Visualize This

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Nathan Yau 加州大學洛杉磯分校統計學專業在讀博士、超級數據迷,專注於數據可視化與個人數據收集。他曾在《紐約時報》、CNN、Mozilla和SyFy工作過,認為數據和信息圖不僅適用於分析,用來講述與數據有關的故事也非常閤適。Yau的目標是讓非專業人士讀懂並用好數據。他創建瞭一個設計、可視化和統計方麵的博http://flowingdata.com,你可以從中欣賞到他最新的數據可視化實驗作品。

嚮怡寜 交互和視覺設計師、搖滾樂手,同時還熱衷於翻譯和寫作。著有《Flash組件、遊戲、SWF加解密》及《就這麼簡單:Web開發中的可用性和用戶體驗》,譯有《奇思妙想:15位計算機天纔及其重大發現》、《瞬間之美:Web界麵設計如何讓用戶心動》、《網站設計解構:有效的交互設計框架和模式》、《網站搜索設計:兼顧SEO及可用性的網站設計心得》等書。他認為“一個不會彈吉他的設計師不是個好譯者”。

出版者:John Wiley & Sons
作者:Nathan Yau
出品人:
頁數:384
译者:
出版時間:2011-7-20
價格:GBP 26.99
裝幀:Paperback
isbn號碼:9780470944882
叢書系列:
圖書標籤:
  • visualization 
  • 數據可視化 
  • 數據圖形化 
  • infographic 
  • 設計 
  • 數據分析 
  • Data 
  • 可視化圖形 
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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.

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[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 { ...  

評分

評分

作者的统计学背景为这本书定下了很好的基础, 如果只是一个图形设计师, 写不出这种书. 因为数据可视化要做得好, 数学非常重要, 在这本书里面, 简单来说, 就是得懂些R的用法, 需要会写一些简单的命令和代码. 可视化见过的多了, 图表见过的多了, Excel见过的多了, 但在同一本书里...  

評分

粗略将书看了一遍,着重看了几个例子的实现,还没动手实践。贯穿书中的数据可视化标准步骤可能就是:Python采集数据,R生成草图,最后illustrator refine。 后面计划将书中实例都好好实践一遍,细细评味下书中对各种chart的选择、评价...  

評分

本书内容十分丰富,涉及到数据可视化的方方面面,适合任何需要处理数据、解读数据的人看。对已经入门且想更加深入了解数据可视化相关资料的,亦可从本书中获得很多的资料。不过对于想深入了解数据可视化算法和程序设计等相关目的的人来说,则本书并非很合适。 另外,虽然本书...  

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很早之前就翻完瞭。講述瞭如何從數據到統計圖錶,到最終美觀的信息圖。難度不高,內容不深,但很完整,值得一讀~~

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推薦所有做MKT research和統計學的同誌讀。

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很早之前就翻完瞭。講述瞭如何從數據到統計圖錶,到最終美觀的信息圖。難度不高,內容不深,但很完整,值得一讀~~

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