Mastering matplotlib

by Duncan M. McGreggor (Author)

8 ratings

ISBN-13: 978-1783987542

ISBN-10: 1783987545

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A practical guide that takes you beyond the basics of matplotlib and gives solutions to plot complex data

About This Book

Customize, configure, and handle events, and interact with figures using matplotlib
Create highly intricate and complicated graphs using matplotlib
Explore matplotlib's depths through examples and explanations in IPython notebooks

Who This Book Is For

If you are a scientist, programmer, software engineer, or student who has working knowledge of matplotlib and now want to extend your usage of matplotlib to plot complex graphs and charts and handle large datasets, then this book is for you.

What You Will Learn

Analyze the matplotlib code base and its internals
Re-render visualized data on the fly based on changes in the user interface
Take advantage of sophisticated third-party libraries to plot complex data relationships
Create custom styles for use in specialize publications, presentations, or online media
Generate consolidated master plots comprising many subplots for dashboard-like results
Deploy matplotlib in Cloud environments
Utilize matplotlib in big data projects

In Detail

matplotlib is a Python plotting library that provides a large feature set for a multitude of platforms. Given the depth of the library's legacy and the variety of related open source projects, gaining expert knowledge can be a time-consuming and often confusing process.

You'll begin your exciting journey learning about the skills that are necessary in leading technical teams for a visualization project or to become a matplotlib contributor.

Supported by highly-detailed IPython Notebooks, this book takes you through the conceptual components underlying the library and then provides a detailed overview of its APIs. From there, you will learn about event handling and how to code for interactive plots.

Next you will move on to customization techniques, local configuration of matplotib, and then deployments in Cloud environments. The adventure culminates in an exploration of big data visualization and matplotlib clustering.

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Product details

Publisher ‏ : ‎ Packt Publishing (June 29, 2015)
Language ‏ : ‎ English
Paperback ‏ : ‎ 292 pages
ISBN-10 ‏ : ‎ 1783987545
ISBN-13 ‏ : ‎ 978-1783987542
Item Weight ‏ : ‎ 1.11 pounds
Dimensions ‏ : ‎ 7.5 x 0.66 x 9.25 inches

Best Sellers Rank: #2,682,858 in Books (See Top 100 in Books)
- #1,481 in Data Modeling & Design (Books)
- #2,900 in Python Programming
- #6,894 in Computer Programming Languages

Customer Reviews:
8 ratings

About the author

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Duncan McGreggor

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Duncan has been programming since 1981, when he joined others of his generation in coding for the pleasure and adventure of it -- with games! Duncan has maintained a blog since 2003 where he has provided tutorials and thoughts on Python, network programming, distributed computing, Lisp dialects, and Erlang. Duncan is a Python Software Foundation Fellow, a speaker at Erlang conferences, core contributor to LFE, and co-maintainer of the LFE documentation and blog. Duncan is the author of a book on data visualization for Python, and spends his nights working on community books for LFE, including an on-going project which is converting the famous work ~Structure and Interpretation of Computer Programs~ to LFE from its native Scheme. With 20 years of active involvement in open source software, Duncan's greatest pleasure comes from sharing amazing technologies -- new and old! -- with curious and interested minds. His greatest joy? Seeing the successes of those he has been able to help, directly or indirectly.

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This is the worst scientific/programming book I have ever read

Reviewed in the United States on July 31, 2018

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This book is simply a collection of examples on what can be done in matplotlib rather than a tool for actually learning it. Besides the opening paragraph where it details the matplotlib library layers, the book does nothing to give you the knowledge needed to use matplotlib on a basic, advanced, or expert level. This is the worst scientific/programming book I have ever read. Skip it.

5 people found this helpful

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NRK

Three Stars

Reviewed in the United States on August 14, 2018

Verified Purchase

I was hoping for a systematic understanding of the package. Didn't get it.

