momepy.closeness_centrality(graph, name='closeness', weight='mm_len', radius=None, distance=None, verbose=True, **kwargs)[source]#

Calculates the closeness centrality for nodes.

Wrapper around networkx.closeness_centrality.

Closeness centrality of a node u is the reciprocal of the average shortest path distance to u over all n-1 nodes within reachable nodes.

\[C(u) = \frac{n - 1}{\sum_{v=1}^{n-1} d(v, u)},\]

where \(d(v, u)\) is the shortest-path distance between \(v\) and \(u\), and \(n\) is the number of nodes that can reach \(u\).


Graph representing street network. Ideally generated from GeoDataFrame using momepy.gdf_to_nx()

namestr, optional

calculated attribute name

weightstr (default ‘mm_len’)

attribute holding the weight of edge (e.g. length, angle)

radius: int

Include all neighbors of distance <= radius from n

distancestr, optional

Use specified edge data key as distance. For example, setting distance=’weight’ will use the edge weight to measure the distance from the node n during ego_graph generation.

verbosebool (default True)

if True, shows progress bars in loops and indication of steps


kwargs for networkx.closeness_centrality




>>> network_graph = mm.closeness_centrality(network_graph)