Effective Data Visualization

Effective Data Visualization

Delivered in Evergreen’s humorous and approachable style, the book covers the spectrum of graph types available beyond the default options, how to determine which one most appropriately fits specific data stories, and easy steps for ...

Author: Stephanie D. H. Evergreen

Publisher: SAGE Publications

ISBN: 9781544350875

Category: Social Science

Page: 352

View: 361

NOW IN FULL COLOR! Written by sought-after speaker, designer, and researcher Stephanie D. H. Evergreen, Effective Data Visualization shows readers how to create Excel charts and graphs that best communicate their data findings. This comprehensive how-to guide functions as a set of blueprints—supported by both research and the author’s extensive experience with clients in industries all over the world—for conveying data in an impactful way. Delivered in Evergreen’s humorous and approachable style, the book covers the spectrum of graph types available beyond the default options, how to determine which one most appropriately fits specific data stories, and easy steps for building the chosen graph in Excel. Now in full color with new examples throughout, the Second Edition includes a revamped chapter on qualitative data, nine new quantitative graph types, new shortcuts in Excel, and an entirely new chapter on Sharing Your Data With the World, which provides advice on using dashboards. New from Stephanie Evergreen! The Data Visualization Sketchbook provides advice on getting started with sketching and offers tips, guidance, and completed sample sketches for a number of reporting formats. Bundle Effective Data Visualization, 2e, and The Data Visualization Sketchbook, using ISBN 978-1-5443-7178-8!
Categories: Social Science

Data Visualization Exploring and Explaining with Data

Data Visualization  Exploring and Explaining with Data

Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Copyright 2022 Cengage Learning. ... Evergreen, S. D. Effective Data Visualization: The Right Chart for the Right Data.

Author: Jeffrey D. Camm

Publisher: Cengage Learning

ISBN: 9780357631430

Category: Computers

Page: 448

View: 332

DATA VISUALIZATION: Exploring and Explaining with Data is designed to introduce best practices in data visualization to undergraduate and graduate students. The book contains material on effective design, choice of chart type, effective use of color, how to explore data visually, and how to explain concepts and results visually in a compelling way with data. In an increasingly data-driven economy, these concepts are becoming more important for analysts, natural scientists, social scientists, engineers, medical professionals, business professionals, and virtually everyone who needs to interact with data. Indeed, the skills developed in this book will be helpful to all who want to influence with data or be accurately informed by data. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Categories: Computers

Data Visualization For Dummies

Data Visualization For Dummies

Effective data analysis involves learning how to synthesize data, especially big data, into a story and present that story in a way that resonates with the audience This full-color guide shows you how to analyze large amounts of data, ...

Author: Mico Yuk

Publisher: John Wiley & Sons

ISBN: 9781118502921

Category: Computers

Page: 256

View: 262

A straightforward, full-color guide to showcasing data so your audience can see what you mean, not just read about it Big data is big news! Every company, industry, not-for-profit, and government agency wants and needs to analyze and leverage datasets that can quickly become ponderously large. Data visualization software enables different industries to present information in ways that are memorable and relevant to their mission. This full-color guide introduces you to a variety of ways to handle and synthesize data in much more interesting ways than mere columns and rows of numbers. Learn meaningful ways to show trending and relationships, how to convey complex data in a clear, concise diagram, ways to create eye-catching visualizations, and much more! Effective data analysis involves learning how to synthesize data, especially big data, into a story and present that story in a way that resonates with the audience This full-color guide shows you how to analyze large amounts of data, communicate complex data in a meaningful way, and quickly slice data into various views Explains how to automate redundant reporting and analyses, create eye-catching visualizations, and use statistical graphics and thematic cartography Enables you to present vast amounts of data in ways that won't overwhelm your audience Part technical manual and part analytical guidebook, Data Visualization For Dummies is the perfect tool for transforming dull tables and charts into high-impact visuals your audience will notice...and remember.
Categories: Computers

Better Presentations

Better Presentations

DATA VISUALIZATION BOOKS If you want to learn more about data visualization, there are some great books that dive deeper ... Author of two books on data visualization, her latest, Effective Data Visualization: The Right Chart for the ...

