Matplotlib for Python Developers: Effective techniques for data visualization with Python, 2nd Edition: 9781788625173: Computer Science Books @ Amazon.com (original) (raw)

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

Key Features

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

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