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IPython Interactive Computing and Visualization Cookbook

You're reading from   IPython Interactive Computing and Visualization Cookbook Harness IPython for powerful scientific computing and Python data visualization with this collection of more than 100 practical data science recipes

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Product type Paperback
Published in Sep 2014
Publisher
ISBN-13 9781783284818
Length 512 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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Table of Contents (17) Chapters Close

Preface 1. A Tour of Interactive Computing with IPython FREE CHAPTER 2. Best Practices in Interactive Computing 3. Mastering the Notebook 4. Profiling and Optimization 5. High-performance Computing 6. Advanced Visualization 7. Statistical Data Analysis 8. Machine Learning 9. Numerical Optimization 10. Signal Processing 11. Image and Audio Processing 12. Deterministic Dynamical Systems 13. Stochastic Dynamical Systems 14. Graphs, Geometry, and Geographic Information Systems 15. Symbolic and Numerical Mathematics Index

Manipulating and visualizing graphs with NetworkX

In this recipe, we will show how to create, manipulate, and visualize graphs with NetworkX.

Getting ready

You can find the installation instructions for NetworkX in the official documentation at http://networkx.github.io/documentation/latest/install.html.

With Anaconda, you can type conda install networkx in a terminal. Alternatively, you can type pip install networkx. On Windows, you can also use Chris Gohlke's installer, available at www.lfd.uci.edu/~gohlke/pythonlibs/#networkx.

How to do it…

  1. Let's import NumPy, NetworkX, and matplotlib:
    In [1]: import numpy as np
            import networkx as nx
            import matplotlib.pyplot as plt
            %matplotlib inline
  2. There are many different ways of creating a graph. Here, we create a list of edges (pairs of node indices):
    In [2]: n = 10  # Number of nodes in the graph.
            # Each node is connected to the two next nodes,
            # in a circular fashion.
            adj = [(i, (i+1)%n...
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