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You're reading from  Matplotlib for Python Developers. - Second Edition

Product typeBook
Published inApr 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781788625173
Edition2nd Edition
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Authors (3):
Aldrin Yim
Aldrin Yim
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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.
Read more about Aldrin Yim

Claire Chung
Claire Chung
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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.
Read more about Claire Chung

Allen Yu
Allen Yu
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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.
Read more about Allen Yu

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Drawing Subplots


In designing layouts of visual aids, it is often necessary to organize multiple relevant plots into panels in the same figure, such as when illustrating different aspects of the same dataset. Matplotlib provides a few ways to create figures with multiple subplots.

Initiating a figure with plt.figure()

The plt.figure() API is the API that is used to initiate a figure that serves as the base canvas. It takes in arguments that determines the number of figures and parameters such as size and background color of the plot image. It displays a new area as the canvas for plotting axes when called. We wouldn't obtain any graphical output unless we add other plotting elements. If we were to call plt.show() at this point, we would see a Matplotlib figure object being returned, as shown in the following screen capture:

When we are plotting simple figures that involve only a single plot, without the need for multiple panels, we can omit calling plt.figure(). If plt.figure() is not called...

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Matplotlib for Python Developers. - Second Edition
Published in: Apr 2018Publisher: PacktISBN-13: 9781788625173

Authors (3)

author image
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.
Read more about Aldrin Yim

author image
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.
Read more about Claire Chung

author image
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.
Read more about Allen Yu