NetworkX

NetworkX

A graph created with NetworkX
Original author(s)	Aric Hagberg Pieter Swart Dan Schult
Developer(s)	Many others
Initial release	11 April 2005; 19 years ago (2005-04-11)[1][2]
Written in	Python
Operating system	Cross-platform
Type	Software library
License	BSD-new license
Website	networkx.github.io

Network science
Theory
Graph Complex network Contagion Small-world Scale-free Community structure Percolation Evolution Controllability Graph drawing Social capital Link analysis Optimization Reciprocity Closure Homophily Transitivity Preferential attachment Balance theory Network effect Social influence
Network types
Informational (computing) Telecommunication Transport Social Scientific collaboration Biological Artificial neural Interdependent Semantic Spatial Dependency Flow on-Chip
Graphs
Features Clique Component Cut Cycle Data structure Edge Loop Neighborhood Path Vertex Adjacency list / matrix Incidence list / matrix Types Bipartite Complete Directed Hyper Multi Random Weighted
Metrics Algorithms
Centrality Degree Betweenness Closeness PageRank Motif Clustering Degree distribution Assortativity Distance Modularity Efficiency
Models
Topology Random graph Erdős–Rényi Barabási–Albert Fitness model Watts–Strogatz Exponential random (ERGM) Random geometric (RGG) Hyperbolic (HGN) Hierarchical Stochastic block Maximum entropy Soft configuration LFR Benchmark Dynamics Boolean network agent based Epidemic/SIR
Lists Categories
Topics Software Network scientists Category:Network theory Category:Graph theory
v t e

NetworkX is a Python library for studying graphs and networks. NetworkX is free software released under the BSD-new license.

Features

• Classes for graphs and digraphs.
• Conversion of graphs to and from several formats.
• Ability to construct random graphs or construct them incrementally.
• Ability to find subgraphs, cliques, k-cores.
• Explore adjacency, degree, diameter, radius, center, betweenness, etc.
• Draw networks in 2D and 3D.

Suitability

NetworkX is suitable for operation on large real-world graphs: e.g., graphs in excess of 10 million nodes and 100 million edges.^{[clarification needed][3]} Due to its dependence on a pure-Python "dictionary of dictionary" data structure, NetworkX is a reasonably efficient, very scalable, highly portable framework for network and social network analysis.^[4]

Integration

NetworkX is integrated into SageMath.^[5]

See also

• Social network analysis software
• JGraph

References

External links

• Official website: networkx.github.io
• NetworkX discussion group
• Survey of existing graph theory software
• NetworkX on StackOverflow
• on GitHub

0.00 (0 votes) Original source: https://en.wikipedia.org/wiki/NetworkX. Read more