Books: 37

Data Visualization

CoverTitleYear
100 Examples
This book introduces readers to the fundamentals of creating presentation graphics using R, based on 100 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, more » 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. 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 7000 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. « less
2017
Learn how to build an interactive source code analytics system using Roslyn and JavaScript. This concise 150 page book will help you create and use practical code analysis tools utilizing the new features of Microsoft’s Roslyn compiler to understand the health of your code and identify parts of the code more » for refactoring. Source code is one of the biggest assets of a software company. However if not maintained well, it can become a big liability. As source code becomes larger. more complex and accessed via the cloud, maintaining code quality becomes even more challenging. The author provides straightforward tools and advice on how to manage code quality in this new environment. Roslyn exposes a set of APIs which allow developers to parse their C# and VB.NET code and drastically lower the barrier to entry for Meta programming in .NET. Roslyn has a dedicated set of APIs for creating custom refactoring for integrating with Visual Studio. This title will show readers how to use Roslyn along with industry standard JavaScript visualization APIs like HighCharts, D3.js etc to create a scalable and highly responsive source code analytics system. What You Will Learn * Understand the Roslyn Syntax API * Use Data Visualization techniques to assist code analysis process visually * Code health monitoring matrices (from the standard of Code Query Language) * Code mining techniques to identify design patterns used in source code * Code forensics techniques to identify probable author of a given source code * Techniques to identify duplicate/near duplicate code Who This Book is For .NET Software Developers and Architects « less
2017
Well-designed graphics are frequently the best way to understand data sets and to communicate results. Gnuplot, the most popular open-source tool to plot and visualize data, has long been the preferred choice for scientists and data analysts for creating publication-quality graphs. The latest version, more » gnuplot 5, adds further capabilities, including new plot types, improved text and color handling, and support for interactive, web-based display formats. Although gnuplot includes comprehensive reference documentation, it can be difficult to fully master this tool. Gnuplot in Action, Second Edition is a major revision of this popular and authoritative guide for developers, engineers, and scientists who want to learn and use gnuplot effectively. The book starts with a tutorial introduction for readers new to gnuplot. Next it provides a systematic overview of gnuplot's core features, and full coverage of gnuplot's advanced capabilities, such as 3D graphics and false-color plots. Experienced readers will appreciate the discussion of gnuplot's new features for working with color and customized plotting styles, as well as the hints for improved workflow and user configurations. The book concludes with chapters on graphical effects and general techniques for understanding data with graphs. « less
2016
Take business intelligence delivery to a new level that is interactive, engaging, even fun, all while driving commercial success through sound decision making. Do this through the power of visualization using this updated edition covering new features and added support for visualization in Excel 2016, more » and describing the latest developments in Get & Transform and DAX. The example data set has also been updated to demonstrate all that Microsoft's self-service business intelligence suite is now capable of. Data Visualization in Excel 2016: Power View, 3D Maps, Get & Transform, and Power BI, 2nd Edition helps in harnessing the power of Microsoft’s flagship, self-service business intelligence suite to deliver compelling and interactive insight with remarkable ease. Learn the essential techniques needed to enhance the look and feel of reports and dashboards so that you can seize your audience’s attention and provide them with clear and accurate information. Also learn to integrate data from a variety of sources and create coherent data models displaying clear metrics and attributes. Power View is Microsoft's ground-breaking tool for ad-hoc data visualization and analysis. It's designed to produce elegant and visually arresting output. It's also built to enhance user experience through polished interactivity. Power Map is a similarly powerful mechanism for analyzing data across geographic and political units. Get & Transform lets you load, shape and streamline data from multiple sources. Power Pivot can extend and develop data into a dynamic model. Power BI allows you to share your findings with colleagues, and present your insights to clients. Data Visualization in Excel 2016: Power View, 3D Maps, Get & Transform, and Power BIhelps you master this suite of powerful tools from Microsoft. You'll learn to identify data sources, and to save time by preparing