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What you will learn

Discover how to create all the common plots you need

Enrich your plots with annotations and sophisticated legends

Take control of your plots and master colors, linestyle, and scales

Add a dimension to your plots and go 3D

Integrate your graphics into your applications

Automate your work and generate a large batch of graphics

Create interactive plots with matplotlib

Combine your plots to create sophisticated visualizations

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Joel Sevilla Mar 24, 2017

I agree with other more experienced reviewers. It is terrific for beginners (like me). Text is clear and the code always run, so the beginner does not have to debug authors code (a task just for advanced users). This book shines between my good list of Python books. Thanks professor Devert.

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Hudan Studiawan Aug 04, 2014

We are often get confused with text book that provides very complex materials and hard to understand. There are rarely a book that can give us a easy and step-by-step guide to get our job done. Fortunately, Packt Publishing comes with a good news!One of the book provided by Packt is matplotlib Plotting Cookbook. It’s all about plotting your graph with matplotlib. It is an open source library massively used and supported by community worldwide. In this book, you can find any kind of plotting type. Starting from live curve, points, bar chart, pie chart, histograms, and other types of graph. A how-to draw simple graph is given in Chapter 1.This kind of matplotlib library is based on Python programming language. Don’t worry about the difficulty when starting graph for the first time. Python is an intuitive computer programming languange and it is easy to learn.In the next chapter, the author, Alexandre Devert, depicts customization for color and pattern of our chart. We can also control marker style and size, or even creating our own color maps for plotted graph. Like other book published by Packt, all steps are briefly described and very well understood :)In Chapter 3, we will find many instructions to modify annotations for our graph. Formula annotation can be employed using Latex-style notations. The book also describes guides to add label to axis, text, legend, and grid behind the chart. Every part is clearly illustrated by “How to do it” subsection and supported with “How it works … ” part in each section. Chapter 4 will drive us to customization of the figure.We can save our generated graph from matplotlib to file. The supported file format are png, svg, or pdf file. We can follow these guides in Chapter 5. This book is also completed with a story about working with 2D and 3D figures Chapter 6 and 7, respectively. The last chapter, we can integrate our work with Python user interface library. matplotlib have an friendly interface to Tkinter, wxWidgets, GTK, and Pyglet.

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Ty Sid Jun 02, 2014

This book has a useful collection of examples for many common use cases that a developer would need in working with Matplotlib. It is written in an easy to follow style that makes it suitable for Python developers that are starting out with Matplotlib. It is not a Python tutorial in any way, but a minimal knowledge of Python is sufficient to understand the code and the examples. I'm relatively new to Python but have significant programming experience in other languages and had no difficulty in picking up the various tools that are presented in the book. Each example comes with complete code listings that just work without any modifications, so one can easily see what is happening with that code. The eBook version comes with code files for all the examples in the book that can be downloaded directly from the Publisher's website (Packt Publishing).I had a bare minimum exposure to Matplotlib but I did not feel that I need to separately following any other tutorial to learn any particular tools. IMO, the given examples provide a better understanding of the most useful tools by seeing them in action and trying them out on your own.The last chapter on User Interfaces covers creating interactive plots using Tkinter, wxWidgets, GTK, etc, which is helpful in bringing the plots to an audience in a way that makes it easier to explain and clarify the data being considered.I would recommend the Matplotlib Plotting Cookbook to people starting out with Matplotlib who want to get up to speed quickly. It's also useful as a quick reference for experienced developers since many common use cases are covered. The index and the table of contents make it simple to find any particular use case.

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Joe Kington Jun 23, 2014

This book is intended to introduce matplotlib to people with relatively little experience with python, and does a good job of getting someone with little experience "up and running" very quickly. The first chapter does a particularly good job of giving a crash course in the basics of scientific programming with python in just a few pages.Overall, this book is easy to follow and does a good job showing concrete examples of most of matplotlib's functionality. Many of the "There's more" and "How it works" sections do a great job of explaining things in a bit more detail (though I do wish they were longer). There's a nice linear flow to the way the chapters are laid out, and for something called a "cookbook", it's more of an "introduction through example" (which is a good thing!).However, I'm not sure this book adds much over the official documentation. There are a lot of examples, but not enough explanation of the underlying concepts (then again, it is a "cookbook" and not "the exhaustive guide to matplotlib", so perhaps I'm being a bit unfair). While matplotlib is a bit disorganzied in some regards, there are several things that are common throughout the library that are useful to know. For example, it would be nice if this book more prominently mentioned that the plotting commands all return "artists" whose properties can be adjusted through the "artist.set(...)" function.A couple of minor pet peeves:1) The author sticks almost entirely to the pyplot interface throughout the book, but then suddenly changes over to the standard object-oriented interface part-way through (beginning with the 3D plotting chapter). It would be good to explain the change. Better yet, explain what the difference is and the relative advantages of the two.2) The chapters are rather misleadingly named. For example, Chapter 6 is titled "Working with Maps", but doesn't cover matplotlib's mapping capabilities (e.g. basemap or cartopy - both dealing with geographic maps) at all. Instead, it deals with image data and vector plots (e.g. "imshow", "quiver", etc). Similarly Chapter 3 - "Working with Annotations" is a great chapter, but the title is a bit misleading: it deals with adding low-level artists like patches and lines as well as adding latex-formatted equations, title, labels, etc. (Again, I'm being a bit picky, but being able to accurately scan the table of contents is very important in technical books.)

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Mgx May 08, 2014

First of all, the book is very easy to read. Most of the book is filled with recipes code examples and their illustrated outputs. So, it would be fairly simple to complete this book in a day or two.Secondly, I agree with the other review that this book would be quite useful to beginners who are just starting out with Python + Matplotlib. In addition, there are a few recipes inside that could save time for intermediate and expert users. For example, I found some of the recipes for 3D plotting useful, but your mileage could vary depending on your data. The last few recipes show how to interface Matplotlib with Python GUI interfaces and this could also be helpful.However, I feel that the price of the book is high ($40+) considering the material it offers. After all, Matplotlib is technically free to use and has free, well-presented documentation online. This book does not substitute the online documentation at all - rather, it presents a subset of the most useful instructions to get things shaking fast.

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matplotlib Plotting Cookbook: Discover how easy it can be to create great scientific visualizations with Python. This cookbook includes over sixty matplotlib recipes together with clarifying explanations to ensure you can produce plots of high quality.

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