Data Points: Visualization That Means Something

Description

A fresh look at visualization from the author of Visualize This Whether it's statistical charts, geographic maps, or the snappy graphical statistics you see on your favorite news sites, the art of data graphics or visualization is fast becoming a movement of its own. In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data. Shares intriguing ideas from Nathan Yau, author of Visualize This and creator of flowingdata.com, with over 66,000 subscribers Focuses on visualization, data graphics that help viewers see trends and patterns they might not otherwise see in a table Includes examples from the author's own illustrations, as well as from professionals in statistics, art, design, business, computer science, cartography, and more Examines standard rules across all visualization applications, then explores when and where you can break those rules Create visualizations that register at all levels, with Data Points: Visualization That Means Something.

Get the book

Amazon.com

Search the book

eBay.com

Search the book

Other editions

• 

  Data Points: Visualization That Means Something

  • 2013-04-15
  • 8 pages
  • Paperback
  • John Wiley & Sons

Similar books

• 

  Visualize This: The FlowingData Guide to Design, Visualization, and Statistics

  By Nathan Yau

  In this book, he offers you dozens of ideas for telling your story with data presented in creative, visual ways. Open the book, open your mind, and discover an almost endless variety of ways to give your data new dimensions.

• 

  Spatial Point Patterns: Methodology and Applications with R

  By Adrian Baddeley, Ege Rubak, Rolf Turner

  ... N. Funwi-Gabga, D.J. Gerrard, A. Green, T. Griffin, U. Hahn, A.H. Hickman, S.P. Hubbell, J. Huntington, V. Isham, ... A. Penttinen, N. Picard, D. Stoyan, M. Tanemura, S. Voss, R. Waagepetersen, K.P. Watkins, and H. Wendrock.

• 

  Ubiquitous Security: First International Conference, UbiSec 2021, Guangzhou, China, December 28-31, 2021, Revised Selected Papers

  By Kim-Kwang Raymond Choo, Bruno Crispo, Guojun Wang

  Anomalous data points are therefore easily separable or isolated from other normal data points, ... Data points are isolated by randomly and recursively splitting the dataset until each partition contains only a single data point or ...

• 

  Style and Ethics of Communication in Science and Engineering

  By Jay Dowell Humphrey, Jeffrey W. Holmes

  In addition to presenting methods for writing clearly and concisely and improving oral presentations, this compact book provides practical guidelines for preparing theses, dissertations, journal papers for publication, and proposals for ...

• 

  Statistical Applications for Environmental Analysis and Risk Assessment

  By Joseph Ofungwu

  values,and thenjoining theobserved X versus estimated Y datapoints toformthe curve that graphically represents the ... In such cases, the scatterplot of individual data points typically coalesces into an amorphous data mass that is ...

• 

  Computational Intelligence Paradigms: Theory & Applications using MATLAB

  By S. Sumathi, Surekha Paneerselvam

  9.6.4 Subtractive Clustering Subtractive clustering is based on a measure of the density of data points in the feature space. The theme behind subtractive clustering is to determine regions in the feature space with high densities of ...

• 

  Super Founders: What Data Reveals About Billion-Dollar Startups

  By Ali Tamaseb

  You will also hear the stories of the early days of billion-dollar startups first-hand.

• 

  Finite Element Mesh Generation

  By Daniel S.H. Lo

  Freitag LA, Ollivier-Gooch C (1996) A comparison of tetrahedral mesh improvement techniques, Proceedings of the Fifth International Meshing Roundtable, Sandia National Laboratories, 87–108. Freitag LA, Ollivier-Gooch C (1997) ...

• 

  Deep Learning in Visual Computing: Explanations and Examples

  By Hassan Ugail

  Often data may not be separable, and so a penalty for having a data point on the “wrong” side of the hyperplane must be ... Then, a large C heavily penalises misclassified points while encouraging hyperplanes that fit the training data ...

• 

  Applied Calculus

  By Geoffrey C. Berresford, Andrew M. Rockett

  Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). ... EnvirOnMEntAL sciEncEs: Maximum Yield A peach grower finds that if he plants 40 trees per acre, each tree will yield 60 bushels ...