Author: Jonathan Schwabish

Publisher: Columbia University Press

ISBN: 9780231542791

Category: Reference

Page: 272

View: 302

Whether you are a university professor, researcher at a think tank, graduate student, or analyst at a private firm, chances are that at some point you have presented your work in front of an audience. Most of us approach this task by converting a written document into slides, but the result is often a text-heavy presentation saddled with bullet points, stock images, and graphs too complex for an audience to decipher—much less understand. Presenting is fundamentally different from writing, and with only a little more time, a little more effort, and a little more planning, you can communicate your work with force and clarity. Designed for presenters of scholarly or data-intensive content, Better Presentations details essential strategies for developing clear, sophisticated, and visually captivating presentations. Following three core principles—visualize, unify, and focus—Better Presentations describes how to visualize data effectively, find and use images appropriately, choose sensible fonts and colors, edit text for powerful delivery, and restructure a written argument for maximum engagement and persuasion. With a range of clear examples for what to do (and what not to do), the practical package offered in Better Presentations shares the best techniques to display work and the best tactics for winning over audiences. It pushes presenters past the frustration and intimidation of the process to more effective, memorable, and persuasive presentations.
Categories: Reference

Data Visualization and Knowledge Engineering

Data Visualization and Knowledge Engineering

Spotting Data Points with Artificial Intelligence Jude Hemanth, Madhulika Bhatia, Oana Geman ... O'Reilly Media Inc, California Evergreen S (2016) Effective data visualization: the right chart for the right data.

Author: Jude Hemanth

Publisher: Springer

ISBN: 9783030257972

Category: Technology & Engineering

Page: 319

View: 393

This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples. Data visualization and engineering has been instrumental in the development of many data-driven products and processes. As such the book promotes basic research on data visualization and knowledge engineering toward data engineering and knowledge. Visual data exploration focuses on perception of information and manipulation of data to enable even non-expert users to extract knowledge. A number of visualization techniques are used in a variety of systems that provide users with innovative ways to interact with data and reveal patterns. A variety of scalable data visualization techniques are required to deal with constantly increasing volume of data in different formats. Knowledge engineering deals with the simulation of the exchange of ideas and the development of smart information systems in which reasoning and knowledge play an important role. Presenting research in areas like data visualization and knowledge engineering, this book is a valuable resource for students, scholars and researchers in the field. Each chapter is self-contained and offers an in-depth analysis of real-world applications. It discusses topics including (but not limited to) spatial data visualization; biomedical visualization and applications; image/video summarization and visualization; perception and cognition in visualization; visualization taxonomies and models; abstract data visualization; information and graph visualization; knowledge engineering; human–machine cooperation; metamodeling; natural language processing; architectures of database, expert and knowledge-based systems; knowledge acquisition methods; applications, case studies and management issues: data administration issues and knowledge; tools for specifying and developing data and knowledge bases using tools based on communication aspects involved in implementing, designing and using KBSs in cyberspace; Semantic Web.
Categories: Technology & Engineering

Foundations of Data Visualization

Foundations of Data Visualization

The effects of visual embellishment on comprehension and memorability of charts. In: Proceedings of the ACM SIGCHI ... Evergreen, S.D.H.: Effective Data Visualization: The Right Chart for the Right Data. SAGE Publications, Thousand Oaks ...

Author: Min Chen

Publisher: Springer Nature

ISBN: 9783030344443

Category: Computers

Page: 389

View: 530

This is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical evidence for such hypotheses. Readers are not instructed to follow a specific theory, but their attention is brought to a broad range of schools of thoughts and different ways of investigating fundamental questions. As such, the book represents the by now most significant collective effort for gathering a large collection of discourses on the foundation of data visualization. Data visualization is a relatively young scientific discipline. Over the last three decades, a large collection of computer-supported visualization techniques have been developed, and the merits and benefits of using these techniques have been evidenced by numerous applications in practice. These technical advancements have given rise to the scientific curiosity about some fundamental questions such as why and how visualization works, when it is useful or effective and when it is not, what are the primary factors affecting its usefulness and effectiveness, and so on. This book signifies timely and exciting opportunities to answer such fundamental questions by building on the wealth of knowledge and experience accumulated in developing and deploying visualization technology in practice.
Categories: Computers

Hands On Data Preprocessing in Python

Hands On Data Preprocessing in Python

Learn how to effectively prepare data for successful data analytics Roy Jafari ... with Data: A Data Visualization Guide for Business Professionals, by Cole Nussbaumer Knaflic, and Effective Data Visualization: The Right Chart for ...

