quickgraph 0.21

A Python package to view the skeleton of a social graph quickly.

Introduction

QuickGraph library can help you get a quick overview of a social graph in an extremely convenient way. QuickGraph will show the basic information of a graph, plot the CDF of selected metrics, characterize the largest connected component (LCC).

Overview

QuickGraph library can help you get a quick overview of a social graph in an extremely convenient way. Show the basic information of a graph, plot the CDF of selected metrics, characterize the largest connected component (LCC), compute representative structural hole related indexes.
Copyright (C) <2021-2026> by Qingyuan Gong, Fudan University ([e-mail])

Before Installation

Please upgrade to Python 3.5

System Requirements

We have tested QuickGraph on both MacOSX (version 11.5.1) and Ubuntu (Version: 20.04 LTS). This library have not been tested on other platforms.

Usage

Please run the following commond and install the dependent libiraires:

Run conda config --add channels conda-forge

conda update –all to make the libraries fit to the operation system

Run conda install networkx to install the networkx library

Run conda install python-louvain to help the structural hole related analysis

Example

>>> import quickgraph as qg
>>> import networkx as nx
>>> G = nx.les_miserables_graph()
>>> qg.info(G)
Number of Nodes: 77, Number of Edges: 254
Avg. degree: 6.5974, Avg. clustering coefficient: 0.5731, Modularity (Louvain) = 0.5663
Number of connected components: 1, Number of nodes in LCC: 77 ( 100.0 %)
>>> qg.LCC_analysis(G,1,1,1)
LCC: Avg. degree = 6.5974, Avg. clustering coefficient = 0.5731, Modularity (Louvain) = 0.5663
(rough) shortest path length = 0 : 3 ( 0.3 %), 1 : 34 ( 3.4 %), 2 : 182 ( 18.2 %), 3 : 205 ( 20.5 %), 4 : 72 ( 7.2 %), 5 : 4 ( 0.4 %), Avg. shortest path length = 2.642

License

See the LICENSE file for license rights and limitations (MIT).