composite in Word Document
D. Graph and Table Composite in PDF File
E. So you want to build an InfoGraphic
1) Creating the elements as individual images
2) Assembling a composite from those images3) Creating an image file from the slide
Chapter 11: Miscellaneous Tips
A. Positioning of Titles in ODS Graphics ImagesB. Title and Footnote Text Handling in Web Graphs
C. Pseudo-3D Effects That Introduce No Distortion or Needless Complexity
Part IV: Appendixes
Appendix A: Additional Resources
1. SAS-Institute-provided Documentation
2. Other Resources at support.sas.com3. Online Conference Proceedings (not available from SAS Institute)
4. Online Newsletters
5. Blogs
6. Others TBD
Appendix B: Possible Lengthy Code for Some Examples
A. When and Why Color: Communication, Not Decoration
B. Benefits of Boring Black and White
C. Contrast with Background
D. Always Bad Backgrounds1) Image Backgrounds (continuous tone color)
2) Color Gradient Backgrounds
3) Textured Backgrounds
E. Visual Dominance
F. Other Choices for Text EmphasisG. Monitor Color vs HardCopy Color
H. Consistency
I. Purpose/Significance Assumed Even If Unintended
J. Color-Coding
K. Thickness of Lines and TextL. Size of Plot Markers and Legend Color Blocks
M. Maximum Number of Distinguishable Shades of One Hue
N. Other Tips
O. Color Control with ODS Graphics Attribute Maps
P. Multi-Line Plot That Obviates Need for a Legend
Part II: Widely Applicable Examples You Can Use
Chapter 3: Technical Introduction
A. Outer Structure of ODS Graphics Code in Examples
B. Inner Structure of ODS Graphics Code in Examples
C. Text Parts of ODS Graphics Images
D. Borders
E. From Defaults through Customization for a Simple Example
F. What Follows
Chapter 4: Charts for Data in Categories
A. Getting Your Charts In Order
B. Pie Charts 1) The Perils of Pie Charts
a) 3D Pie Charts are ALWAYS misleading
b) Labels Can Collide If All Outside
c) Labels Can Be Hard To Read If Inside If Insufficient Color Fill Contrast
d) Slices Too Small To Be Seen Are Not Necessarily a Problem
e) Reason to Avoid the OTHER Collective Pie Slice
2) Pie Chart Alternatives a) Default Colors vs Better Background for Inside-Of-Slice Labels
b) All Inside Labels
c) All Outside Labels for Name/Category, Value, Percent
d) Label Collisions Problem
e) Collision Problem Solved
f) Maximally Informative CallOut Labels
g) Default Legend h) Maximally Informative Legend
i) The Ineffable Incontrovertible Insightful Power of Simplicity: The Pac-Man Pie Chart-the Extremes of Other C. Donut Charts
D. Horizontal Bar Charts
1) Default Chart
2) Easy Bar Annotation
3) Adding Percent of Total Measurement
4) Key Design Principles
a) Ranking; Show Them What's Important
b) Subsetting: Let Part Stand for the Whole5) The Maximally Informative Horizontal Bar Chart
6) Interlinked Subsets Images Only
7) A Tall Horizontal Bar Chart: The Complement of a Subset
8) "Nested" Bar Charts (Web Charts)
9) Clustered Bar Chart
10 Dot Chart
11 When to use alphabetical order for bar labels
12 ButterFly Chart
E. Vertical Bar Charts 1) Basic
2) Alternative to the Always Unsatisfactory Stacked Bar Chart
3) Bar Over Bar (Overlay) Chart
4) Needle Plot
5) WaterFall Charts
F. Panels of Bar Charts
G. Other Charts Data with a Single Categorical Key
1) Series Chart with Block Chart 2) Needle Plot with Block Chart
H. Single Categorical Key But Two Measurement Variables: Vertical Bar Chart with Overlaid Line Chart I. Charts for Two Categorical Keys
1) Bubble Chart
2) Heat Map
a) Default
b) Improved
c) Alternative with Simpler Code
Chapter 5: Plots for Time-Dependent DataA. Best Use of Vertical Axis Space
B. CurveLabels vs Legend
C. Single-Line Plots
1) Simple
2) Band Plot
3) With Band As OverLay "Companion" to Highlight Part of Plotted Area
D. All the ways to present a v e r y l o n g plot
E. Multiple Line Plots Concurrently Displayed
1) Overlaid
2) Overlaid and Using Line Color Control
3) Overlaid and Using Data Labels and, to Eliminate Need for Legend, Curve Labels
4) Overlaid and Using XAxis Table, No Legend or CurveLabels Needed
5) In a PanelF. The Ineffable Incontrovertible Insightful Power of Simplicity: Annotated SparseLines
1) Single
2) Stacked or Paneled
G. Spark Tables - SparkLines Used in a Table
H. Other Ways To Present Time Series Data 1) Needle Plot
2) Step Plot
3) High-Low Open-Close Plot for Virtual Multi-Line Plot
I. Vertical Bar Charts to Show Date/Time Dependence
J. Animation To Show Time Evolution
K. Other Alternatives to Providing Numbers
