Visualize This: The Flowingdata Guide To Design, Visualization, And Statistics 9780470944882 pmlz 电子版 pdf docx 网盘 kindle azw3 下载

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 de*ions 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.

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 Options.

Wrapping Up.

4 Visualizing Patterns over Time.

What to Look for over Time.

Discrete Points in Time.

Continuous Data.

Wrapping Up.

5 Visualizing Proportions.

What to Look for in Proportions.

Parts of a Whole.

Proportions over Time.

Wrapping Up.

6 Visualizing Relationships.

What Relationships to Look For.

Correlation.

Distribution.

Comparison.

Wrapping Up.

7 Spotting Differences.

What to Look For.

Comparing across Multiple Variables.

Reducing Dimensions.

Searching for Outliers.

Wrapping Up.

8 Visualizing Spatial Relationships.

What to Look For.

Specific Locations.

Regions.

Over Space and Time.

Wrapping Up.

9 Designing with a Purpose.

Prepare Yourself.

Prepare Your Readers.

Visual Cues.

Good Visualization.

Wrapping Up.

Index.

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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datafl.ws/12i.

datafl.ws/12i

Modest Maps is a BSD-licensed display and interaction 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。

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 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.