Publisher's Synopsis
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
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 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
In Detail
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.
Style and approach
Step by step approach to learning the best of Matplotlib 2.1.x
