28,14 €
Mehr erfahren.
- Herausgeber: Packt Publishing
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Understand and build beautiful and advanced plots with Matplotlib and Python
Key Features
- Practical guide with hands-on examples to design interactive plots
- Advanced techniques to constructing complex plots
- Explore 3D plotting and visualization using Jupyter Notebook
Book Description
In this book, you'll get hands-on with customizing your data plots with the help of Matplotlib. You'll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You'll explore non-trivial layouts, Pylab customization, and more about tile configuration. You'll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you'll explore them further in this book. You'll delve into niche plots and visualize ordinal and tabular data. In this book, you'll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will also be explored. Finally, you'll learn how to create interactive plots with the help of Jupyter.
Learn expert techniques for effective data visualization using Matplotlib 3 and Python with our latest offering -- Matplotlib 3.0 Cookbook
What you will learn
- Deal with non-trivial and unusual plots
- Understanding Basemap methods
- Customize and represent data in 3D
- Construct Non-Cartesian and vector plots
- Design interactive plots using Jupyter Notebook
- Make movies for enhanced data representation
Who this book is for
This book is aimed at individuals who want to explore data visualization techniques. A basic knowledge of Matplotlib and Python is required.
Das E-Book können Sie in Legimi-Apps oder einer beliebigen App lesen, die das folgende Format unterstützen:
Seitenzahl: 129
Veröffentlichungsjahr: 2018
Ähnliche
Mastering Matplotlib 2.x
Copyright © 2018 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
Commissioning Editor: Pavan RamchandaniAcquisition Editor:Dayne CastelinoContent Development Editor:Ronnel MathewTechnical Editor: Sagar SawantCopy Editor: Safis EditingProject Coordinator:Namrata SwettaProofreader: Safis EditingIndexer:Tejal Daruwale SoniGraphics: Jisha ChirayilProduction Coordinator:Jyoti Chauhan
First published: November 2018
Production reference: 1281118
Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK.
ISBN 978-1-78961-769-6
www.packtpub.com
Mapt is an online digital library that gives you full access to over 5,000 books and videos, as well as industry leading tools to help you plan your personal development and advance your career. For more information, please visit our website.
Why subscribe?
Spend less time learning and more time coding with practical eBooks and Videos from over 4,000 industry professionals
Improve your learning with Skill Plans built especially for you
Get a free eBook or video every month
Mapt is fully searchable
Copy and paste, print, and bookmark content
Packt.com
Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at www.packt.com and as a print book customer, you are entitled to a discount on the eBook copy. Get in touch with us at [email protected] for more details.
At www.packt.com, you can also read a collection of free technical articles, sign up for a range of free newsletters, and receive exclusive discounts and offers on Packt books and eBooks.
Contributors
About the author
Benjamin Walter Keller is currently a PhD candidate at McMaster University and gained his BSc in physics with a minor in computer science from the University of Calgary in 2011. His current research involves numerical modeling of galaxy evolution over cosmological timescales. As an undergraduate at the U of C, he worked on stacking radio polarization to examine faint extragalactic sources. He also worked in the POSSUM Working Group 2 to determine the requirements for stacking applications for the Australian SKA Pathfinder (ASKAP) radio telescope. He is particularly interested in questions involving stellar feedback (supernovae, stellar winds, and so on) and its impact on galaxies and their surrounding intergalactic medium.
Packt is searching for authors like you
If you're interested in becoming an author for Packt, please visit authors.packtpub.com and apply today. We have worked with thousands of developers and tech professionals, just like you, to help them share their insight with the global tech community. You can make a general application, apply for a specific hot topic that we are recruiting an author for, or submit your own idea.
Table of Contents
Title Page
Copyright and Credits
Mastering Matplotlib 2.x
About Packt
Why subscribe?
Packt.com
Contributors
About the author
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Download the color images
Conventions used
Get in touch
Reviews
Heavy Customization
Customizing PyLab using style
How to use styles to change the appearance of our plots
Different Matplotlib styles
Creating your own styles
Deep diving into color
Questions to ask when choosing a color map
Using color maps
Working on non-trivial layouts
The Matplotlib configuration files
Matplotlibrc – where does it live?
Summary
Drawing on Plots
Putting lines in place
Adding horizontal and vertical lines
Adding spans that cover whole regions
Adding and tweaking a background grid
Adding text on your plots
Adding text to both axis and figure objects
Adding text in multi-panel figures
Playing with polygons and shapes
Adding polygons and shapes to our plots
The built-in shapes that Matplotlib provides
Building your own polygons
Versatile annotating
Adding arrows to our plots with the annotate method
Adding some text to the arrows
Customizing the appearance of the annotations
Summary
Special Purpose Plots
Non-Cartesian plots
Creating polar axes
Applying log, symmetric log, and logistic scales to your axes
Plotting vector fields
Making vector plots with quiver
Customizing the appearance of vector plots
Annotating vector plots with a quiver key
Making stream plots
Statistics with boxes and violins
Making box plots to show the interquartile ranges and the outliers
Making violin plots show different distributions
Customizing the appearance of plots
Visualizing ordinal and tabular data
Pie charts
Tables
Customizing the appearance of plots
Summary
3D and Geospatial Plots
Plotting with 3D axes
How to add 3D axes to a figure
How to use the interactive backend to manipulate the 3D plots
How to plot on the 3D axes
Looking at various 3D plot types
How to rotate the camera in 3D plots
How to add line and scatter plots
How to add wireframe, surface, and triangular surface plots
How to add 3D contour types
The basemap methods
How to create map projections
How to choose between different kinds of map projections
Further reading
Plotting on map projections
How to add simple points and lines to our plots
How to draw great circles
How to draw a day/night terminator
Adding geography
How to add coastline and water features
How to add political boundaries for countries, states, and provinces
Summary
Interactive Plotting
Interactive plots in the Jupyter Notebook
How to install and enable the ipywidgets module
How to use the interact method to make basic widgets
How to view the different kinds of widgets that ipywidgets provides
How to customize widgets
Event handling with plot callbacks
How to add interactivity by capturing mouse events
How to capture keyboard clicks
How to use the picker to manipulate plots
GUI neutral widgets
How to add the basic GUI neutral widgets
A selection of the different kinds of widgets that are available in Matplotlib
How to add interactivity to these widgets using callbacks
Making movies
How to generate animations to make plots that update themselves
How to customize the animation frame rate, speed, and repetitions
How to save animations as mp4 videos and animated GIFs
Summary
Other Books You May Enjoy
Leave a review - let other readers know what you think
Preface
Mastering Matplotlib covers use cases and unusual cases that require powerful tools. With easy-to-follow examples and the high-end components of Matplotlib, this book will enable you to develop advanced and interactive plots using Python scripting and Matplotlib.
