Visualize This 在线电子书 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
发表于2025-02-18
Visualize This 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2025
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
评分每个理科研究生,特别是R用户都应该读读
评分详细讲解基础图像在R中画法。
评分有点儿意思(仍然痛恨flash)
评分真够次的,打两星纯属苦劳。据说 data points 比这还不如,呵呵……
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
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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
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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
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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] 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 { ...
评分作者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...
评分一些图形对于R用户来说,不是有多难,没有看到用巧思妙想来展示可视化数据化,图!=可视化。这一点我个人有点体会。比如http://xccds1977.blogspot.com/2012/07/blog-post_26.html这篇文章,粗看很炫,可实际效用多少呢,满屏满屏的线条,能说明什么呢。 这里无意冒犯谁,因为...
评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。
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...
Visualize This 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2025