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Laddar... Data Points: Visualization That Means Something (2013)av Nathan Yau
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Gå med i LibraryThing för att få reda på om du skulle tycka om den här boken. Det finns inga diskussioner på LibraryThing om den här boken. Following on from the success of Visualize This, the author aims to extend the scope of his topic to a more general take on data visualization. Different phases of the work process are covered and the book is more independent of specific tools and software. However, many of the examples and main ideas are the same as in the previous book, and it sometimes feels more like a revision that a sequel. This is a great primer on what data visualization is and how the author goes about it. For a visualization to mean something, it must speak to the audience. If that happens, the visualization is successful; it is not dogmatic. This is also not a step-by-step guide to using a particular vis package (for that see, e.g., Yau's "Visualize This.") It is a call for mindfulness in creating a visualization. inga recensioner | lägg till en recension
A fresh look at visualization from the author of Visualize This Whether it's statistical charts, geographic maps, or the snappy graphical statistics you see on your favorite news sites, the art of data graphics or visualization is fast becoming a movement of its own. In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both Inga biblioteksbeskrivningar kunde hittas. |
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Google Books — Laddar... GenrerMelvil Decimal System (DDC)001.4226Information Computing and Information Knowledge Research Research methods Statistical methodsKlassifikation enligt LCBetygMedelbetyg:
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their place, albeit a limited one, in the visualization domain. As such, he promotes freedom and the ability to choose above all.
There are lots of data that need appropriate visualization in today's world. The ability to procure data on just about anything has gone up astronomically in recent years. Yau's approach does not offer a lot towards programmers who want to mass-produce visualizations. Instead, this author of FolowingData.com focuses on building one powerful, elegant visualization at a time. He's less an artist and more a statistician (belying his PhD in Statistics). He focuses on communicating the right message through visualization of your data.
As is customary in books like this, the examples tend to carry the narrative. While the communication of the principles of visualization is the primary message of this book, Yau carries his story through interesting examples of how people communicate (and sometimes miscommunicate) with data. While not as erudite and varied as Tufte's compilations, Yau's work provides much food for thought as the reader analyzes the graphics. Reading this book is simply fun.
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