Download Fundamentals of Data Visualization A Primer on Making Informative and Compelling Figures eBook Claus O Wilke
Download As PDF : Fundamentals of Data Visualization A Primer on Making Informative and Compelling Figures eBook Claus O Wilke
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
Download Fundamentals of Data Visualization A Primer on Making Informative and Compelling Figures eBook Claus O Wilke
"In this well-illustrated view of what it means to clearly visualize data, Claus Wilke explains his rationale for why some graphs are effective and others are not. This incredibly useful guide provides clear examples that beginners can emulate as well as explanations for stylistic choices so experts can learn what to modify.
The book's beautiful figures use both good and bad examples to discuss visualization clarity. Very practically, there is also a helpful explanation of image file types, which is critical for quality."
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Fundamentals of Data Visualization A Primer on Making Informative and Compelling Figures eBook Claus O Wilke Reviews :
Fundamentals of Data Visualization A Primer on Making Informative and Compelling Figures eBook Claus O Wilke Reviews
- Wilke’s “Fundamentals of Data Visualization†fills an important niche a manual for the professional data scientist who wants to convey the essence of data succinctly, accurately, and in an aesthetically pleasing way. Wilke shows that this is (perhaps surprisingly) difficult, and he does this by showing both good and bad examples of data visualization in order to make this point. The book really attempts to build up the reader’s intuition about what makes a good visualization chapter by chapter. By the end, the lessons learned have become so obvious that when going back to earlier chapters, a single glance at the figure is enough to remind you about what is good (or bad) in the example given. This is not a book that gives programming examples that tell the reader how to achieve a particular figure, and I think this is intentional. The emphasis is on understanding the principles of data visualization, not on supplying a hack for the next figure. (But for those who want to recreate a figure, Wilke provides the entire source code for the book on a web site). All in all, this is probably the best book on data visualization for the practicing scientist out there. The prose is clear and concise, the principles behind the choices he makes are clearly laid out, and the figures are clean and free of clutter. My only gripe is that the colors in the book appear to be somewhat flat and less intense than in the electronic version. Hopefully this can be remedied in the future.
- I saw this book on a friend’s desk and had to get my own copy! I’ve read straight through a quarter of it already and it is so clear and straightforward that it makes all the ideas seem obvious. I had previously tried to absorb some works by Edward Tufte but found them overwhelming compared to this book. I’ve been an academic biologist for years and wish I’d had a book like this earlier in my career. The principles the author explains help me codify what I already intuitively sensed about various visual representations. It will be much easier now to design effective figures for my own work and to interpret at a glance the data of others! In fact I have already used a principle from these early chapters to improve a figure I’m working on for a manuscript. While extremely readable and appropriate for any layman, this book is a must for professionals representing data in any form, and in teaching graduate students how to communicate data. This book is so straight forward I would hope it could be used even in high schools where the basic important concepts would serve everybody entering this data-rich world!
- In our data era, many have to communicate to others what they data mean. This book covers the principles, the how to design an effective graph communication strategy and contrast bad, ugly versus good choices on how to present the data. Everything is important you need to think about how you position your data, how to color it how to choose line types etc. A brilliant book to let you have more insights on how to design better figures
- As a visualization researcher I am thrilled to see this book -- it's thorough and practical, covering many common situations that I tend to get asked about. Other books tend to focus too much on low level details like coding visualizations, or too much on higher level ideas without getting in to specific concerns that come up in visualization design, like, how do i find the right way to show proportion, how do I use a log scale without confusing my audience, or what should I avoid when picking colors. This book covers these lower level choices that add up to make or break a plot. At the same time, the advice is well aligned with findings from visualization research, but without distracting with unnecessary details about what studies have shown. As a researcher who has done a lot of work to try to improve uncertainty visualization, I am especially impressed by the uncertainty chapter in this book - it is the best aligned book chapter on the topic I've seen with what we know about how to visualize uncertainty well in the research community, but it's again written in a very direct, practical way. I'll be recommending it to my students as an aid to the visualization design and analysis assignments in the data visualization courses I teach.
- What is it that makes a data visualization beautiful? How do you compose your own beautiful plot? This books is like a direct injection of solid design sense - engaging and rewarding enough to read straight through like a novel.
This book condenses figure design into its fundamentals. The advice is presented clearly, directly, and memorably. In such a way that, as I'm working a figure, I find myself remembering the lessons from the book, and making modifications as necessary. This pretty much always results in a visually improved figure. Can awkwardly rotated text be better presented? Are my color choices visually consistent, accessible, and balanced across a multipanel figure?
Finally, I wish I could fold chapter 24 "Use larger axis labels" into a paper airplane, and throw it towards most everyone presenting figures in talks. - In this well-illustrated view of what it means to clearly visualize data, Claus Wilke explains his rationale for why some graphs are effective and others are not. This incredibly useful guide provides clear examples that beginners can emulate as well as explanations for stylistic choices so experts can learn what to modify.
The book's beautiful figures use both good and bad examples to discuss visualization clarity. Very practically, there is also a helpful explanation of image file types, which is critical for quality.