1) Limiting Labels to Y Values by Using Needle Plot to Get to X axis precisely 2) Use DropLines to Both Axes
3) Using TEXT Statements
4) Using ODS Graphics Annotation [LIGHT HERE, a usage example is provided for the US By-State Population Map]
L. When all on-image annotation methods are infeasible, or declined
1) Web Graph Linked to Excel Table and Back 2) Graph and Table Composite in Excel WorkSheet
3) Graph and Table Composite in PowerPoint Slide
4) Graph and Table Composite in Word Document
5) Graph and Table Composite in PDF File
Chapter 6: Looking for Relationships between Two Variables
A. Scatter Charts 1) SGSCATTER with PLOT Statement vs SGPLOT with SCATTER Statement
2) Annotation with DataLabels
3) Highly Informative DataLabels
4) DropLines Instead of DataLabels
5) Annotation with the TEXT Statement 6) PROC SGSCATTER Panel of One Y Variable vs Two X Variables
7) PROC SGSCATTER Panel of Two Y Variables vs One X Variable 8) PROC SGSCATTER Panel of Three Y Variables vs One X Variable
9, 10, 11) Use PROC SGPANEL and SCATTER statement to create above examples-possibly retain just this solution
12} Overlay of Two Scatter Plots for Different Values of a Categorical Variable (e.g., Gender) to See Correlations and Differences in the y-x Relationship
13) SGPANEL of two Gender-Specific SCATTER plots for data in Item 12
13) Horizontal or Vertical Panel of the Above Overlay with the Two Individual Scatter Plots as Companion Images for Clarity 15) Annotated Scattter Plot using SGPLOT and SCATTER Statement
16) Add x values to annotation and suppress the superfluous axis
17) Replace y,x annotation with names of people whose data is plotted
18) Maximal annotation with Name, y, x
19) SGPANEL other examples TBD, maybe none
B. Fit and Confidence Plots
1) Introduction
2) ELLIPSE
3) Linear Regression Plot
4) Cubic Regression Plot
5) LOESS Fit 6) SPLINE
7) Penalized B-Spline Plot
C. VLINE Plus VBAR on the Same Chart
Chapter 7: Distribution of a Single Variable
A. Histogram 1) Basic
2) With Density Plot3) With Fringe Plot
B. Density Plot with Fringe Plot
C. Box Plots
Chapter 8: Maps for Data with Geographic Keys
A. Examples for various types of unit area
1) By Country 2) By State
3) By County
4) By Point Location, such as City
B. Rationales for Range Setting for the Measurement Reported
C. Automating implementation of the rationale D. Annotating the map for maximal information communication
E. The "For Color" Map Problem Solved-Color Coding for Maps F. What to do for a unit area that is too tiny to be readily visible
Part III: Other Features
Chapter 9: Ways to Enhance Your Graph
A. Attribute Maps B. Reference Lines
C. Inserting Text with INSET and TEXT Statements
Chapter 10: Other Ways To Deliver Data VisualizationA. Graph and Table Composite in Excel WorkSheet
B. Graph and Table Composite in & Other Examples in PowerPoint Slides C. Graph and Table Composite in Word Document
D. Graph and Table Composite in PDF File
E. So you want to build an InfoGraphic
1) Creating the elements as individual images
2) Assembling a composite from those images3) Creating an image file from the slide
Chapter 11: Miscellaneous Tips
A. Positioning of Titles in ODS Graphics ImagesB. Title and Footnote Text Handling in Web Graphs
C. Pseudo-3D Effects That Introduce No Distortion or Needless Complexity
Part IV: Appendixes
Appendix A: Additional Resources
1. SAS-Institute-provided Documentation
2. Other Resources at support.sas.com3. Online Conference Proceedings (not available from SAS Institute)
4. Online Newsletters
5. Blogs
6. Others TBD
Appendix B: Possible Lengthy Code for Some Examples
... weniger
Autoren-Porträt von LeRoy Bessler
LeRoy Bessler has been a devotee of computer graphics tools in SAS since 1981, and is an award-winning, internationally recognized expert on data visualization. He has been on a continuing quest to find and promote best graphic designs and practices for delivering visual data insights. His book is a long-in-the-making and gradually evolved guiding compendium of his design principles for communication-effective data visualization, with widely applicable examples. He shares his SAS software knowledge, experience, and ideas at conferences in the USA and overseas, and contributes quarterly articles to the VIEWS Newsletter for SAS users.
Bibliographische Angaben
- Autor: LeRoy Bessler
- 2023, 1st ed., XIX, 621 Seiten, 259 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 1484286081
- ISBN-13: 9781484286081
Sprache:
Englisch
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