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”。
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...
评分本科的数学生涯确实因为缺少兴趣而显得枯燥乏味,机缘巧合在图书馆里借了这本书,兴致勃勃的看了两遍。她像调味剂一样,将在学校学到的统计知识与编程应用以可视化的形式糅合在一起,是数学出身的本科生以不丢弃本专业为前提而找到自己的方向的入门级好书,尤其是喜欢视觉设计...
评分在多看买的电子版,闲时翻翻,看了一半。 鲜活的数据没有感觉到,倒是介绍了一些工具,Python/R/Illustrator/Flash/ActionScript。 不喜欢代码的人,一目十行略过;不喜欢 Illustrator 的人,也差不多。 我呢,既不想了解 Illustrator,暂时也没有计划学习 R,更关注数据的可视...
评分本科的数学生涯确实因为缺少兴趣而显得枯燥乏味,机缘巧合在图书馆里借了这本书,兴致勃勃的看了两遍。她像调味剂一样,将在学校学到的统计知识与编程应用以可视化的形式糅合在一起,是数学出身的本科生以不丢弃本专业为前提而找到自己的方向的入门级好书,尤其是喜欢视觉设计...
评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...
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
评分the flowing data 网站的作者。没有告诉怎么实现, 但是基本上是R + Python + Illustrator
评分哟哟
评分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。。。
评分suitable for undergraduate students
本站所有内容均为互联网搜索引擎提供的公开搜索信息,本站不存储任何数据与内容,任何内容与数据均与本站无关,如有需要请联系相关搜索引擎包括但不限于百度,google,bing,sogou 等
© 2025 book.wenda123.org All Rights Reserved. 图书目录大全 版权所有