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Data Analysis with Python

You're reading from   Data Analysis with Python A Modern Approach

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789950069
Length 490 pages
Edition 1st Edition
Languages
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Author (1):
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David Taieb David Taieb
Author Profile Icon David Taieb
David Taieb
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Table of Contents (14) Chapters Close

Preface 1. Programming and Data Science – A New Toolset FREE CHAPTER 2. Python and Jupyter Notebooks to Power your Data Analysis 3. Accelerate your Data Analysis with Python Libraries 4. Publish your Data Analysis to the Web - the PixieApp Tool 5. Python and PixieDust Best Practices and Advanced Concepts 6. Analytics Study: AI and Image Recognition with TensorFlow 7. Analytics Study: NLP and Big Data with Twitter Sentiment Analysis 8. Analytics Study: Prediction - Financial Time Series Analysis and Forecasting 9. Analytics Study: Graph Algorithms - US Domestic Flight Data Analysis 10. The Future of Data Analysis and Where to Develop your Skills A. PixieApp Quick-Reference Other Books You May Enjoy Index

Getting started with the networkx graph library


Before we start, if not already done, we need to install the networkx library using the pip tool. Execute the following code in its own cell:

!pip install networkx

Note

Note: As always, don't forget to restart the kernel after the installation is complete.

Most of the algorithms provided by networkx are directly callable from the main module. Therefore a user will only need the following import statement:

import networkx as nx

Creating a graph

As a starting point, let's review the different types of graphs supported by networkx and the constructors that create empty graphs:

  • Graph: An undirected graph with only one edge between vertices allowed. Self-loop edges are permitted. Constructor example:

    G = nx.Graph()
  • Digraph: Subclass of Graph that implements a directed graph. Constructor example:

    G = nx.DiGraph()
  • MultiGraph: Undirected graph that allows multiple edges between vertices. Constructor example:

    G = nx.MultiGraph()
  • MultiDiGraph: Directed graph...

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