Matplotlib for Python Developers: Effective techniques for data visualization with Python, 2nd Edition - Tapa blanda

Reseña del editor

Leverage the power of Matplotlib to visualize and understand your data more effectively

Key Features

• 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

Book Description

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, you'll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You'll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you'll 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, you'll 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.

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

Who This Book Is For

This book is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. If you're a data scientist or analyst and wish to create attractive visualizations using Python, you'll find this book useful. Some knowledge of Python programming is all you need to get started.

Table of Contents

1. Introduction to Matplotlib
2. Getting Started with Matplotlib
3. Decorate Graphs with Plot Styles and Types
4. Advanced Matplotlib
5. Embedding Matplotlib in GTK+3
6. Embedding Matplotlib in Qt 5
7. Embedding Matplotlib in wxWidgets using wxPython
8. Integrating Matplotlib to web applications
9. Matplotlib in the Real World
10. Integrating interactive, real-time visualization technique into your current workflow

Biografía del autor

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.