in_degree_centrality#

in_degree_centrality(G)[source]#

Compute the in-degree centrality for nodes.

The in-degree centrality for a node v is the fraction of nodes its incoming edges are connected to.

Parameters:

Ggraph: A NetworkX graph

Returns:

nodesdictionary: Dictionary of nodes with in-degree centrality as values.

Raises:

NetworkXNotImplemented: If G is undirected.

See also

degree_centrality, out_degree_centrality

Notes

The degree centrality values are normalized by dividing by the maximum possible degree in a simple graph n-1 where n is the number of nodes in G.

For multigraphs or graphs with self loops the maximum degree might be higher than n-1 and values of degree centrality greater than 1 are possible.

Examples

>>> G = nx.DiGraph([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)])
>>> nx.in_degree_centrality(G)
{0: 0.0, 1: 0.3333333333333333, 2: 0.6666666666666666, 3: 0.6666666666666666}
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Additional backends implement this function

cugraph : GPU-accelerated backend.

graphblas : OpenMP-enabled sparse linear algebra backend.