掌握复杂数据可视化：matplotlib高级实战指南

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"Mastering Matplotlib: A Practical Guide to Advanced Plotting with Python" 是由 Duncan M. McGregor 所著的一本专著，由 PACKT Publishing 出版于 2015 年。这本书旨在帮助读者深入理解和掌握 matplotlib 这个强大的 Python 绘图库，它提供了丰富的功能，适用于多种平台。对于那些希望领导技术团队进行可视化项目或成为 matplotlib 贡献者的人来说，这是一本极具价值的学习资源。本书以详细的 IPython Notebook 为辅助，首先引导读者理解 matplotlib 的核心概念和技术架构，然后逐步介绍其 API 的详细使用。学习内容包括事件处理、交互式图表编程，以及如何根据项目需求定制化图形，如本地配置和在云端环境中的部署。最后，书中还涵盖了大数据可视化和 matplotlib 在数据聚类方面的应用，使读者能够应对复杂数据的高效展示。在阅读过程中，读者将学到如何利用 matplotlib 实现高效的数据分析和可视化，提升项目的可读性和专业性。此外，版权信息表明，未经 Packt Publishing 的书面许可，书中的任何部分都不能复制、存储或传输，以保护作者和出版社的权益。尽管本书力求提供准确的信息，但所有内容不带任何形式的保修，因为可能存在信息过时或疏漏的情况。读者在使用书中提供的方法时，应自行判断并承担可能产生的风险。Packt Publishing 在引用商标时已尽力确保准确性，但并不能对此做出保证。 "Mastering Matplotlib" 是一本实用且详尽的教程，适合希望通过深入学习 matplotlib 掌握高级绘图技巧的开发者和数据科学家，无论是为了个人职业发展还是团队协作，都能从中受益匪浅。

[ vii ]

Preface

In just over a decade, matplotlib has grown to offer the Python scientic computing

community a world-class plotting and visualization library. When combined with

related projects, such as Jupyter, NumPy, SciPy, and SymPy, matplotlib competes

head-to-head with commercial software, which is far more established in the

industry. Furthermore, the growth experienced by this open source software project

is reected again and again by individuals around the world, who make their way

through the thorny wilds that face the newcomer and who develop into strong

intermediate users with the potential to be very productive.

In essence, Mastering matplotlib is a very practical book. Yet every chapter was written

considering this learning process, as well as a larger view of the same. It is not just the

raw knowledge that denes how far developers progress in their goal. It is also the

ability of motivated individuals to apply meta-levels of analysis to the problem and

the obstacles that must be surmounted. Implicit in the examples that are provided in

each chapter are multiple levels of analysis, which are integral to the mastery of the

subject matter. These levels of analysis involve the processes of dening the problem,

anticipating potential solutions, evaluating approaches without losing focus, and

enriching your experience with a wider range of useful projects.

Finding resources that facilitate developers in their journey towards advanced

knowledge and beyond can be difcult. This is not due to the lack of materials.

Rather, it is because of the complex interaction of learning styles, continually

improving codebases with strong legacies, and the very exible nature of the

Python programming language itself. The matplotlib developers who aspire to

attain an advanced level, must tackle all of this and more. This book aims to be

a guide for those in search of such mastery.

www.it-ebooks.info

Preface

[ viii ]

What this book covers

Chapter 1, Getting Up to Speed, covers some history and background of matplotlib,

goes over some of the latest features of the library, provides a refresher on Python

3 and IPython Notebooks, and whets the reader's appetite with some advanced

plotting examples.

Chapter 2, The matplotlib Architecture, reviews the original design goals of matplotlib

and then proceeds to discuss its current architecture in detail, providing visualizations

of the conceptual structure and relationships between the Python modules.

Chapter 3, matplotlib APIs and Integrations, walks the reader through the matplotlib

APIs, adapting a single example accordingly, examines how third-party libraries

are integrated with matplotlib, and gives migration advice to the advanced users

of the deprecated pylab API.

Chapter 4, Event Handling and Interactive Plots, provides a review of the event-based

systems, covers event loops in matplotlib and IPython, goes over a selection of

matplotlib events, and shows how to take advantage of these to create interactive plots.

Chapter 5, High-level Plotting and Data Analysis, combines the interrelated topics,

providing a historical background of plotting, a discussion on the grammar of

graphics, and an overview of high-level plotting libraries. This is then put to use

in a detailed analysis of weather-related data that spans 120 years.

Chapter 6, Customization and Conguration, covers the custom styles in matplotlib

and the use of grid specs to create a dashboard effect with the combined plots. The

lesser-known conguration options are also discussed with an eye to optimization.

Chapter 7, Deploying matplotlib in Cloud Environments, explores a use case for

matplotlib in a remote deployment, which is followed by a detailed programmatic

batch-job example using Docker and Amazon AWS.

Chapter 8, matplotlib and Big Data, provides detailed examples of working with

large local data sets, as well as distributed ones, covering options such as

numpy.memmap, HDF5, and Hadoop. Plots with millions of points will also

be demonstrated.

Chapter 9, Clustering for matplotlib, introduces parallel programming and clusters

that are designed for use with matplotlib, demonstrating how to distribute the

parts of a problem and then assemble the results for analysis in matplotlib.

www.it-ebooks.info

Preface

[ xi ]

Downloading the example code

Each chapter in Mastering matplotlib provides instructions on obtaining the example

code and notebook from Github. A master list has been provided at https://github.

com/masteringmatplotlib/notebooks. You can download the example code les

from your account at http://www.packtpub.com for all the Packt Publishing books

you have purchased. If you purchased this book elsewhere, you can visit http://www.

packtpub.com/support and register to have the les e-mailed directly to you.

Downloading the color images of this book

We also provide you with a PDF le that has color images of the screenshots/

diagrams used in this book. The color images will help you better understand the

changes in the output. You can download this le from https://www.packtpub.

com/sites/default/files/downloads/7542OS_ColoredImages.pdf.

Errata

Although we have taken every care to ensure the accuracy of our content, mistakes

do happen. If you nd a mistake in one of our books—maybe a mistake in the text or

the code—we would be grateful if you could report this to us. By doing so, you can

save other readers from frustration and help us improve subsequent versions of this

book. If you nd any errata, please report them by visiting http://www.packtpub.

com/submit-errata, selecting your book, clicking on the Errata Submission Form

link, and entering the details of your errata. Once your errata are veried, your

submission will be accepted and the errata will be uploaded to our website or added

to any list of existing errata under the Errata section of that title.

To view the previously submitted errata, go to https://www.packtpub.com/books/

content/support and enter the name of the book in the search eld. The required

information will appear under the Errata section.

Piracy

Piracy of copyrighted material on the Internet is an ongoing problem across all

media. At Packt, we take the protection of our copyright and licenses very seriously.

If you come across any illegal copies of our works in any form on the Internet, please

provide us with the location address or website name immediately so that we can

pursue a remedy.

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