Author: Roy Jafari

Publisher: Packt Publishing Ltd

ISBN: 9781801079952

Category: Computers

Page: 602

View: 415

This book will make the link between data cleaning and preprocessing to help you design effective data analytic solutions Key Features Develop the skills to perform data cleaning, data integration, data reduction, and data transformation Get ready to make the most of your data with powerful data transformation and massaging techniques Perform thorough data cleaning, such as dealing with missing values and outliers Book Description Data preprocessing is the first step in data visualization, data analytics, and machine learning, where data is prepared for analytics functions to get the best possible insights. Around 90% of the time spent on data analytics, data visualization, and machine learning projects is dedicated to performing data preprocessing. This book will equip you with the optimum data preprocessing techniques from multiple perspectives. You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment. This book will provide a comprehensive articulation of data preprocessing, its whys and hows, and help you identify opportunities where data analytics could lead to more effective decision making. It also demonstrates the role of data management systems and technologies for effective analytics and how to use APIs to pull data. By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques; and handle outliers or missing values to effectively prepare data for analytic tools. What you will learn Use Python to perform analytics functions on your data Understand the role of databases and how to effectively pull data from databases Perform data preprocessing steps defined by your analytics goals Recognize and resolve data integration challenges Identify the need for data reduction and execute it Detect opportunities to improve analytics with data transformation Who this book is for Junior and senior data analysts, business intelligence professionals, engineering undergraduates, and data enthusiasts looking to perform preprocessing and data cleaning on large amounts of data will find this book useful. Basic programming skills, such as working with variables, conditionals, and loops, along with beginner-level knowledge of Python and simple analytics experience, are assumed.
Categories: Computers

The Data Visualization Sketchbook

The Data Visualization Sketchbook

Her second book, Effective Data Visualization: The Right Chart for the Right Data, was published in a Second Edition in May 2019. Introduction Why Sketch “Sure, Stephanie, your idea that good visuals.

Author: Stephanie D. H. Evergreen

Publisher: SAGE Publications

ISBN: 9781544350981

Category: Social Science

Page: 136

View: 961

The Data Visualization Sketchbook, the latest addition to bestselling author Stephanie D.H. Evergreen’s arsenal of data viz tools, provides advice on getting started with sketching and offers tips, guidance, and completed sample sketches for a number of reporting formats including a project page, graphs, dashboards, a one-page handout, slide design, and a report structure. Dr. Evergreen shows how sketching gives people the space to think through not just an individual graphic, but how several graphics could fit together in a composition when creating drafts for infographics and dashboards. The book comprises six complete sets of report templates for you to sketch in and plan your own reporting, and it includes full color qualitative and quantitative "Chart Choosers”. This must-have sketchbook helps readers realize mistakes, find solutions quickly, and report data by methods that keep audiences engaged and informed.
Categories: Social Science

Social Research Methods

Social Research Methods

1 What is data visualization? b Discuss whether (or how) the visualization 2 Why are data visualizations valuable for may be ... Evergreen, Stephanie D. H. (2017) Effective Data Visualization: The Right Chart for the Right Data.

Author: Sigmund Grønmo

Publisher: SAGE

ISBN: 9781526485540

Category: Reference

Page: 592

View: 804

Structured around one of the concepts students struggle with the most—the research question—this book begins with how to understand the role of good questions before demonstrating how questions underpin good research designs and how social research can be framed as asking and answering questions. Perfect for undergraduate students new to methods, it teaches students how qualitative, quantitative, and mixed methods research can be used to answer these questions. "An incredibly resourceful book that contains a forensic insight into social research methods, offering the full range of contemporary approaches. Students will find particular value in the accessibility and detail of the text. Each chapter provides a set of learning outcomes, study questions and further reading." - Dr Ruth McAreavey, Newcastle University Supported by a website that maps online resources to key stages of the learning process, it helps students: - Understand the scientific method - Learn the vocabulary of social science research - Plan and design research - Practice with and interpret data - Explore social science literature and improve assignments with good citations - Improve critical thinking. - Extensive visualizations, overviews, examples, exercises, and other learning features, make this the perfect introductory text to build confidence and best practice around research methods.
Categories: Reference

Embodying Data

Embodying Data

Effective data visualization: The right chart for the right data. Sage. Eyre, C., & Baines, J. (1989). Interactions between orality and literacy in ancient Egypt. Paper presented in the Conference “From Orality to Literacy and Back”.

Author: Qi Li

Publisher: Springer Nature

ISBN: 9789811550690

Category: Philosophy

Page: 182

View: 541

This book investigates a new interactive data visualisation concept that employs traditional Chinese aesthetics as a basis for exploring contemporary digital technological contexts. It outlines the aesthetic approach, which draws on non-Western aesthetic concepts, specifically the Yijing and Taoist cosmological principles, and discusses the development of data-based digital practices within a theoretical framework that combines traditional Taoist ideas with the digital humanities. The book also offers a critique of the Western aesthetics underpinning data visualisation, in particular the Kantian sublime, which prioritises the experience of power over the natural world viewed at a distance. Taoist philosophy, in contrast, highlights the integration of the surface of the body and the surface of nature as a Taoist body, rather than promoting an opposition of mind and body. The book then explores the transformational potential between the human body and technology, particularly in creating an aesthetic approach spanning traditional Chinese aesthetics and gesture-based technology. Representing a valuable contribution to the digital humanities, the book helps readers understand data-based artistic practices, while also bringing the ideas of traditional Chinese aesthetics to Western audiences. In addition, it will be of interest to practitioners in the fields of digital art and data visualisation seeking new models.
Categories: Philosophy