Arrays, Linked Lists, and Graphs: Why Connecting Your Data Makes Sense
Written by: Dr. Clair J. Sullivan, Data Science Advocate, Neo4j
Presented to Data Umbrella on March 15, 2022
email: clair.sullivan@neo4j.com
Twitter: @CJLovesData1
Last updated: March 14, 2022
This repository contains all of the code and slides used in the March 15th running of the Data Umbrella course, "Arrays, Linked Lists, and Graphs". You will need the following to follow along in the course:
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Access to a notebook environment such as Jupyter Notebook, Google Colab or the VS Code Notebook Environment.
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If you choose to work with a graph database, you can create a free one (demonstrated in the course) with the Neo4j Sandbox. For this course, we will be using the "Graph Data Science" sandbox, which is a pre-populated database of a Game of Thrones graph.
In addition to the above, you will need the following Python packages:
- pandas
- neo4j (the official Python driver for Neo4j)