your underlying data correctly. You'll also learn to deliver your powerful visualizations and analyses through the cloud to PCs, tablets and smartphones. * Simple techniques take raw data and convert it into information. * Slicing and dicing metrics delivers interactive insight. * Visually arresting output grabs and focuses attention on key indicators. What You Will Learn * Produce designer output that will astound your bosses and peers. * Drive business intelligence from Excel using BI in the Cloud. * Gather source data from corporate and public sources. * Integrate charts, maps, and tables to deliver visually stunning information. * Discover new insights as you chop and tweak your data as never before. * Adapt delivery to mobile devices. * Outshine competing products and enhance existing skills. Who This Book Is For Data Visualization in Excel 2016: Power View, 3D Maps, Get & Transform, and Power BI, 2nd Edition is written for any Power BI Desktop, Excel or SharePoint user. Business Intelligence developers, power users, IT managers, finance experts, and more can use this book to outshine the competition by producing high-impact business intelligence reporting on a variety of devices from a variety of sources. « less
2016
Prevalent types of data in scientific visualization are volumetric data, vector field data, and particle-based data. Particle data typically originates from measurements and simulations in various fields, such as life sciences or physics. The particles are often visualized directly, that is, by simple more » representants like spheres. Interactive rendering facilitates the exploration and visual analysis of the data. With increasing data set sizes in terms of particle numbers, interactive high-quality visualization is a challenging task. This is especially true for dynamic data or abstract representations that are based on the raw particle data. This book covers direct particle visualization using simple glyphs as well as abstractions that are application-driven such as clustering and aggregation. It targets visualization researchers and developers who are interested in visualization techniques for large, dynamic particle-based data. Its explanations focus on GPU-accelerated algorithms for high-performance rendering and data processing that run in real-time on modern desktop hardware. Consequently, the implementation of said algorithms and the required data structures to make use of the capabilities of modern graphics APIs are discussed in detail. Furthermore, it covers GPU-accelerated methods for the generation of application-dependent abstract representations. This includes various representations commonly used in application areas such as structural biology, systems biology, thermodynamics, and astrophysics. « less
2016
*** Key Features *** * Predict and use a probabilistic graphical models (PGM) as an expert system * Comprehend how your computer can learn Bayesian modeling to solve real-world problems * Know how to prepare data and feed the models by using the appropriate algorithms from the appropriate R package *** more » Book Description *** Probabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov networks. R has many packages to implement graphical models. We'll start by showing you how to transform a classical statistical model into a modern PGM and then look at how to do exact inference in graphical models. Proceeding, we'll introduce you to many modern R packages that will help you to perform inference on the models. We will then run a Bayesian linear regression and you'll see the advantage of going probabilistic when you want to do prediction. Next, you'll master using R packages and implementing its techniques. Finally, you'll be presented with machine learning applications that have a direct impact in many fields. Here, we'll cover clustering and the discovery of hidden information in big data, as well as two important methods, PCA and ICA, to reduce the size of big problems. *** What you will learn *** * Understand the concepts of PGM and which type of PGM to use for which problem * Tune the model's parameters and explore new models automatically * Understand the basic principles of Bayesian models, from simple to advanced * Transform the old linear regression model into a powerful probabilistic model * Use standard industry models but with the power of PGM * Understand the advanced models used throughout today's industry * See how to compute posterior distribution with exact and approximate inference algorithms *** About the Author *** David Bellot is a PhD graduate in computer science from INRIA, France, with a focus on Bayesian machine learning. He was a postdoctoral fellow at the University of California, Berkeley, and worked for companies such as Intel, Orange, and Barclays Bank. He currently works in the financial industry, where he develops financial market prediction algorithms using machine learning. He is also a contributor to open source projects such as the Boost C++ library. *** Table of Contents *** 1. Probabilistic Reasoning 2. Exact Inference 3. Learning Parameters 4. Bayesian Modeling – Basic Models 5. Approximate Inference 6. Bayesian Modeling – Linear Models 7. Probabilistic Mixture Models 8. Appendix « less
R
