Book Image

Practical Data Science Cookbook, Second Edition - Second Edition

By : Prabhanjan Narayanachar Tattar, Bhushan Purushottam Joshi, Sean Patrick Murphy, ABHIJIT DASGUPTA, Anthony Ojeda
Book Image

Practical Data Science Cookbook, Second Edition - Second Edition

By: Prabhanjan Narayanachar Tattar, Bhushan Purushottam Joshi, Sean Patrick Murphy, ABHIJIT DASGUPTA, Anthony Ojeda

Overview of this book

As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don’t. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python.
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface

Importing networks


The dataset we will explore in this chapter is fun. It's the Marvel Universe Social Graph dataset constructed by Cesc Rosselló, Ricardo Alberich, and Joe Miro as part of their research on disordered systems and neural networks ( http://bioinfo.uib.es/~joemiro/marvel.html ). They created the network by compiling characters with the comic books in which they appear; as it turns out, the network actually mimics a real-world social network. Since then, there have been many visualizations of, and other mashups using this famous dataset (as well as extensions). In this recipe, we will import the needed data into our Python environment.

Getting ready

Once you have installed the needed libraries from the preceding recipe, you will need to use the dataset provided with the chapter.

How to do it...

Perform the following steps to import the data:

  1. In order to get this graph into a NetworkX graph representation, iterate over the dataset and add edges (which automatically create the nodes...