Visualizing Time - Designing Graphical Representations for Statistical Data
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| Verlag | Springer |
| Auflage | 2016 |
| Seiten | 256 |
| Format | 15,6 x 23,4 x 1,4 cm |
| Previously published in hardcover | |
| Gewicht | 421 g |
| Artikeltyp | Englisches Buch |
| Reihe | Statistics and Computing |
| EAN | 9781493939244 |
| Bestell-Nr | 49393924UA |
In this book, Graham Wills bridges the gap between the art and the science of visually representing data. He does not simply give rules and advice, but bases these on general principles and provide a clear path between them.
Art, or Science? Which of these is the right way to think of the field of visualization? This is not an easy question to answer, even for those who have many years experience in making graphical depictions of data with a view to help people understand it and take action. In this book, Graham Wills bridges the gap between the art and the science of visually representing data. He does not simply give rules and advice, but bases these on general principles and provide a clear path between them
This book is concerned with the graphical representation of time data and is written to cover a range of different users. A visualization expert designing tools for displaying time will find it valuable, but so also should a financier assembling a report in a spreadsheet, or a medical researcher trying to display gene sequences using a commercial statistical package.
Inhaltsverzeichnis:
History.- Framework.- Designing Visualizations.- Types of Data.- Time as a Coordinate.- Coordinate Systems, Transformations, Faceting, and Axes.- Aesthetics.- Transformations.- Interactivity.- Topics in Time.- Gallery of Figures.
Rezension:
From the reviews:
"This book begins by noting that visualization, a word which has come to mean the graphical representation of data, has both scientific and artistic aspects. ... This book provides the foundation for the training and effort which ... will certainly move us some way along that path. ... this is the first book on visualization devoted specifically to data which is recorded over time. ... the graphs in this book are beautiful." (David J. Hand, International Statistical Review, Vol. 80 (3), 2012)
