Overview

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, butterflycharts, 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 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

Full Product Details

Author:   LeRoy Bessler
Publisher:   APress
Imprint:   APress
Edition:   1st ed.
Weight:   0.973kg
ISBN:  

9781484286081

ISBN 10:   1484286081
Pages:   621
Publication Date:   04 January 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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 Attention G.     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 Labels N.     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 Information S.       Scrolling on Web Graphs T.       Maximizing Information Delivery in Titles and Subtitles U.     3D Chapter 2: Principles of Communication-Effective Use of Color A.      When and Why Color: Communication, Not Decoration B.      Benefits of Boring Black and White C.      Contrast with Background D.      Always Bad Backgrounds 1)      Image Backgrounds (continuous tone color) 2)      Color Gradient Backgrounds 3)      Textured Backgrounds E.       Visual Dominance F.       Other Choices for Text Emphasis G.     Monitor Color vs HardCopy Color H.      Consistency I.        Purpose/Significance Assumed Even If Unintended J.        Color-Coding K.      Thickness of Lines and Text L.       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 Whole 5)      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 Data A.      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 Panel F.       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 Plot 3)      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 Visualization A.      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 images 3)      Creating an image file from the slide Chapter 11: Miscellaneous Tips A.      Positioning of Titles in ODS Graphics Images B.      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.com 3.       Online Conference Proceedings (not available from SAS Institute) 4.       Online Newsletters 5.       Blogs 6.       Others TBD   Appendix B: Possible Lengthy Code for Some Examples  

Reviews

Author Information

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. 

Tab Content 6

Author Website:  

Customer Reviews

Recent Reviews

No review item found!

Add your own review!

Countries Available

All regions