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Chapter 8 - Implementation: storing and manipulating network data

from Part II - Applications, tools, and tasks

Published online by Cambridge University Press:  aN Invalid Date NaN

James Bagrow  and
Yong‐Yeol Ahn
James Bagrow
Affiliation:
University of Vermont
Yong‐Yeol Ahn
Affiliation:
Indiana University, Bloomington
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Summary

In this chapter, we discuss how to represent network data inside a computer, with some examples of computational tasks and the data structures that enable those computations. When working with network data using code, you have many choices of data structures---but which ones are best for our given goals? Writing your own code to process network data can be valuable, yet existing libraries, which feature extensively-tested and efficiently-engineered functionalities, are worth considering as well. Python and R, both excellent programming languages for data science, come well-equipped with third-party libraries for working with network data, and we describe some examples. We also discuss choosing and using typical file formats for storing network data, as many standard formats exist.

Keywords

Network data representationComputational tasksData structuresProgramming languages for data scienceThird-party libraries for network dataPython for network dataR for network dataFile formats for network dataEfficient data processingLibraries vs. custom code
Type
Chapter
Information
Working with Network Data
A Data Science Perspective
 , pp. 89 - 104
Publisher: Cambridge University Press
Print publication year: 2024

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