3 people found this helpful

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G. A. Patino

The matplotlib book for intermediate users

Reviewed in the United States on August 12, 2015

This is the definite book to learn the most advanced aspects of matplotlib. Even though the book covers installation and gives the fundamentals about basic plots, it is best suited for intermediate users in both Python and matplotlib. In fact, the authors are very class-oriented, making a fair familiarity with object-oriented programming something of a prerequisite. However, if you have those prerequisites the book is a worthy investment as you will be able to take full advantage of matplotlib.
Even though the topics covered are advanced, from the matplotlib architecture to deploying it in Docker and implementing in parallel computing, they are presented in a clear and concise way. Yet the breadth of applications covered is quite comprehensive, and the authors are able to articulate all the different chapters so that the learning feels like a natural progression instead of trying to cram very disparate subjects. The code is elegant and relatively short, facilitating its reading; and the authors explanations for it are very easy to follow. In particular, the chapter of big data visualization definitely goes beyond what is presented in other books that also cover the same topic, and the implementation explanations are much better. The fact that the book is under 300 pages long is a huge plus. The only chapter I felt that wasn't as easy to follow is the one on GUI deployment.
One aspect I really enjoyed about the book is the multiple explanations about the different approaches to creating figures with matplotlib. When you are learning Python and matplotlib you see some books that use pyplot, while others use pylab. Or some like the ax. synthax while others stick to the plt. one. This is the first book in which I see a presentation of all those possibilities, along with their advantages and disadvantages. By the same token, if you are confused as to when to use Seaborn vs yhat ggplot, what's the point of NetworkX, what is ModGrapher, etc. you will find all those explanations here, along with suggestions for their appropriate application.

20 people found this helpful

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Ro'eh Nävee

Intermediate matplotlib

Reviewed in the United States on May 12, 2017

'Mastering matplotlib' is a textbook for someone acquainted with using the Python library named 'matplotlib.' Also the IPython/Jupyter interpreter, since the 'nbagg' IPython Notebook backend to matplotlib will also be used. The 'nbagg' backend is for working with plots in a Web browser. Other Python libraries were SciPy, NumPy, Pandas and Seaborn.

Most Jupyter notebooks in the tutorials start with:

import matplotlib
matplotlib.use('nbagg')
%matplotlib inline
import matplotlib.pyplot as plt

One convenience to appreciate is how the author listed dependent libraries featured in the textbook, and even stored them in a text file included within the accompanying code, which can be downloaded for free from Packt Publishing. The generous author even states: "...you are welcome to...utilize the matplotlib library and the provided code in whatever way you see fit." Free practical, usable code. Once the free code has been downloaded, the github.com repo masteringmatplotlib/notebooks is optional. Mastering matplotlib

3 people found this helpful

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Loris

Very good book to improve your matplotlib skills

Reviewed in the United States on August 11, 2015

I bought this book with the goal of improving my basic knowledge of matplotlib: while the creation of basic plots is straightforward, I found it difficult to modify the default behaviors of the library, and I faced problems in plotting large amount of data. I can safely say that this book helped me to solve both issues. As the author mentions in the book, a prior knowledge of matplotlib will definitely makes the reading more enjoiable.

The book begins by giving an historical overview of matplotlib and by introducing two popular projects, seaborn and pandas. The chapters that follow describes the matplotlib internal architecture and its API. Next the author illustrates how events are handled in matplotlib and how to create interactive plots. The fifth chapter is dedicated to high-level plotting and shows how to create plots with third-party libraries, such as networkX, pandas, and seaborn, which wrap matplotlib functionality. The chapter also briefly introduces Bokeh, a library that offers a series of improvements over matplotlib and focus its attention on the web browser. In this chapter the author did a very good job in showing how a good visualization of the data is crucial in data analysis. The next chapter covers the customization (and the configuration) of matplotlib. Here the author shows how to create complex layouts where different plots are combined in the same figure. In the eight chapter the author explains how to plot huge amount of data by illustrating different strategies that range from using tools such as numpy's memmap function and pytables, to decimating data (removal of a fraction of the data). The last chapter shows how it is possible to improve the performance of matplotlib by using a clustered environment.

Last but not least, the authors provided a GitHub repository with the example code and notebooks of each chapter of the book.

14 people found this helpful

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Top reviews from other countries

The solution for non-computer scientists unable to work in teams

Reviewed in the United Kingdom on December 19, 2017

Verified Purchase

If you are a scientist who doesn't play well with others this might be all you need to get by with matplotlib. Should you be a computer scientist you'll find it a clumsy stumble around your field. My advice to fellow scientists outside of computer science, is to knock on the doors of your Comp. Sci. colleagues and let us collaborate to do something well together.

Justin Marley

Detailed Book for Advanced Readers

Reviewed in the United Kingdom on November 24, 2017

Verified Purchase

Very good book with a lot of material including code, graphs and hardware/cloud discussion to take the reader to the next level.

N. Phillips

Assumes Python 3

Reviewed in the United Kingdom on June 6, 2016

Verified Purchase

This book is heavily dependent on Python 3 if you are working in 2.7 it is probably not a good buy. It would be really useful it it made this clear in the book description.

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Mastering matplotlib

About This Book

Who This Book Is For

What You Will Learn

In Detail

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Product details

About the author

Duncan McGreggor