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 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, scatter plots, and swarm plots * Get acquainted with GTK+ and Qt 5 to understand the UI back end of Matplotlib * Develop advanced static plots with third-party packages such as Pandas, GeoPandas, Seaborn, and Scikit-learn * Create interactive plots locally with real-time updates using GTK+ and Qt 5 * Develop web-based, Matplotlib-powered graph visualizations with third-party packages such as Flask and 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. This book shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to the 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+, Qt 5, and WXWIDGETS. Youll also be able to tweak the look and feel of your visualization with the help of the 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 Flask and 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 leverage its power to build attractive, insightful, and powerful visualizations.
Author: Aldrin Yim