Skip to main content
`Ctrl`+`K`

# 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.
`degree_pearson_correlation_coefficient`(G[, ...]) | 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.

## Mixing

`attribute_mixing_matrix`(G, attribute[, ...]) | Returns mixing matrix for attribute.
`degree_mixing_matrix`(G[, x, y, weight, ...]) | Returns 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]) | Yields 2-tuples of node attribute values for all edges in `G`.
`node_degree_xy`(G[, x, y, weight, nodes]) | Yields 2-tuples of `(degree, degree)` values for edges in `G`.