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average_clustering¶

average_clustering
(G, nodes=None, weight=None, count_zeros=True)[source]¶ Compute the average clustering coefficient for the graph G.
The clustering coefficient for the graph is the average,
\[C = \frac{1}{n}\sum_{v \in G} c_v,\]where \(n\) is the number of nodes in \(G\).
Parameters: G : graph
nodes : container of nodes, optional (default=all nodes in G)
Compute average clustering for nodes in this container.
weight : string or None, optional (default=None)
The edge attribute that holds the numerical value used as a weight. If None, then each edge has weight 1.
count_zeros : bool (default=False)
If False include only the nodes with nonzero clustering in the average.
Returns: avg : float
Average clustering
Notes
This is a space saving routine; it might be faster to use the clustering function to get a list and then take the average.
Self loops are ignored.
References
[R201] Generalizations of the clustering coefficient to weighted complex networks by J. Saramäki, M. Kivelä, J.P. Onnela, K. Kaski, and J. Kertész, Physical Review E, 75 027105 (2007). http://jponnela.com/web_documents/a9.pdf [R202] Marcus Kaiser, Mean clustering coefficients: the role of isolated nodes and leafs on clustering measures for smallworld networks. http://arxiv.org/abs/0802.2512 Examples
>>> G=nx.complete_graph(5) >>> print(nx.average_clustering(G)) 1.0