Pro Data Visualization Using R and JavaScript

Pro Data Visualization using R and JavaScript makes the R language approachable, and promotes the idea of data gathering and analysis. You'll see how to use R to interrogate and analyze your data, and then use the D3 JavaScript library to format and display that data in an elegant, informative, and interactive way. You will learn how to gather data effectively, and also how to understand the philosophy and implementation of each type of chart, so as to be able to represent the results visually. With the popularity of the R language, the art and practice of creating data visualizations is no longer the preserve of mathematicians, statisticians, or cartographers. As technology leaders, we can gather metrics around what we do and use data visualizations to communicate that information. Pro Data Visualization using R and JavaScript combines the power of the R language with the simplicity and familiarity of JavaScript to display clear and informative data visualizations. Gathering and analyzing empirical data is the key to truly understanding anything. We can track operational metrics to quantify the health of our products in production. We can track quality metrics of our projects, and even use our data to identify bad code. Visualizing this data allows anyone to read our analysis and easily get a deep understanding of the story the data tells. What you’ll learn A rich understanding of how to gather, and analyze empirical data How to tell a story with data using data visualizations What types of data visualizations are best to use for the story that you want to tell with your data A comprehensive introduction to the R language, covering all the essentials Exploration of how to construct interactive data visualizations using JavaScript and JavaScript libraries Who this book is for Developers at all levels interested in data visualization, beginning to intermediate engineering managers, statisticians, mathematicians, economists and any others interested in data visualization. Table of Contents Techniques for Data Visualization The R Language A Deeper Dive into R Data Visualization with D3 Visualizing Spatial Information from Access Logs (Data Maps) Visualizing Defects over Time (Time Series) Bar Charts Correlation Analysis with Team Dynamics (Scatterplot and Bubble Chart) Balancing Delivery with Quality (Parallel Coordinates Chart)

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Data Visualisation with R

This book introduces readers to the fundamentals of creating presentation graphics using R, based on 111 detailed and complete scripts. It shows how bar and column charts, population pyramids, Lorenz curves, box plots, scatter plots, time series, radial polygons, Gantt charts, heat maps, bump charts, mosaic and balloon charts, and a series of different thematic map types can be created using R’s Base Graphics System. Every example uses real data and includes step-by-step explanations of the figures and their programming. This second edition contains additional examples for cartograms, chord-diagrams and networks, and interactive visualizations with Javascript. The open source software R is an established standard and a powerful tool for various visualizing applications, integrating nearly all technologies relevant for data visualization. The basic software, enhanced by more than 14000 extension packs currently freely available, is intensively used by organizations including Google, Facebook and the CIA. The book serves as a comprehensive reference guide to a broad variety of applications in various fields. This book is intended for all kinds of R users, ranging from experts, for whom especially the example codes are particularly useful, to beginners, who will find the finished graphics most helpful in learning what R can actually deliver.

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Pro JavaScript Performance

Performance is a hugely important area of web development. If your site runs slowly, users are going to leave, and the problem only grows as your site gets more popular. Pro JavaScript Performance gives you the tools you need to keep your sites smooth and responsive no matter how many users you have. Best practices are changing or becoming redefined continually because of changes and optimizations at the interpreter level, and differences in system configuration, and network speeds. This is exacerbated by the quickened release schedule that most browsers have adopted. Just as important as following best practices is the ability to measure your own performance, so that you can adjust as times change, and so that you can note the subtle nuances in your own code and define your own best practices by your own observations. This book gives you the tools to observe and track the performance of your web applications over time from multiple perspectives, so that you are always aware of, and can fix, all aspects of your performance.

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Beginning R 4

Learn how to use R 4, write and save R scripts, read in data files, use built-in functions, and write custom statistical functions. This in-depth tutorial includes key R 4 features such as a new color palette for charts, an enhanced reference counting system, and normalization of matrix and array types where matrix objects will formally inherit from the array class, eliminating many inconsistencies. Each chapter starts with a list of learning outcomes and concludes with a summary of any R functions introduced in that chapter, a list of specific cited references for more reading, and some exercises to test your new knowledge. The text opens with a hands-on installation of R (and a limited number of packages) for both Windows and macOS. The bulk of the book is an introduction to statistical methods (a non-proof-based introduction) that relies heavily on R (and R visualizations) to understand, motivate, and perform statistical outcomes. Beginning R 4 shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. Additionally, the text comprehensively includes learning outcomes for Texas common course number Math 1342 (elementary statistical methods). What You Will Learn Acquire and install R Import and export data and scripts Analyze data and generate graphics Program in R to write custom functions Use R for interactive statistical explorations Conduct bootstrapping and other advanced techniques Who This Book Is For Programmers and data analysts who are new to R. Some prior experience in programming is recommended.

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Current Index to Statistics Applications Methods and Theory

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Business Periodicals Index

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Index to IEEE Publications

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Biomedical Image Processing and Biomedical Visualization

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Publications Bulletin

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Interactions

A magazine for designers of interactive products.

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Government Reports Announcements Index

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Research publications and professional activities

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Expanding the Role of Medical Physics in Nuclear Medicine

In recent years the field of nuclear medicine has been undergoing a renaissance. The widespread application of SPECT imaging and slow diffusion of PET techniques have revitalized nuclear imaging. At the same time rapid developments in radiopharmaceuticals have produced new imaging methods. These developments have increased the need for well-trained medical physicists to work in the university setting and to assist smaller hospitals with implementing these techniques.

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Research resources reporter

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Seminars in Family Medicine

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Globecom 99

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13th International Parallel Processing Symposium 10th Symposium on Parallel and Distributed Processing

Contains 113 papers presented at the April 1999 meetings. Arrangement is in 21 sections covering such topics as: algorithmic paradigms and primitives; latency tolerance and performance modeling; communication, run-time systems; scalable computing; communication and protocols for clusters; communication libraries; routing and broadcasting; miscellaneous architecture; advanced software for applications support; scientific engineering systems; signal processing; data mining and databases; and biological and discrete systems. Also included are abstracts of the panel discussions and the two keynote addresses from each of the symposiums. No subject index. Annotation copyrighted by Book News, Inc., Portland, OR

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Directory of Graduate Research

Faculties, publications and doctoral theses in departments or divisions of chemistry, chemical engineering, biochemistry and pharmaceutical and/or medicinal chemistry at universities in the United States and Canada.

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Energy Research Abstracts

Includes all works deriving from DOE, other related government-sponsored information and foreign nonnuclear information.

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2002 IEEE International Conference on Data Mining

Consists of 72 full papers and 49 short papers from the December 2002 conference on the design, analysis, and implementation of data mining theory, systems, and applications. Topics of the full papers include evolutionary time series segmentation for stock data mining, cluster merging and splitting

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