data points visualization that means something

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Data Points

Author : Nathan Yau
ISBN : 9781118654934
Genre : Computers
File Size : 78. 20 MB
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A fresh look at visualization from the author of VisualizeThis Whether it's statistical charts, geographic maps, or the snappygraphical statistics you see on your favorite news sites, the artof data graphics or visualization is fast becoming a movement ofits own. In Data Points: Visualization That Means Something,author Nathan Yau presents an intriguing complement to hisbestseller Visualize This, this time focusing on thegraphics side of data analysis. Using examples from art, design,business, statistics, cartography, and online media, he exploresboth standard-and not so standard-concepts and ideas aboutillustrating data. Shares intriguing ideas from Nathan Yau, author of VisualizeThis and creator of flowingdata.com, with over 66,000subscribers Focuses on visualization, data graphics that help viewers seetrends and patterns they might not otherwise see in a table Includes examples from the author's own illustrations, as wellas 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 DataPoints: Visualization That Means Something.

Flowingdata Com Data Visualization Set

Author : Nathan Yau
ISBN : 9781118919880
Genre : Computers
File Size : 29. 51 MB
Format : PDF
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Visualize This is a guide on how to visualize and tellstories with data, providing practical design tips complementedwith step-by-step tutorials. It begins with a description of thehuge growth of data and visualization in industry, news, and gov'tand opportunities for those who tell stories with data. Logicallyit moves on to actual stories in data-statistical ones with trendsand human stories. the technical part comes up quickly with how togather, parse and format data with Python, R, Excel, Google docs,etc and details tools to visualize data-native graphics for the Weblike ActionScript, Flash libraries, PHP, JavaScript, CSS, HTML.Every chapter provides an example as well. Patterns over time andkinds of data charts are followed by proportions, chart types andexamples. Next, examples and descriptions of outliers and how toshow them, different kinds of maps, how to guide your readers andexplain the data "in the visualization". The book ends with avalue-add appendix on graphical perception. Data Points focuses on the approach to visualization anddata. Visualization is a medium that can be used as a tool, art, away to tell stories, etc., Data Points guides readersthrough making data approachable through visualization techniquesand best practices. The focus is on designing with a purpose inmind. Data Points discusses why recipes (from the rules)work and expands on how readers can make their own recipes. Thebook is example-driven, featuring work from people in areas of art,design, business, statistics, computer science, cartography, andonline media, as well as many of the author's own illustrations.The major sections of the book cover: Visualization as Medium -- In the same way not all movies aredocumentaries, not all visualization is about optimal visualperception. Data Representation -- There are rules across allvisualization applications, such as the use of appropriate shapesto accurately represent values. Design with Purpose -- Rules can be broken though. It alldepends on who and what you're designing for. Data Points digs deep into the foundations of datavisualization: Understanding Data and Visualization Representing Data Exploring Data Visually Designing for an Audience Visualizing with Clarity Putting Everything Into Practice with Tools and Resources

The New Abcs Of Research

Author : Ben Shneiderman
ISBN : 9780198758839
Genre : Communication in science
File Size : 38. 84 MB
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The problems we face in the 21st century require innovative thinking from all of us. Be it students, academics, business researchers of government policy makers. Hopes for improving our healthcare, food supply, community safety and environmental sustainability depend on the pervasive application of research solutions. The research heroes who take on the immense problems of our time face bigger than ever challenges, but if they adopt potent guiding principles and effective research lifecycle strategies, they can produce the advances that will enhance the lives of many people. These inspirational research leaders will break free from traditional thinking, disciplinary boundaries, and narrow aspirations. They will be bold innovators and engaged collaborators, who are ready to lead, yet open to new ideas, self-confident, yet empathetic to others. In this book, Ben Shneiderman recognizes the unbounded nature of human creativity, the multiplicative power of teamwork, and the catalytic effects of innovation. He reports on the growing number of initiatives to promote more integrated approaches to research so as to promote the expansion of these efforts. It is meant as a guide to students and junior researchers, as well as a manifesto for senior researchers and policy makers, challenging widely-held beliefs about how applied innovations evolve and how basic breakthroughs are made, and to help plotting the course towards tomorrow's great advancements.

Data Visualizations And Infographics

Author : Sarah K. C. Mauldin
ISBN : 9781442243880
Genre : Language Arts & Disciplines
File Size : 24. 40 MB
Format : PDF, ePub, Mobi
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This complete how-to guidebook provides you with the tools and inspiration you need to use infographics and data visualization techniques in your library to knock your audience’s socks off as you tell your story in a visual format that can be consumed and understood at a glance.

Data Visualization

Author : Lauren Magnuson
ISBN : 9781442271128
Genre : Language Arts & Disciplines
File Size : 77. 25 MB
Format : PDF, Mobi
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Data Visualization: A Guide to Visual Storytelling for Libraries is a practical guide to the skills and tools needed to create beautiful and meaningful visual stories through data visualization. Learn how to sift through complex datasets to better understand a variety of metrics, such as trends in user behavior and electronic resource usage, return on investment (ROI) and impact metrics, and data about library collections and repositories. A 20-page color insert showcases an extensive selection of visualizations using a variety of technologies and programming languages that can serve as inspiration for creating your own visualizations. Understanding and communicating trends from your organization’s data is essential. Whether you are looking to make more informed decisions by visualizing organizational data, or to tell the story of your library’s impact on your community, this book will give you the tools to make it happen.

Data Visualization Made Simple

Author : Kristen Sosulski
ISBN : 9781351380775
Genre : Business & Economics
File Size : 88. 77 MB
Format : PDF, Kindle
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Data Visualization Made Simple is a practical guide to the fundamentals, strategies, and real-world cases for data visualization, an essential skill required in today’s information-rich world. With foundations rooted in statistics, psychology, and computer science, data visualization offers practitioners in almost every field a coherent way to share findings from original research, big data, learning analytics, and more. In nine appealing chapters, the book: examines the role of data graphics in decision-making, sharing information, sparking discussions, and inspiring future research; scrutinizes data graphics, deliberates on the messages they convey, and looks at options for design visualization; and includes cases and interviews to provide a contemporary view of how data graphics are used by professionals across industries Both novices and seasoned designers in education, business, and other areas can use this book’s effective, linear process to develop data visualization literacy and promote exploratory, inquiry-based approaches to visualization problems.

R Data Visualization Cookbook

Author : Atmajitsinh Gohil
ISBN : 9781783989515
Genre : Computers
File Size : 48. 61 MB
Format : PDF, ePub, Docs
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If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected.

Web And Network Data Science

Author : Thomas W. Miller
ISBN : 9780133887648
Genre : Computers
File Size : 70. 62 MB
Format : PDF, Kindle
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Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.

Modeling Techniques In Predictive Analytics With Python And R

Author : Thomas W. Miller
ISBN : 9780133892147
Genre : Computers
File Size : 88. 76 MB
Format : PDF, ePub
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Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Modeling Techniques In Predictive Analytics

Author : Thomas W. Miller
ISBN : 9780133886191
Genre : Computers
File Size : 75. 91 MB
Format : PDF, Kindle
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To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

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