Summary

From the bridges of 17^th century Königsberg to the internet, network science emerged from a diverse range of fields, all seeking to quantify and study relationships of some kind. The networks in network science model relationships as edges between nodes, which can represent anything from a species of flower, to an atom in a crystal, to an individual in a society. To quantify properties of relationships, edges can be directed and/or weighted. NetworkX provides Python classes and functions to create and manipulate such networks with ease. By now, you should have a sense of the types of problems network science and NetworkX can solve. The following chapters will cover various applications of network science as well as related features of NetworkX, with examples of how they can be applied to real datasets.