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Python Data Science Essentials

You're reading from   Python Data Science Essentials A practitioner's guide covering essential data science principles, tools, and techniques

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789537864
Length 472 pages
Edition 3rd Edition
Languages
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Authors (2):
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Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Alberto Boschetti Alberto Boschetti
Author Profile Icon Alberto Boschetti
Alberto Boschetti
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Toc

Table of Contents (11) Chapters Close

Preface 1. First Steps 2. Data Munging FREE CHAPTER 3. The Data Pipeline 4. Machine Learning 5. Visualization, Insights, and Results 6. Social Network Analysis 7. Deep Learning Beyond the Basics 8. Spark for Big Data 9. Strengthen Your Python Foundations 10. Other Books You May Enjoy

Introduction to graph theory

Basically, a graph is a data structure that's able to represent relations in a collection of objects. Under this paradigm, the objects are the graph's nodes and the relations are the graph's links (or edges). The graph is directed if the links have an orientation (conceptually, they're like the one-way streets of a city); otherwise, the graph is undirected. In the following table, examples of well-known graphs are provided:

Graph example

Type

Nodes

Edges

World Wide Web

Directed

Web pages

Links

Facebook

Undirected

People

Friendship

Twitter

Directed

People

Follower

IP network

Undirected

Hosts

Wires/Connections

Navigation systems

Directed

Places/Addresses

Streets

Wikipedia

Directed

Pages

Anchor links

Scientific literature

Directed

Papers

Citations

Markov...

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