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Learning IPython for Interactive Computing and Data Visualization, Second Edition

You're reading from   Learning IPython for Interactive Computing and Data Visualization, Second Edition Get started with Python for data analysis and numerical computing in the Jupyter notebook

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783986989
Length 200 pages
Edition 1st Edition
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Author (1):
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Cyrille Rossant Cyrille Rossant
Author Profile Icon Cyrille Rossant
Cyrille Rossant
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matplotlib and seaborn essentials


matplotlib is the main plotting library in Python. While it is particularly rich and powerful, it may be difficult to use sometimes. Further, its default styling could be better. There is some work in progress to improve the default styling in matplotlib. In the meantime, the seaborn library offers better styling for matplotlib as well as easy-to-use high-level statistical plotting routines based on matplotlib.

In this section, we will detail some of the main plotting capabilities of matplotlib, while using the seaborn styling.

We first import matplotlib and seaborn and we activate the inline mode in the Notebook:

In [1]: import numpy as np
        import matplotlib.pyplot as plt
        import seaborn
        %matplotlib inline

Note

There is a pylab mode that imports all NumPy and matplotlib variables into the interactive namespace. This mode makes the transition easier for users coming from MATLAB. However, using this mode is not recommended. The standard...

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