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Matplotlib 3.0 Cookbook
Matplotlib 3.0 Cookbook

Matplotlib 3.0 Cookbook: Over 150 recipes to create highly detailed interactive visualizations using Python

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Matplotlib 3.0 Cookbook

Chapter 1. Anatomy of Matplotlib

This chapter will begin with an introduction to matplotlib including the architecture of matplotlib and the elements of a figure followed by the recipes. The following are the recipes that will be covered in this chapter: 

  • Working in interactive mode
  • Working in non-interactive mode
  • Reading from external files and plotting
  • How to change and reset default environment variables 
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Key benefits

  • Master Matplotlib for data visualization
  • Customize basic plots to make and deploy figures in cloud environments
  • Explore recipes to design various data visualizations from simple bar charts to advanced 3D plots

Description

Matplotlib provides a large library of customizable plots, along with a comprehensive set of backends. Matplotlib 3.0 Cookbook is your hands-on guide to exploring the world of Matplotlib, and covers the most effective plotting packages for Python 3.7. With the help of this cookbook, you'll be able to tackle any problem you might come across while designing attractive, insightful data visualizations. With the help of over 150 recipes, you'll learn how to develop plots related to business intelligence, data science, and engineering disciplines with highly detailed visualizations. Once you've familiarized yourself with the fundamentals, you'll move on to developing professional dashboards with a wide variety of graphs and sophisticated grid layouts in 2D and 3D. You'll annotate and add rich text to the plots, enabling the creation of a business storyline. In addition to this, you'll learn how to save figures and animations in various formats for downstream deployment, followed by extending the functionality offered by various internal and third-party toolkits, such as axisartist, axes_grid, Cartopy, and Seaborn. By the end of this book, you'll be able to create high-quality customized plots and deploy them on the web and on supported GUI applications such as Tkinter, Qt 5, and wxPython by implementing real-world use cases and examples.

Who is this book for?

The Matplotlib 3.0 Cookbook is for you if you are a data analyst, data scientist, or Python developer looking for quick recipes for a multitude of visualizations. This book is also for those who want to build variations of interactive visualizations.

What you will learn

  • Develop simple to advanced data visualizations in Matplotlib
  • Use the pyplot API to quickly develop and deploy different plots
  • Use object-oriented APIs for maximum flexibility with the customization of figures
  • Develop interactive plots with animation and widgets
  • Use maps for geographical plotting
  • Enrich your visualizations using embedded texts and mathematical expressions
  • Embed Matplotlib plots into other GUIs used for developing applications
  • Use toolkits such as axisartist, axes_grid1, and cartopy to extend the base functionality of Matplotlib

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 23, 2018
Length: 676 pages
Edition : 1st
Language : English
ISBN-13 : 9781789138665
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Product Details

Publication date : Oct 23, 2018
Length: 676 pages
Edition : 1st
Language : English
ISBN-13 : 9781789138665
Category :
Tools :

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Table of Contents

15 Chapters
Anatomy of Matplotlib Chevron down icon Chevron up icon
Getting Started with Basic Plots Chevron down icon Chevron up icon
Plotting Multiple Charts, Subplots, and Figures Chevron down icon Chevron up icon
Developing Visualizations for Publishing Quality Chevron down icon Chevron up icon
Plotting with Object-Oriented API Chevron down icon Chevron up icon
Plotting with Advanced Features Chevron down icon Chevron up icon
Embedding Text and Expressions Chevron down icon Chevron up icon
Saving the Figure in Different Formats Chevron down icon Chevron up icon
Developing Interactive Plots Chevron down icon Chevron up icon
Embedding Plots in a Graphical User Interface Chevron down icon Chevron up icon
Plotting 3D Graphs Using the mplot3d Toolkit Chevron down icon Chevron up icon
Using the axisartist Toolkit Chevron down icon Chevron up icon
Using the axes_grid1 Toolkit Chevron down icon Chevron up icon
Plotting Geographical Maps Using Cartopy Toolkit Chevron down icon Chevron up icon
Exploratory Data Analysis Using the Seaborn Toolkit Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
(5 Ratings)
5 star 20%
4 star 20%
3 star 20%
2 star 20%
1 star 20%
John C. May 20, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is a well written and thorough survey of the Matplotlib library with a solid introduction to the Seaborn library. You don't need to know anything about Matplotlib to get started. It starts with plotting a line through two points on default axes and adds more and more features to the examples as the book progresses.That said, you DO need a basic competency in Python to understand the explanations. This is, after all, a library of extensions to the Python language.Super helpful is full code for all the examples available for download. You can read the discussion, experiment with the example code and really understand what's going on. You'll need the free open source Jupyter Python IDE to run the code, but Jupyter is probably the most frequently used platform for running Matplotlib, and it's ideal for this kind of hands on learning.
Amazon Verified review Amazon
Saurabh Oct 02, 2019
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Matplotlib is tedious but you need to know it whether you are using pandas based plotting or seaborn.I like the fact that book is very detailed. I don't know of a better book right now to learn matplotlib. However, the approach uses a lot of state based plotting, which is no longer recommended. For example it uses a lot of plt.xticks() instead of ax.xticks() approach.Another problem is it does not show how to make plots using pandas data frame plot method. Since most people making plots today are using pandas, I'm disappointed that the data frame plot method was not covered.Overall this book is not for beginner python users. It will be appreciated more by intermediate python and pandas users.
Amazon Verified review Amazon
Student of the Universe Oct 23, 2022
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
I've not a seasoned Python developer, so, when I purchased this book, I was pleased to see it has all the content I was interested in learning. I downloaded the code for this book from GitHub, worked through the first two chapters, and then in chapter 3, I ran into multiple errors right off. It appears that the book is out of date and the GitHub site is not updated for the latest Python 3 that is installed with Anaconda (I'm using the Mac). So, there is a chart where the author called out what is required for Windows 10. I will have to use Parallels on the Mac to see if that works. Pitty.
Amazon Verified review Amazon
Richard McClellan May 15, 2019
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
It is a pretty good book. The code examples are clear, and well explained.HOWEVER. This is 2019. You buy a programming book (I bought the Kindle version) you expect to be able to access the code. Usually on-line or a download. Since you can't cut and past out of Kindle, typing in examples is wholly last century.Well, there is a website (packt) that supposedly lets you download. 95mb zipped file later, I find that it is some combination of pdf's and png's of output. No code. Some mysterious IPYNB extension. So--a last century level, effectively. Last century you got a CD.It would be at least 4 stars if I could get at the code without having to type it all in.Two stars because it isn't entirely worthless.
Amazon Verified review Amazon
Adrian Savage Apr 12, 2019
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
This is, as it says, a cookbook. That is it give recipes for many different uses for Matplotlib. What it fails to do is to give any useful information as to the Matplotlib modules, the uses to which they can be put and the syntax of each command. In fact, should you wish to find out how a call such as Matplotlib.dates.DateFormatter works, you will not even find it in the index. In fact date and time are not in the index so in the 652 mostly useless pages of the book, you will struggle to make a graph with date/time on the x axis. As a cookbook its recipes are without taste or interest.
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