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matplotlib Plotting Cookbook
 
 

matplotlib Plotting Cookbook [Kindle Edition]

Alexandre Devert
4.0 von 5 Sternen  Alle Rezensionen anzeigen (1 Kundenrezension)

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Produktbeschreibungen

Kurzbeschreibung

In Detail

matplotlib is part of the Scientific Python modules collection. matplotlib provides a large library of customizable plots and a comprehensive set of backends. It tries to make easy things easy and hard things possible. You can generate plots, add dimensions to the plots, and also make the plots interactive with just a few lines of code with matplotlib. Also, matplotlib integrates well with all common GUI modules.

This book is a head-first, hands-on journey into matplotlib, the complete and definite plotting package for Python. You will learn about the basic plots, how to customize them, and combine them to make sophisticated figures. Along with basic plots, you will also learn to make professional scientific plots.

In this book, you will start with the common figures that are offered by most plotting packages. You will learn how to add annotations, and play with styles, colors, scales, and shapes so that you can add personality and visual punch to your graphics. You will also see how to combine several graphics. With this book you will learn how to create sophisticated visualizations with simple code. Finally, you can make your plots interactive.

After reading "matplotlib Plotting Cookbook", you will be able to create the highest quality plots.

Approach

This book follows a cookbook style approach that puts orthogonal and non-redundant recipes in your hands. Rather than rehashing the user manual, the explanations expose the underlying logic behind matplotlib.

Who this book is for

If you are an engineer or scientist who wants to create great visualizations with Python, rather than yet another specialized language, this is the book for you. While there are several very competent plotting packages, matplotlib is “just” a Python module. Thus, if you know some Python already, you will feel at home from the first steps on. In case you are an application writer, you won't be left out since the integration of matplotlib is covered.


Produktinformation

  • Format: Kindle Edition
  • Dateigröße: 3019 KB
  • Seitenzahl der Print-Ausgabe: 224 Seiten
  • ISBN-Quelle für Seitenzahl: 1849513260
  • Verlag: Packt Publishing (26. März 2014)
  • Verkauf durch: Amazon Media EU S.à r.l.
  • Sprache: Englisch
  • ASIN: B00JAAW27U
  • Text-to-Speech (Vorlesemodus): Aktiviert
  • X-Ray:
  • Durchschnittliche Kundenbewertung: 4.0 von 5 Sternen  Alle Rezensionen anzeigen (1 Kundenrezension)
  • Amazon Bestseller-Rang: #237.628 Bezahlt in Kindle-Shop (Siehe Top 100 Bezahlt in Kindle-Shop)

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4.0 von 5 Sternen
4.0 von 5 Sternen
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4.0 von 5 Sternen Very useful as reference and inspiration source 20. April 2014
Format:Kindle Edition
This book has become my first reference when working with matplotlib. In particular the comprehensive examples starting from simple curves and ranging to very sophisticated data plots I very often find extremely useful. They not only provide solution but only give good ideas what is possible with data and matplotlib.

For more advanced users it might be an improvement to have some explanations about the data structure that comes with setting up a plot.
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Amazon.com: 4.2 von 5 Sternen  9 Rezensionen
2 von 2 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen A good alternative to the official matplotlib documentation 4. Juni 2014
Von Vaan - Veröffentlicht auf Amazon.com
Format:Taschenbuch
As a frequent matplotlib user I have to say that this book really fulfills it's promise as a cookbook by covering the most common use cases, and it is a pretty good and thorough introduction for beginners too (Python beginners as well as matplotlib beginners). However, the problem of this book is that there is the (free) matplotlib gallery (http://matplotlib.org/gallery.html) which also has plenty of very good examples, and I can imagine that it is a tough job as an author to add additional value to that.

What this book does very well is introducing matplotlib quite gently in the first chapter, which makes it quite attractive for Python & matplotlib beginners. But also here, we have the alternative free user guide available online http://matplotlib.org/contents.html

My main point of criticism why I find the matplotlib.org resources more accessible might be that they are actually in color: the plot and the code syntax. Unfortunately, the book only uses colors throughout the first chapter (and very very rarely for a handful of other plots later on), so that the largest portion of the plots are in gray-scale - also no syntax highlighting throughout this book. Since I have the ebook version, I do not fully understand why there is no coloring throughout the other chapters (especially the 2nd chapter, which is called "Chapter 2: Customizing Colors and Styles").

But overall, it covers matplotlib pretty well, and I'd recommend it as an alternative to the resources matplotlib.org.

But to it's defense, my hard copy of the "Gnuplot in Action" is also presented in gray-scales, and the "R Graphic's cookbook" also only makes use of colors rather sparingly. However, I think, nowadays in 2014 I'd at least expect the ebook to be in color - especially if you want to make it more attractive than the freely available online resources.

Not a real point of criticism but more like a suggestion for future editions: as big fan of it, I was actually looking for this section that mentions how to use it in IPython notebooks (%pylab inline vs. matplotlib inline), and maybe also plotly for additional value :)
5.0 von 5 Sternen matplotlib: the easy way 4. August 2014
Von Hudan Studiawan - Veröffentlicht auf Amazon.com
Format:Taschenbuch
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.
4.0 von 5 Sternen A solid introduction, but it may not add much beyond the official documentation 23. Juni 2014
Von Joe Kington - Veröffentlicht auf Amazon.com
Format:Taschenbuch
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.)
4.0 von 5 Sternen What you can do with this is Amazing! 3. Juni 2014
Von Amey - Veröffentlicht auf Amazon.com
Format:Taschenbuch
I read this book to for my project work! Its pretty simple to use.
The book is to the point and I could reference the topics very easily.

[...]
5.0 von 5 Sternen quick recipes, easy to follow 2. Juni 2014
Von Ty Sid - Veröffentlicht auf Amazon.com
Format:Taschenbuch
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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