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Matplotlib 2.x By Example

More Information
Learn
  • Familiarize with the latest features in Matplotlib 2.x
  • Create data visualizations on 2D and 3D charts in the form of bar charts, bubble charts, heat maps, histograms, scatter plots, stacked area charts, swarm plots and many more.
  • Make clear and appealing figures for scientific publications.
  • Create interactive charts and animation.
  • Extend the functionalities of Matplotlib with third-party packages, such as Basemap, GeoPandas, Mplot3d, Pandas, Scikit-learn, and Seaborn.
  • Design intuitive infographics for effective storytelling.
About

Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization.

Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples.

It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts.

By the end of this book, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This book will guide you to prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable.

Features
  • Create and customize live graphs, by adding style, color, font to make appealing graphs.
  • A complete guide with insightful use cases and examples to perform data visualizations with Matplotlib's extensive toolkits.
  • Create timestamp data visualizations on 2D and 3D graphs in form of plots, histogram, bar charts, scatterplots and more.
Page Count 334
Course Length 10 hours 1 minutes
ISBN9781788295260
Date Of Publication 27 Aug 2017

Authors

Allen Yu

Allen Yu, PhD, is a Chevening Scholar, 2017-18, and an MSC student in computer science at the University of Oxford. He holds a PhD degree in Biochemistry from the Chinese University of Hong Kong, and he has used Python and Matplotlib extensively during his 10 years of bioinformatics experience.

Apart from academic research, Allen is the co-founder of Codex Genetics Limited, which aims to provide a personalized medicine service in Asia through the use of the latest genomics technology.

Claire Chung

Claire Chung is pursuing her PhD degree as a Bioinformatician at the Chinese University of Hong Kong. She enjoys using Python daily for work and lifehack. While passionate in science, her challenge-loving character motivates her to go beyond data analytics. She has participated in web development projects, as well as developed skills in graphic design and multilingual translation. She led the Campus Network Support Team in college, and shared her experience in data visualization in PyCon HK 2017.

Aldrin Yim

Aldrin Yim is a PhD candidate and Markey Scholar in the Computation and System Biology program at Washington University, School of Medicine. His research focuses on applying big data analytics and machine learning approaches in studying neurological diseases and cancer. He is also the founding CEO of Codex Genetics Limited, which provides precision medicine solutions to patients and hospitals in Asia.