1. Aprender
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  3. Introduction to Network Analysis in Python
  • 1

    Introduction to networks

    Gratuito

    In this chapter, you'll be introduced to fundamental concepts in network analytics while exploring a real-world Twitter network dataset. You'll also learn about NetworkX, a library that allows you to manipulate, analyze, and model graph data. You'll learn about the different types of graphs and how to rationally visualize them.

  • 2

    Important nodes

    You'll learn about ways to identify nodes that are important in a network. In doing so, you'll be introduced to more advanced concepts in network analysis as well as the basics of path-finding algorithms. The chapter concludes with a deep dive into the Twitter network dataset which will reinforce the concepts you've learned, such as degree centrality and betweenness centrality.

  • 3

    Structures

    This chapter is all about finding interesting structures within network data. You'll learn about essential concepts such as cliques, communities, and subgraphs, which will leverage all of the skills you acquired in Chapter 2. By the end of this chapter, you'll be ready to apply the concepts you've learned to a real-world case study.

  • 4

    Bringing it all together

    In this final chapter of the course, you'll consolidate everything you've learned through an in-depth case study of GitHub collaborator network data. This is a great example of real-world social network data, and your newly acquired skills will be fully tested. By the end of this chapter, you'll have developed your very own recommendation system to connect GitHub users who should collaborate together.

Initializing

Exercicio

Finding nodes involved in triangles

NetworkX provides an API for counting the number of triangles that every node is involved in: nx.triangles(G). It returns a dictionary of nodes as the keys and number of triangles as the values. Your job in this exercise is to modify the function defined earlier to extract all of the nodes involved in a triangle relationship with a given node.

Instruções

100 XP
  • Write a function nodes_in_triangle() that has two parameters - G and n - and identifies all nodes in a triangle relationship with a given node.
    • In the for loop, iterate over all possible triangle relationship combinations.
    • Check whether the nodes n1 and n2 have an edge between them. If they do, add both nodes to the set triangle_nodes.
  • Use your function in an assert statement to check that the number of nodes involved in a triangle relationship with node 1 of graph T is equal to 35.