2016
KEY FEATURES * Arm yourself with an arsenal of advanced chart types and geocoding to efficiently and engagingly present information * Map a grid over a network node diagram and use that grid to demonstrate loads, processing time, and more in Tableau * Integrate R with Tableau by utilizing R functions, more » libraries, and saved models BOOK DESCRIPTION Tableau has emerged as one of the most popular Business Intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. This book will empower you to become a master in Tableau by exploiting the many new features introduced in Tableau 10.0. You will embark on this exciting journey by getting to know the valuable methods of utilizing advanced calculations to solve complex problems. These techniques include creative use of different types of calculations such as row-level, aggregate-level, and more. You will discover how almost any data visualization challenge can be met in Tableau by getting a proper understanding of the tool's inner workings and creatively exploring possibilities. You'll be armed with an arsenal of advanced chart types and techniques to enable you to efficiently and engagingly present information to a variety of audiences through the use of clear, efficient, and engaging dashboards. Explanations and examples of efficient and inefficient visualization techniques, well-designed and poorly designed dashboards, and compromise options when Tableau consumers will not embrace data visualization will build on your understanding of Tableau and how to use it efficiently. By the end of the book, you will be equipped with all the information you need to create effective dashboards and data visualization solutions using Tableau. WHAT YOU WILL LEARN * Create a worksheet that can display the current balance for any given period in time * Recreate a star schema from in a data warehouse in Tableau * Combine level of detail calculations with table calculations, sets, and parameters * Create custom polygons to build filled maps for area codes in the USA * Visualize data using a set of analytical and advanced charting techniques * Know when to use Tableau instead of PowerPoint * Build a dashboard and export it to PowerPoint ABOUT THE AUTHOR David Baldwin has provided consulting in the business intelligence sector for 17 years. His experience includes Tableau training and consulting, developing BI solutions, project management, technical writing, and the web and graphic design. His vertical experience includes financial, healthcare, human resource, aerospace, energy, education, government, and entertainment industries. As a Tableau trainer and consultant, David enjoys serving a variety of clients throughout the USA. Tableau provides David a platform that collates his broad experience into a skill set that can service a diverse client base. TABLE OF CONTENTS 1. Getting Up to Speed – a Review of the Basics 2. All about Data – Getting Your Data Ready 3. All about Data – Joins, Blends, and Data Structures 4. All about Data – Data Densification, Cubes, and Big Data 5. Table Calculations 6. Level of Detail Calculations 7. Beyond the Basic Chart Types 8. Mapping 9. Tableau for Presentations 10. Visualization Best Practices and Dashboard Design 11. Improving Performance 12. Interacting with Tableau Server 13. R Integration « less
2016
Your indispensable guide to mastering the efficient use of D3.js in professional-standard data visualization projects. You will learn what data visualization is, how to work with it, and how to think like a D3.js expert, both practically and theoretically. Practical D3.js does not just show you how more » to use D3.js, it teaches you how to think like a data scientist and work with the data in the real world. In Part One, you will learn about theories behind data visualization. In Part Two, you will learn how to use D3.js to create the best charts and layouts. Uniquely, this book intertwines the technical details of D3.js with practical topics such as data journalism and the use of open government data. Written by leading data scientists Tarek Amr and Rayna Stamboliyska, this book is your guide to using D3.js in the real world – add it to your library today. You Will Learn: * How to think like a data scientist and present data in the best way * What structure and design strategies you can use for compelling data visualization * How to use data binding, animations and events, scales, and color pickers * How to use shapes, path generators, arcs and polygons Who This Book is For: This book is for anyone who wants to learn to master the use of D3.js in a practical manner, while still learning the important theoretical aspects needed to enable them to work with their data in the best possible way. « less
2016
Illustrate your data in a more interactive way by implementing data visualization principles and creating visual stories using Tableau
