Explore complex network theory, metrics, and analysis via Python's NetworkX. Gain insights into creating, visualizing, and applying networks in fields like machine learning and data analysis.

Introduction to complex network analusis.png

netwprl.tar.gz

networkx

Complex networks are a powerful data structure capable of modeling several complex data relationships such as social media interactions, ecosystems, energy systems, and financial information.

In this course, you’ll learn the basic theory behind complex networks and the metrics commonly used to analyze them. Then, you’ll learn how to create complex networks, visualize them, and calculate their analysis metrics using NetworkX, the most used Python library for complex network analysis. Finally, you’ll learn some advanced applications of complex networks, such as machine learning applications and embedding generation using complex networks.

By the end of this course, you’ll have a basic understanding of what complex networks are and how you can use them in your application using Python. With this knowledge, you can generate more advanced analyses and examine data from new perspectives, improving your analytical skills.

Introduction to Complex Network Analysis with Python

Which data representation should *not* be used for a sparse network?

Which data representation should not be used for a sparse network?

By setting an edge from the node to itself.

We can’t because an adjacency matrix is required.

By creating a node list and adding it to the graph with the `G.add_nodes_from()` method.

How can we add singletons to a NetworkX graph that was created using an edge list?

How can we add singletons to a NetworkX graph that was created using an edge list?

It’s a class that adds nodes to a list.

It’s a method that generates a graph given some rules.

It’s a variable inside a graph that extracts its creation rule.

There’s no graph generator inside NetworkX.

Which format can we *not* read with NetworkX?

Which format can we not read with NetworkX?

We can use the `with_labels` parameter in the `draw()` method.

We can use the `node_labels` parameter in the `plot()` method.

How can we add node labels to a NetworkX graph plot?

How can we add node labels to a NetworkX graph plot?

Test your knowledge of graphs and complex network handling in Python

Introduction to Graphs and Complex Networks

Assess Your Knowledge of Graphs and Complex Networks

Graphs and Complex Networks in Python

Complex Networks Measurements

Assess Your Knowledge of Complex Networks in Python

Random Graphs and Complex Networks Models

Community Detection in Complex Networks

Assess Your Knowledge of Network Models and Community Detection

Similarity in Complex Networks

Assess Your Knowledge of Similarity in Complex Networks

Complex Network Embeddings

Assess Your Knowledge of Network Embeddings

Wrap Up

Quiz: Graphs and Complex Networks in Python