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Exploring the Interconnected World: Network/Graph Analysis in Python

Repository of 90 minutes training session held at ODSC West 2021 & ODSC East 2021.


Networks, also known as graphs are one of the most crucial data structures in our increasingly intertwined world. Social friendship networks, the world-wide-web, financial systems, infrastructure (power grid, streets), etc. are all network structures. Knowing how to analyze the underlying network topology of interconnected systems can provide an invaluable skill in anyone's toolbox. This tutorial will provide a hands-on guide on how to approach a network analysis project from scratch and end-to-end: how to generate, manipulate, analyze and visualize graph structures that will help you gain insight about relationships between elements in your data.

Session Outline

Lesson 1: Generate & manipulate graph structures. Learn how to generate basic network types, and the most often encountered network models in real data. Next, discover the most informative network measures to understand network structures and behaviors.

Lesson 2: Analyze and visualize networks. Extract information about real public social network data by building, analyzing and visualizing it to gain understanding about its structure and behaviors.


  1. Installation of NetworkX Python library:
  2. We will use Jupyter Notebooks throughout the session:
  3. A couple of days prior the session the used Jupyter Notebook and data files will be downloadable from this GitHub repository:



Slides and code repository for 90 minutes training session held at ODSC West 2020.






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