***** About This Book ***** * Use data visualization principles to help you to design dashboards that enlighten and support business decisions * Integrate your data to provide mashed-up dashboards * Connect to various data sources and understand what data is appropriate for Tableau Public * Understand more » chart types and when to use specific chart types with different types of data ***** Who This Book Is For ***** Data scientists who have just started using Tableau and want to build on the skills using practical examples. Familiarity with previous versions of Tableau will be helpful, but not necessary. ***** What You Will Learn ***** * Customize your designs to meet the needs of your business using Tableau * Use Tableau to prototype, develop, and deploy the final dashboard * Create filled maps and use any shape file * Discover features of Tableau Public, from basic to advanced * Build geographic maps to bring context to data * Create filters and actions to allow greater interactivity to Tableau Public visualizations and dashboards * Publish and embed Tableau visualizations and dashboards in articles ***** In Detail ***** With increasing interest for data visualization in the media, businesses are looking to create effective dashboards that engage as well as communicate the truth of data. Tableau makes data accessible to everyone, and is a great way of sharing enterprise dashboards across the business. Tableau is a revolutionary toolkit that lets you simply and effectively create high-quality data visualizations. This course starts with making you familiar with its features and enable you to develop and enhance your dashboard skills, starting with an overview of what dashboard is, followed by how you can collect data using various mathematical formulas. Next, you'll learn to filter and group data, as well as how to use various functions to present the data in an appealing and accurate way. In the first module, you will learn how to use the key advanced string functions to play with data and images. You will be walked through the various features of Tableau including dual axes, scatterplot matrices, heat maps, and sizing.In the second module, you'll start with getting your data into Tableau, move onto generating progressively complex graphics, and end with the finishing touches and packaging your work for distribution. This module is filled with practical examples to help you create filled maps, use custom markers, add slider selectors, and create dashboards. You will learn how to manipulate data in various ways by applying various filters, logic, and calculating various aggregate measures. Finally, in the third module, you learn about Tableau Public using which allows readers to explore data associations in multiple-sourced public data, and uses state-of-the-art dashboard and chart graphics to immerse the users in an interactive experience. In this module, the readers can quickly gain confidence in understanding and expanding their visualization, creation knowledge, and quickly create interesting, interactive data visualizations to bring a richness and vibrancy to complex articles. The course provides a great overview for beginner to intermediate Tableau users, and covers the creation of data visualizations of varying complexities. ***** Style and approach ***** The approach will be a combined perspective, wherein we start by performing some basic recipes and move on to some advanced ones. Finally, we perform some advanced analytics and create appealing and insightful data stories using Tableau Public in a step-by-step manner. « less
2016
Unchain your data from the desktop with responsive visualizations Building Responsive Data Visualization for the Web is a handbook for any front-end development team needing a framework for integrating responsive web design into the current workflow. Written by a leading industry expert and design lead more » at Starbase Go, this book provides a wealth of information and practical guidance from the perspective of a real-world designer. You'll walk through the process of building data visualizations responsively as you learn best practices that build upon responsive web design principles, and get the hands-on practice you need with exercises, examples, and source code provided in every chapter. These strategies are designed to be implemented by teams large and small, with varying skill sets, so you can apply these concepts and skills to your project right away. Responsive web design is the practice of building a website to suit base browser capability, then adding features that enhance the experience based on the user's device's capabilities. Applying these ideas to data produces visualizations that always look as if they were designed specifically for the device through which they are viewed. This book shows you how to incorporate these principles into your current practices, with highly practical hands-on training. * Examine the hard data surrounding responsive design * Master best practices with hands-on exercises * Learn data-based document manipulation using D3.js * Adapt your current strategies to responsive workflows Data is growing exponentially, and the need to visualize it in any context has become crucial. Traditional visualizations allow important data to become lost when viewed on a small screen, and the web traffic speaks for itself – viewers repeatedly demonstrate their preference for responsive design. If you're ready to create more accessible, take-anywhere visualizations, Building Responsive Data Visualization for the Web is your tailor-made solution. « less
2015