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Python Data Science Essentials

You're reading from   Python Data Science Essentials Become an efficient data science practitioner by thoroughly understanding the key concepts of Python

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Product type Paperback
Published in Apr 2015
Publisher Packt
ISBN-13 9781785280429
Length 258 pages
Edition 1st Edition
Languages
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Toc

Graph algorithms


To get insights from graphs, many algorithms have been developed. In this chapter, we'll use a well-known graph in NetworkX, the Krackhardt Kite graph. It is a dummy graph containing 10 nodes, and it is typically used to proof graph algorithms. Krackhardt is the creator of the structure, which has the shape of a kite. It's composed of two different zones. In the first zone (composed of nodes 0 to 6), the nodes are interlinked; in the other zone (nodes 7 to 9), they are connected as a chain:

In: G = nx.krackhardt_kite_graph()
nx.draw_networkx(G)
plt.show()

Let's start with connectivity. Two nodes of a graph are connected if there is at least a path (that is, a sequence of traversed nodes) between them.

Note

Note that in a directed graph, you must follow the link's directions.

If at least a path exists, the shortest path between the two nodes is the one with the shortest collection of traversed nodes.

In NetworkX, checking whether a path exists between two nodes, calculating the...

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