Matplotlib is a multi-platform data visualization tool built upon the NumPy and SciPy frameworks. One of Matplotlib's most important features is its ability to work well with many operating systems and graphics backends. In this book, you'll get hands-on with customizing your data plots with the help of Matplotlib. You'll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You'll explore non-trivial layouts, Pylab customization, and tile configuration. You'll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you'll explore them further in this book. You'll delve into niche plots and visualize ordinal and tabular data.
In this book, you'll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will be also be explored. Finally, you'll learn how to create interactive plots with the help of Jupyter. By the end of this book, you'll be able to construct advanced plots with additional customization techniques and 3D plot types.
Who this book is for
This book is aimed at individuals who want to explore data visualization techniques. Basic knowledge of Matplotlib and Python is required.
What this book covers
Chapter 1, Heavy Customization, covers customizing Pylab and also learn about working on non-trivial layouts and the different Matplotlib configuration files.
Chapter 2, Drawing on Plots, explains how to put lines in place and add text to your plots. We will also learn about playing with polygons, shapes, and versatile annotating.
Chapter 3, Special Purpose Plots, covers non-Cartesian plots and plotting vector fields. We will also learn about statistics with boxes and violins, and also visualize ordinal and tabular data.
Chapter 4, 3D and Geospatial, explores plotting with 3D axes, looking at the various 3D plot types and the Basemap methods. We will also learn about plotting on map projections and adding geography.
Chapter 5, Interactive Plotting, looks at interactive plots in Jupyter Notebook and event handling with plot callbacks. We will also learn about GUI neutral widgets and how to make movies.
To get the most out of this book
The readers should have basic knowledge of Python.
Download the example code files
You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.
You can download the code files by following these steps:
Log in or register at
www.packt.com
.
Select the
SUPPORT
tab.
Click on
Code Downloads & Errata
.
Enter the name of the book in the
Search
box and follow the onscreen instructions.
Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:
WinRAR/7-Zip for Windows
Zipeg/iZip/UnRarX for Mac
7-Zip/PeaZip for Linux
The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Mastering-Matplotlib-2.x. In case there's an update to the code, it will be updated on the existing GitHub repository.
We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!
Download the color images
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: http://www.packtpub.com/sites/default/files/downloads/9781789617696_ColorImages.pdf.
Conventions used
There are a number of text conventions used throughout this book.
CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "The easiest way to do this is to remove the plot keyword and call semilogy."
A block of code is set as follows:
import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt %matplotlib inline
Any command-line input or output is written as follows:
$ mkdir css
$ cd css
Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Select System info from the Administration panel."
Get in touch
Feedback from our readers is always welcome.
General feedback: If you have questions about any aspect of this book, mention the book title in the subject of your message and email us at [email protected].
Errata: Although we have taken every care to ensure the accuracy of our content, mistakes do happen. If you have found a mistake in this book, we would be grateful if you would report this to us. Please visit www.packt.com/submit-errata, selecting your book, clicking on the Errata Submission Form link, and entering the details.
Piracy: If you come across any illegal copies of our works in any form on the Internet, we would be grateful if you would provide us with the location address or website name. Please contact us at [email protected] with a link to the material.
If you are interested in becoming an author: If there is a topic that you have expertise in and you are interested in either writing or contributing to a book, please visit authors.packtpub.com.
Reviews
Please leave a review. Once you have read and used this book, why not leave a review on the site that you purchased it from? Potential readers can then see and use your unbiased opinion to make purchase decisions, we at Packt can understand what you think about our products, and our authors can see your feedback on their book. Thank you!
For more information about Packt, please visit packt.com.
Heavy Customization
This book will teach us about advanced Matplotlib plots. It will enable you to go from data to plot to insight, in order to take raw numbers, raw information, and turn them into a visualization, which will allow us to build within our mind the actual bit of insight on how the data behaves. This will also focus on the advanced tools to derive more subtle insights from your data.
In this chapter, we will be focusing on the advanced tools of plotting so that you can really derive more subtle insights from your data. The prerequisites for this course give us a basic understanding of Python and the ability to use NumPy to work with array data.
We will learn about the following topics:
Using style sheets to customize our plot's appearance
Working with Matplotlib colors
Building multi-panel plots with complex layouts
How to configure Matplotlib to use our preferences whenever we start up a new Matplotlib session
