Returns the average degree of the neighborhood of each node.
The average degree of a node is
where are the neighbors of node and is the degree of node which belongs to . For weighted graphs, an analogous measure can be defined [R133],
where is the weighted degree of node , is the weight of the edge that links and and are the neighbors of node .
Parameters :  G : NetworkX graph source : string (“in””out”)
target : string (“in””out”)
nodes : list or iterable, optional
weight : string or None, optional (default=None)


Returns :  d: dict :

See also
Notes
For directed graphs you can also specify indegree or outdegree by passing keyword arguments.
References
[R133]  (1, 2) A. Barrat, M. Barthélemy, R. PastorSatorras, and A. Vespignani, “The architecture of complex weighted networks”. PNAS 101 (11): 3747–3752 (2004). 
Examples
>>> G=nx.path_graph(4)
>>> G.edge[0][1]['weight'] = 5
>>> G.edge[2][3]['weight'] = 3
>>> nx.average_neighbor_degree(G)
{0: 2.0, 1: 1.5, 2: 1.5, 3: 2.0}
>>> nx.average_neighbor_degree(G, weight='weight')
{0: 2.0, 1: 1.1666666666666667, 2: 1.25, 3: 2.0}
>>> G=nx.DiGraph()
>>> G.add_path([0,1,2,3])
>>> nx.average_neighbor_degree(G, source='in', target='in')
{0: 1.0, 1: 1.0, 2: 1.0, 3: 0.0}
>>> nx.average_neighbor_degree(G, source='out', target='out')
{0: 1.0, 1: 1.0, 2: 0.0, 3: 0.0}