Allen Yu - Matplotlib for Python Developers
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Leverage the power of Matplotlib to visualize and understand your data more effectively
About This Book- Perform effective data visualization with Matplotlib and get actionable insights from your data
- Design attractive graphs, charts, and 2D plots, and deploy them to the web
- Get the most out of Matplotlib in this practical guide with updated code and examples
This book is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. If youre a data scientist or analyst and wish to create attractive visualizations using Python, youll find this book useful. Some knowledge of Python programming is all you need to get started.
What You Will Learn- Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots
- Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of Matplotlib
- Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn
- Create interactive plots with real-time updates
- Develop web-based, Matplotlib-powered graph visualizations with third-party packages such as Django
- Write data visualization code that is readily expandable on the cloud platform
Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library.
Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, youll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. Youll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, youll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples.
By the end of this book, youll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations.
Style and approachStep by step approach to learning the best of Matplotlib 2.1.x
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Second Edition
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 authors, 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: Amey Varangaonkar
Acquisition Editor: Varsha Shetty
Content Development Editor: Mayur Pawanikar
Technical Editor: Prasad Ramesh
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Indexer: Mariammal Chettiyar
Graphics: Tania Dutta
Production Coordinator: Shantanu Zagade
First published: November 2009
Second edition: April 2018
Production reference: 1200418
Published by Packt Publishing Ltd.
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ISBN 978-1-78862-517-3
www.packtpub.com
Cancer has taken away my grandfather, my aunt, and my friend, I hate cancer. This book is dedicated to the memory of my grandfather, ChiuKhan Chan, who thought I shouldnt study that much. May he rest in peace.
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Aldrin Yim is a PhD candidate and Markey Scholar in the Computation and System Biology program at Washington University, School of Medicine. His research focuses on applying big data analytics and machine learning approaches in studying neurological diseases and cancer. He is also the founding CEO of Codex Genetics Limited, which provides precision medicine solutions to patients and hospitals in Asia.
Claire Chung is pursuing her PhD degree as a Bioinformatician at the Chinese University of Hong Kong. She enjoys using Python daily for work and lifehack. While passionate in science, her challenge-loving character motivates her to go beyond data analytics. She has participated in web development projects, as well as developed skills in graphic design and multilingual translation. She led the Campus Network Support Team in college, and shared her experience in data visualization in PyCon HK 2017.
Allen Yu, PhD, is a Chevening Scholar, 2017-18, and an MSC student in computer science at the University of Oxford. He holds a PhD degree in Biochemistry from the Chinese University of Hong Kong, and he has used Python and Matplotlib extensively during his 10 years of bioinformatics experience.
Apart from academic research, Allen is the co-founder of Codex Genetics Limited, which aims to provide a personalized medicine service in Asia through the use of the latest genomics technology.
, Introduction to Matplotlib , gets you familiar with the capabilities and functionalities of Matplotlib.
, Getting Started with Matplotlib , gets you started with basic plotting techniques using Matplotlib syntax.
, Decorating Graphs with Plot Styles and Types , shows how to beautify your plots and select the right kind of plot that communicates your data effectively.
, Advanced Matplotlib , teaches you how to group multiple relevant plots into subplots in one figure using nonlinear scales, axis scales, plotting images, and advanced plots with the help of some popular third-party packages.
, Embedding Matplotlib in GTK+3 , shows examples of embeding Matplotlib in applications using GTK+3.
, Embedding Matplotlib in Qt 5 , explains how to embed a figure in a QWidget, use layout manager to pack a figure in a QWidget, create a timer, react to events, and update a Matplotlib graph accordingly. We use QT Designer to draw a simple GUI for Matplotlib embedding.
, Embedding Matplotlib in wxWidgets Using wxPython , shows how you can use Matplotlib in the wxWidgets framework, particularly using wxPython bindings.
, Integrating Matplotlib with Web Applications , teaches you how to develop a simple site that displays the price of Bitcoin.
, Matplotlib in the Real World , begins our journey of understanding more advanced Matplotlib usage through real-world examples.
, Integrating Data Visualization into the Workflow, covers a mini-project combining the skills of data analytics with the visualization techniques you have learned.
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