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Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures (Record no. 147942)

MARC details
000 -LEADER
fixed length control field	04917nam a22001577a 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field	231129b \|\|\|\|\|\|\|\| \|\|\|\| 00\| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number	9789352138111
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number	001.4226
Item number	WIL
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name	Wilke, Claus O.
9 (RLIN)	46546
245 ## - TITLE STATEMENT
Title	Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc	Shroff Publishers and Distributors Pvt. Ltd.
Place of publication, distribution, etc	Mumbai
Date of publication, distribution, etc	2019
300 ## - PHYSICAL DESCRIPTION
Extent	370p
500 ## - GENERAL NOTE
General note	2. 1. Introduction <br/>1. Ugly, Bad, and Wrong Figures <br/>3. I. From Data to Visualization <br/>4. 2. Visualizing Data: Mapping Data onto Aesthetics <br/>1. Aesthetics and Types of Data <br/>2. Scales Map Data Values onto Aesthetics <br/>5. 3. Coordinate Systems and Axes <br/>1. Cartesian Coordinates <br/>2. Nonlinear Axes <br/>3. Coordinate Systems with Curved Axes <br/>6. 4. Color Scales <br/>1. Color as a Tool to Distinguish <br/>2. Color to Represent Data Values <br/>3. Color as a Tool to Highlight <br/>7. 5. Directory of Visualizations <br/>1. Amounts <br/>2. Distributions <br/>3. Proportions <br/>4. x–y relationships <br/>5. Geospatial Data <br/>6. Uncertainty <br/>8. 6. Visualizing Amounts <br/>1. Bar Plots <br/>2. Grouped and Stacked Bars <br/>3. Dot Plots and Heatmaps <br/>9. 7. Visualizing Distributions: Histograms and Density Plots <br/>1. Visualizing a Single Distribution <br/>2. Visualizing Multiple Distributions at the Same Time <br/>10. 8. Visualizing Distributions: Empirical Cumulative Distribution Functions and Q-Q Plots <br/>1. Empirical Cumulative Distribution Functions <br/>2. Highly Skewed Distributions <br/>3. Quantile-Quantile Plots <br/>11. 9. Visualizing Many Distributions at Once <br/>1. Visualizing Distributions Along the Vertical Axis <br/>2. Visualizing Distributions Along the Horizontal Axis <br/>12. 10. Visualizing Proportions <br/>1. A Case for Pie Charts <br/>2. A Case for Side-by-Side Bars <br/>3. A Case for Stacked Bars and Stacked Densities <br/>4. Visualizing Proportions Separately as Parts of the Total <br/>13. 11. Visualizing Nested Proportions <br/>1. Nested Proportions Gone Wrong <br/>2. Mosaic Plots and Treemaps <br/>3. Nested Pies <br/>4. Parallel Sets <br/>14. 12. Visualizing Associations Among Two or More Quantitative Variables <br/>1. Scatterplots <br/>2. Correlograms <br/>3. Dimension Reduction <br/>4. Paired Data <br/>15. 13. Visualizing Time Series and Other Functions of an Independent Variable <br/>1. Individual Time Series <br/>2. Multiple Time Series and Dose–Response Curves <br/>3. Time Series of Two or More Response Variables <br/>16. 14. Visualizing Trends <br/>1. Smoothing <br/>2. Showing Trends with a Defined Functional Form <br/>3. Detrending and Time-Series Decomposition <br/>17. 15. Visualizing Geospatial Data <br/>1. Projections <br/>2. Layers <br/>3. Choropleth Mapping <br/>4. Cartograms <br/>18. 16. Visualizing Uncertainty <br/>1. Framing Probabilities as Frequencies <br/>2. Visualizing the Uncertainty of Point Estimates <br/>3. Visualizing the Uncertainty of Curve Fits <br/>4. Hypothetical Outcome Plots <br/>19. II. Principles of Figure Design <br/>20. 17. The Principle of Proportional Ink <br/>1. Visualizations Along Linear Axes <br/>2. Visualizations Along Logarithmic Axes <br/>3. Direct Area Visualizations <br/>21. 18. Handling Overlapping Points <br/>1. Partial Transparency and Jittering <br/>2. 2D Histograms <br/>3. Contour Lines <br/>22. 19. Common Pitfalls of Color Use <br/>1. Encoding Too Much or Irrelevant Information <br/>2. Using Nonmonotonic Color Scales to Encode Data Values <br/>3. Not Designing for Color-Vision Deficiency <br/>23. 20. Redundant Coding <br/>1. Designing Legends with Redundant Coding <br/>2. Designing Figures Without Legends <br/>24. 21. Multipanel Figures <br/>1. Small Multiples <br/>2. Compound Figures <br/>25. 22. Titles, Captions, and Tables <br/>1. Figure Titles and Captions <br/>2. Axis and Legend Titles <br/>3. Tables <br/>26. 23. Balance the Data and the Context <br/>1. Providing the Appropriate Amount of Context <br/>2. Background Grids <br/>3. Paired Data <br/>4. Summary <br/>27. 24. Use Larger Axis Labels <br/>28. 25. Avoid Line Drawings <br/>29. 26. Don’t Go 3D <br/>1. Avoid Gratuitous 3D <br/>2. Avoid 3D Position Scales <br/>3. Appropriate Use of 3D Visualizations <br/>30. III. Miscellaneous Topics <br/>31. 27. Understanding the Most Commonly Used Image File Formats <br/>1. Bitmap and Vector Graphics <br/>2. Lossless and Lossy Compression of Bitmap Graphics <br/>3. Converting Between Image Formats <br/>32. 28. Choosing the Right Visualization Software <br/>1. Reproducibility and Repeatability <br/>2. Data Exploration Versus Data Presentation <br/>3. Separation of Content and Design <br/>33. 29. Telling a Story and Making a Point <br/>1. What Is a Story? <br/>2. Make a Figure for the Generals <br/>3. Build Up Toward Complex Figures <br/>4. Make Your Figures Memorable <br/>5. Be Consistent but Don’t Be Repetitive <br/>34. Annotated Bibliography <br/>1. Thinking About Data and Visualization <br/>2. Programming Books <br/>3. Statistics Texts <br/>4. Historical Texts <br/>5. Books on Broadly Related Topics <br/>35. Technical Notes <br/>36. References <br/>37. Index <br/><br/>
600 ## - SUBJECT ADDED ENTRY--PERSONAL NAME
Personal name	Computer Engineering
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme	Dewey Decimal Classification
Call number suffix	001.4226
Call number prefix	WIL
Item type	Book

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