Book Image

Python Data Science Essentials

Book Image

Python Data Science Essentials

Overview of this book

The book starts by introducing you to setting up your essential data science toolbox. Then it will guide you across all the data munging and preprocessing phases. This will be done in a manner that explains all the core data science activities related to loading data, transforming and fixing it for analysis, as well as exploring and processing it. Finally, it will complete the overview by presenting you with the main machine learning algorithms, the graph analysis technicalities, and all the visualization instruments that can make your life easier in presenting your results. In this walkthrough, structured as a data science project, you will always be accompanied by clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
Table of Contents (13 chapters)

Chapter 5. Social Network Analysis

Social Network Analysis, usually referred to as SNA, models and studies the relationships of a group of social entities, which exist in the form of a network. An entity can be a person, a computer, or a webpage, and a relation can be a like, link, or a friendship (that is, a connection between the entities).

In this chapter, you'll learn about the following:

  • Graphs, since social networks are usually represented in this form

  • Important algorithms that are used to gain insights from a graph

  • How to load, dump, and sample large graphs