# Assortativity#

## Assortativity#

 `degree_assortativity_coefficient`(G[, x, y, ...]) Compute degree assortativity of graph. `attribute_assortativity_coefficient`(G, attribute) Compute assortativity for node attributes. `numeric_assortativity_coefficient`(G, attribute) Compute assortativity for numerical node attributes. Compute degree assortativity of graph.

## Average neighbor degree#

 `average_neighbor_degree`(G[, source, target, ...]) Returns the average degree of the neighborhood of each node.

## Average degree connectivity#

 `average_degree_connectivity`(G[, source, ...]) Compute the average degree connectivity of graph. `k_nearest_neighbors`(G[, source, target, ...]) Compute the average degree connectivity of graph.

## Mixing#

 `attribute_mixing_matrix`(G, attribute[, ...]) Returns mixing matrix for attribute. `degree_mixing_matrix`(G[, x, y, weight, ...]) Returns mixing matrix for attribute. `numeric_mixing_matrix`(G, attribute[, nodes, ...]) Returns numeric mixing matrix for attribute. `attribute_mixing_dict`(G, attribute[, nodes, ...]) Returns dictionary representation of mixing matrix for attribute. `degree_mixing_dict`(G[, x, y, weight, nodes, ...]) Returns dictionary representation of mixing matrix for degree. `mixing_dict`(xy[, normalized]) Returns a dictionary representation of mixing matrix.

## Pairs#

 `node_attribute_xy`(G, attribute[, nodes]) Returns iterator of node-attribute pairs for all edges in G. `node_degree_xy`(G[, x, y, weight, nodes]) Generate node degree-degree pairs for edges in G.