Practical data design tips from a data visualization expert of the modern age Data doesn?t decrease; it is ever-increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn?t it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to t...
Practical data design tips from a data visualization expert of the modern age Data doesn?t decrease; it is ever-increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn?t it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full-color book, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships. Presents a unique approach to visualizing and telling stories with data, from a data visualization expert and the creator of flowingdata.com, Nathan Yau Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design to find meaning in the numbers Details tools that can be used to visualize data-native graphics for the Web, such as ActionScript, Flash libraries, PHP, and JavaScript and tools to design graphics for print, such as R and Illustrator Contains numerous examples and descriptions of patterns and outliers and explains how to show them Visualize This demonstrates how to explain data visually so that you can present your information in a way that is easy to understand and appealing.
From the Author: Telling Stories with Data
Author Nathan Yau A common mistake in data design is to approach a project with a visual layout before looking at your data. This leads to graphics that lack context and provide little value. Visualize This teaches you a data-first approach. Explore what your data has to say first, and you can design graphics that mean something.
Visualization and data design all come easier with practice, and you can advance your skills with every new dataset and project. To begin though, you need a proper foundation and know what tools are available to you (but not let them bog you down). I wrote Visualize This with that in mind.
You'll be exposed to a variety of software and code and jump right into real-world datasets so that you can learn visualization by doing, and most importantly be able to apply what you learn to your own data.
Three Data Visualization Steps:
1) Ask a Question
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When you get a dataset, it sometimes is a challenge figuring out where to start, especially when it's a large dataset. Approach your data with a simple curiosity or a question that you want answered, and go from there.
2) Explore Your Data
(Click Graphic to See Larger Version)
A simple curiosity often leads to more questions, which are a good guide for what stories to dig into. What variables are related to each other? Can you see changes over time? Are there any features in the data that stand out? Find out all you can about your data, because the more you know what's behind the numbers, the better story you can tell.
3) Visualize Your Data
(Click Graphic to See Larger Version)
Once you know the important parts of your data, you can design graphics the best way you see fit. Use shapes, colors, and sizes that make sense and help tell your story clearly to readers. While the base of your charts and graphs will share many of the same properties – bars, slices, dots, and lines – the final design elements will and should vary by your unique dataset.
About Nathan who writes for FlowingData My name is Nathan Yau, and I'm the one writing for FlowingData. In a previous life I was an electrical engineering and computer science student at Berkeley, but now I'm a UCLA PhD candidate in statistics with a focu...
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PMInterview产品经理精英访谈录—— HP China +Design Team 设计总监向怡宁 PM.camp:我们知道您在游戏、软件、网页交互设计和翻译、写书等方面都取得了不俗的成绩,请您介绍一下自己吧。新锐设计师?翻译?摇滚音乐人?您最喜欢那个称呼? 向怡宁:“不俗的成绩”是过誉了,...
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作者Nahan Yau,创建了可视化博客flowingdata.com,拥有66000用户,查看了下Amazon.com,发现作者一共只出版了两本书,一本书是这本《鲜活的数据-数据可视化指南》,另一本是2013年出版的《Data Points: Visualization That Means Something》,算是对上一本的补充,侧重讲各种...
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0 有用 陆壹肆 2017-01-25
当handbook用。
1 有用 みちる 2015-05-24
2015-01-09
0 有用 marego 2013-01-01
值得每一个用数据说话的人看看!
1 有用 陈钢 2012-07-27
很早之前就翻完了。讲述了如何从数据到统计图表,到最终美观的信息图。难度不高,内容不深,但很完整,值得一读~~
1 有用 常上九 2017-07-11
哟哟
0 有用 雷克沙士季 2021-01-05
照理说这本书作为 Data Points 之后写的书应该从时间感上更接近现在一些,但实际看来还有不少已经被淘汰的技术。还是推荐作者的博客,订阅收费的内容更佳。
0 有用 Inari 2020-04-10
这书可能适合完全没有做过viz的人来看看代码大概长什么样子。对于略有基础的人来说实在是过于浅层,说是demo却并没有demo到针对不同的数据/不同的目的应该怎么选择viz的点子上。书中略提了一点design principle,也没有什么令人印象深刻的地方。我翻完全书,唯一记住的一点是,原来专业的infographics最后是用Illustrator加工过一遍的,怪不得比大伙平常用Python/R... 这书可能适合完全没有做过viz的人来看看代码大概长什么样子。对于略有基础的人来说实在是过于浅层,说是demo却并没有demo到针对不同的数据/不同的目的应该怎么选择viz的点子上。书中略提了一点design principle,也没有什么令人印象深刻的地方。我翻完全书,唯一记住的一点是,原来专业的infographics最后是用Illustrator加工过一遍的,怪不得比大伙平常用Python/R干画出来的好看多了。。。 (展开)
0 有用 o0O 2020-03-30
当年折磨我的论文来源
0 有用 濯希 2020-03-28
太基本了,不建议买,浪费钱。没有基础的可以看。有经验的可以跳过
1 有用 常上九 2017-07-11
哟哟