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Matplotlib for Python Developers

You're reading from   Matplotlib for Python Developers Effective techniques for data visualization with Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788625173
Length 300 pages
Edition 2nd Edition
Languages
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Authors (3):
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Claire Chung Claire Chung
Author Profile Icon Claire Chung
Claire Chung
Aldrin Yim Aldrin Yim
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Aldrin Yim
Allen Yu Allen Yu
Author Profile Icon Allen Yu
Allen Yu
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Matplotlib FREE CHAPTER 2. Getting Started with Matplotlib 3. Decorating 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 with Web Applications 9. Matplotlib in the Real World 10. Integrating Data Visualization into the Workflow

Preface

Python is a general-purpose programming language that's increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python that's used to design effective plots and graphs. This book 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, you'll embed and customize your plots in third-party tools such as GTK+, Qt 5, and WXWIDGETS.

You'll 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, you'll 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, you'll 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.

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