GDS Python Client

Move from interactive exploration to automated workflows. In this module, you'll use the Python GDSAnalysing data through the structure of its connections. Also the name of the Neo4j library that implements it. client to run graph algorithms programmatically.

You'll learn:

• How to connect to Neo4j and run algorithms using Python
• How to work with algorithm results as pandas DataFrames
• How to apply PageRankA centrality algorithm that scores a node by the number of nodes pointing at it and by how important those nodes are., Betweenness, LouvainA community detection algorithm that repeatedly merges nodes into groups for as long as merging raises modularity., and FastRPA node embedding algorithm, short for Fast Random Projection. It builds each node's vector by combining random vectors drawn from the nodes around it. to a citation network

This module demonstrates GDS applied to academic citation analysis.