Visualize This

Nathan Yau 加州大学洛杉矶分校统计学专业在读博士、超级数据迷，专注于数据可视化与个人数据收集。他曾在《纽约时报》、CNN、Mozilla和SyFy工作过，认为数据和信息图不仅适用于分析，用来讲述与数据有关的故事也非常合适。Yau的目标是让非专业人士读懂并用好数据。他创建了一个设计、可视化和统计方面的博http://flowingdata.com，你可以从中欣赏到他最新的数据可视化实验作品。向怡宁 交互和视觉设计师、摇滚乐手，同时还热衷于翻译和写作。著有《Flash组件、游戏、SWF加解密》及《就这么简单：Web开发中的可用性和用户体验》，译有《奇思妙想：15位计算机天才及其重大发现》、《瞬间之美：Web界面设计如何让用户心动》、《网站设计解构：有效的交互设计框架和模式》、《网站搜索设计：兼顾SEO及可用性的网站设计心得》等书。他认为“一个不会弹吉他的设计师不是个好译者”。

出版者:John Wiley & Sons

作者:Nathan Yau

页数:384

出版时间:2011-7-20

价格:GBP 26.99

装帧:Paperback

isbn号码:9780470944882

图书标签:visualization数据可视化数据图形化infographic设计数据分析Data可视化图形

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

(Click Graphic to See Larger Version)

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.

读后感

本书的可视化数据基本上是用Python完成数据收集与基本处理，再以R软件制作，最后用Adobe Illustrator修饰完成的。静态部分基本上大同小异，无非只是在R创建的时候，更改一下创建图表的类型（什么情况该用什么图表，本书还是给了很详细的说明的）。如果还想创建互动版本，则需要...

普及性质，作者非常热爱数据可视化 http://app.yinxiang.com/shard/s2/sh/5ac3535a-8218-4d57-8a33-5478c16a6c37/a7251d1a09c33ab8e14754b8897efdbc  

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...  

[作者] Nathan Yau 博士 超级数据迷 flowingdata.com ================================= [本书思路] 数据可视化的作用 -> 处理数据 -> 各样式的数据可视化 ================================= [摘抄]： 1 从数据中获得什么{ 模式、相互关系、有问题的数据 } 2 数据来源 { ...  

用户评价

哟哟

继上次的幻灯片之禅的流行, 这次可能会来个数据可视化之禅什么的.

继上次的幻灯片之禅的流行, 这次可能会来个数据可视化之禅什么的.

总体来说不错，但没期望的那么好。 主题有些分散了。

当年折磨我的论文来源