Matplotlib for Python Developers Second Edition

<Matplotlib for Python Developers Second Edition> ▶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

▶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

▶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.

▶What this book covers
⦁ Chapter 1, Introduction to Matplotlib, gets you familiar with the capabilities and
functionalities of Matplotlib.
⦁ Chapter 2, Getting Started with Matplotlib, gets you started with basic plotting techniques using Matplotlib syntax.
⦁ Chapter 3, 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.
⦁ Chapter 4, 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.
⦁ Chapter 5, Embedding Matplotlib in GTK+3, shows examples of embeding Matplotlib in applications using GTK+3.
⦁ Chapter 6, 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.
⦁ Chapter 7, Embedding Matplotlib in wxWidgets Using wxPython, shows how you can use Matplotlib in the wxWidgets framework, particularly using wxPython bindings.
⦁ Chapter 8, Integrating Matplotlib with Web Applications, teaches you how to develop a simple site that displays the price of Bitcoin.
⦁ Chapter 9, Matplotlib in the Real World, begins our journey of understanding more advanced Matplotlib usage through real-world examples.
⦁ Chapter 10, Integrating Data Visualization into the Workflow, covers a mini-project combining the skills of data analytics with the visualization techniques you have learned.