数据可视化：洞察与理解的艺术

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“数据可视化之美.pdf”是一本关于数据可视化设计的书籍，由Julie Steele和Noah Iliinsky编辑。本书探讨了如何通过艺术性的设计和对细节的精确呈现，来提升数据可视化的效率和影响力，进而促进对数据的深入理解和洞察。在数据科学和信息技术领域，数据可视化是一个至关重要的部分。它不仅涉及美学，还涵盖了信息传达的科学。书中的“Beautiful Visualization”可能包含了多个章节，每个章节可能由业界专家撰写，分别讨论不同的设计原则、工具和技术。例如，书中可能会涵盖以下知识点： 1. **设计原则**：书中可能详细讲解了色彩理论、比例和尺度的使用、视觉层次构建、图表选择以及如何避免常见的可视化误导。设计原则旨在帮助读者理解如何有效地将复杂的数据转换为易于理解的图形。 2. **数据故事叙述**：数据可视化不仅仅是展示信息，更是一种讲述故事的方式。书可能教导读者如何通过可视化构建引人入胜的故事线，使数据具有更强的说服力和情感共鸣。 3. **交互式可视化**：随着技术的发展，交互式可视化成为趋势。书中可能介绍了如何利用JavaScript库（如D3.js）创建动态和响应式的可视化，以增强用户参与度和探索性分析。 4. **可视化工具**：书可能列举并比较了各种数据可视化工具，如Tableau、Power BI、QlikView等，分析它们的优缺点，以及在不同场景下的适用性。 5. **最佳实践和案例研究**：书中可能包含了一系列成功可视化的实例，这些案例可能来自各个行业，展示了如何通过有效的设计解决特定问题或揭示隐藏的模式。 6. **数据可视化伦理**：书中可能强调了数据可视化过程中的伦理考虑，如确保公正无偏见地呈现数据，尊重数据隐私，以及正确处理缺失和异常值。 7. **可视化创新**：随着技术的进步，新的可视化方法和技巧不断涌现。书可能探讨了如地理信息系统（GIS）、网络图和多维可视化等领域的最新发展。通过阅读“数据可视化之美”，读者不仅可以提升设计感，还能学习到如何更有效地将数据转化为强大的决策支持工具，同时理解如何将艺术与科学相结合，创造真正意义上的“Beautiful Visualization”。

xiv

PREFACE

Conventions Used in This Book

The following typographical conventions are used in this book:

Italic

Indicates new terms, URLs, email addresses, filenames, and file extensions. Also

used for emphasis in the text.

Constant width

Used for program listings, as well as within paragraphs to refer to program ele-

ments such as variable or function names, databases, data types, environment

variables, statements, and keywords.

Constant width bold

Used for emphasis within code listings.

Constant width italic

Shows text that should be replaced with user-supplied values or by values deter-

mined by context.

Using Code Examples

This book is here to help you get your job done. In general, you may use the code in

this book in your programs and documentation. You do not need to contact us for

permission unless you’re reproducing a significant portion of the code. For example,

writing a program that uses several chunks of code from this book does not require

permission. Selling or distributing a CD-ROM of examples from O’Reilly books does

require permission. Answering a question by citing this book and quoting example

code does not require permission. Incorporating a significant amount of example code

from this book into your product’s documentation does require permission.

We appreciate, but do not require, attribution. An attribution usually includes the title,

author, publisher, and ISBN. For example: “Beautiful Visualization, edited by Julie Steele

If you feel your use of code examples falls outside fair use or the permission given

above, feel free to contact us at permissions@oreilly.com.

BEAUTIFUL VISUALIZATION

so not because they were designed to be novel, but because they were designed to be

effective; their novelty is a byproduct of effectively revealing some new insight about

the world.

Informative

The key to the success of any visual, beautiful or not, is providing access to informa-

tion so that the user may gain knowledge. A visual that does not achieve this goal has

failed. Because it is the most important factor in determining overall success, the abil-

ity to convey information must be the primary driver of the design of a visual.

There are dozens of contextual, perceptive, and cognitive considerations that come

into play in making an effective visual. Though many of these are largely outside the

scope of this chapter, we can focus on two particulars: the intended message and the con-

text of use. Keen attention to these two factors, in addition to the data itself, will go far

toward making a data visualization effective, successful, and beautiful; we will look at

them more closely a little later.

Efficient

A beautiful visualization has a clear goal, a message, or a particular perspective on

the information that it is designed to convey. Access to this information should be as

straightforward as possible, without sacrificing any necessary, relevant complexity.

A visual must not include too much off-topic content or information. Putting more

information on the page may (or may not) result in conveying more information to

the reader. However, presenting more information necessarily means that it will take

the reader longer to find any desired subset of that information. Irrelevant data is the

same thing as noise. If it’s not helping, it’s probably getting in the way.

Aesthetic

The graphical construction—consisting of axes and layout, shape, colors, lines, and

typography—is a necessary, but not solely sufficient, ingredient in achieving beauty.

Appropriate usage of these elements is essential for guiding the reader, communicat-

ing meaning, revealing relationships, and highlighting conclusions, as well as for visual

appeal.

The graphical aspects of design must primarily serve the goal of presenting informa-

tion. Any facet of the graphical treatment that does not aid in the presentation of

information is a potential obstacle: it may reduce the efficiency and inhibit the suc-

cess of a visualization. As with the data presented, less is usually more in the graphics

department. If it’s not helping, it’s probably getting in the way.

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