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内容简介:
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 ***anize 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
relati***hips.
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 de*i*** of patterns and
outliers and explains how to show them
Visualize This ***s how to explain data visually so that
you can present your information in a way that is easy to
understand and appealing.
书籍目录:
Introduction.
1 Telling Stories with Data.
More Than Numbers.
What to Look For.
Design.
Wrapping Up.
2 Handling Data.
Gather Data.
Formatting Data.
Wrapping Up.
3 Choosing Tools to Visualize Data.
Out-of-the-Box Visualization.
Programming.
Illustration.
Mapping.
Survey Your Opti***.
Wrapping Up.
4 Visualizing Patterns over Time.
What to Look for over Time.
Discrete Points in Time.
Continuous Data.
Wrapping Up.
5 Visualizing Proporti***.
What to Look for in Proporti***.
Parts of a W***.
Proporti*** over Time.
Wrapping Up.
6 Visualizing Relati***hips.
What Relati***hips to Look For.
Correlation.
Distribution.
Comparison.
Wrapping Up.
7 Spotting Differences.
What to Look For.
Comparing across Multiple Variables.
Reducing Dimensi***.
Searching for Outliers.
Wrapping Up.
8 Visualizing Spatial Relati***hips.
What to Look For.
Specific Locati***.
Regi***.
Over Space and Time.
Wrapping Up.
9 Designing with a Purpose.
Prepare Yourself.
Prepare Your Readers.
Visual Cues.
Good Visualization.
Wrapping Up.
Index.
作者介绍:
Nathan Yau is a PhD candidate in Statistics at
UCLA and a lifelong data junkie. His goal is to make data available
and useful to those who aren't necessarily data experts, and he
focuses on data visualization and personal data collection. You can
follow his visualization experiments at http://flowingdata.com.
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原文赏析:
datafl.ws/12i.
datafl.ws/12i
Modest Maps is a BSD-licensed display and in***ction library for tile-based maps in Flash (ActionScript 2.0 and ActionScript 3.0) and Python.
That was more than twice the amount anyone in the world had eaten before him.
hard-coded array
数据就静静地待在我们生活的每一个角落。园子里已经果实累累,正等待我们去采摘。对大多数人来说,真正有意思的并不是数据本身,而是数据背后蕴涵的信息。
其它内容:
书籍介绍
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 ***anize 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 relati***hips. 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 descripti*** of patterns and outliers and explains how to show them Visualize This ***s 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 easie***ith 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 *** curiosity or a question that you want answered, and go from there.
2) Explore Your Data
(Click Graphic to See Larger Version)
A *** curiosity often leads to more questi***, which are a good guide fo***hat 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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