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”。
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.
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...
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...
評分本书介绍了数据可视化的常用工具,基本以R语言为例介绍不同类别的数据可视化场景的解决方案。可以看作数据可视化工具清单。已经看过一遍,估计以后还会经常拿出来翻翻。 另外这本书在图灵网站上可以买到电子版,PDF的,看着挺舒服的。
評分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...
評分繼上次的幻燈片之禪的流行, 這次可能會來個數據可視化之禪什麼的.
评分每個理科研究生,特彆是R用戶都應該讀讀
评分繼上次的幻燈片之禪的流行, 這次可能會來個數據可視化之禪什麼的.
评分the flowing data 網站的作者。沒有告訴怎麼實現, 但是基本上是R + Python + Illustrator
评分太基本瞭,不建議買,浪費錢。沒有基礎的可以看。有經驗的可以跳過
本站所有內容均為互聯網搜索引擎提供的公開搜索信息,本站不存儲任何數據與內容,任何內容與數據均與本站無關,如有需要請聯繫相關搜索引擎包括但不限於百度,google,bing,sogou 等
© 2025 book.quotespace.org All Rights Reserved. 小美書屋 版权所有