Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization. Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value Understand the importance of redundant coding to ensure you provide key information in multiple ways Use the book’s visualizations directory, a graphical guide to commonly used types of data visualizations Get extensive examples of good and bad figures Learn how to use figures in a document or report and how employ them effectively to tell a compelling story

Data visualization involves graphical and visual tools used in data analysis and decision making. The emphasis in this book is on recent trends and applications of visualization tools using conventional and big data. These tools are widely used in data visualization and quality improvement to analyze, enhance, and improve the quality of products and services. Data visualization is an easy way to obtain a first look at the data visually. The book provides a collection of visual and graphical tools widely used to gain an insight into the data before applying more complex analysis. The focus is on the key application areas of these tools including business process improvement, business data analysis, health care, finance, manufacturing, engineering, process improvement, and Lean Six Sigma. The key areas of application include data and data analysis concepts, recent trends in data visualization and ÒBig Data,Ó widely used charts and graphs and their applications, analysis of the relationships between two or more variables graphically using scatterplots, bubble graphs, matrix plots, etc., data visualization with big data, computer applications and implementation of widely used graphical and visual tools, and computer instructions to create the graphics presented along with the data files.

An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions

Visualizing the data is an essential part of any data analysis. Modern computing developments have led to big improvements in graphic capabilities and there are many new possibilities for data displays. This book gives an overview of modern data visualization methods, both in theory and practice. It details modern graphical tools such as mosaic plots, parallel coordinate plots, and linked views. Coverage also examines graphical methodology for particular areas of statistics, for example Bayesian analysis, genomic data and cluster analysis, as well software for graphics.

This book discusses data and information visualization techniques-the decision-making tools with applications in health care, finance, manufacturing engineering, process improvement, product design, and others. These tools are an excellent means of viewing the current state of the process and improving them. The initial chapters discuss data analysis, the current trends in visualization, the concepts of systems and processes from which data are collected. The second part is devoted to quality tools-a set of graphical and information visualization tools in data analysis, decision-making, and Lean Six-Sigma quality. The eight basic tools of quality discussed are the Process Maps, Check Sheets, Histograms, Scatter Diagrams, Run Charts, Control Charts, Cause-and-Effect Diagrams, and Pareto Charts. The new quality tools presented are the Affinity, Tree, and Matrix Diagrams, Interrelationship Digraph, Prioritizing Matrices, Process Decision Program Chart, and Activity Network Diagram along with Quality Function Deployment (QFD) and Multivari Charts.

This book contains 33 papers presented at the Third Joint Visualization Symposium of the Eurographics Association and the Technical Committee on Visualization and Graphics of the IEEE Computer Society. The main topics treated are: visualization of geoscience data; multi-resolution and adaptive techniques; unstructured data, multi-scale and visibility; flow visualization; biomedical applications; information visualization; object representation; volume rendering; information visualization applications; and automotive applications.