June 2023
Intermediate to advanced
236 pages
6h 25m
English
Overview
Dive into the world of graph databases with "Graph Data Modeling in Python". This book offers a practical approach to mastering the skills needed for curating, analyzing, and visualizing data with graphs. Whether you're a data scientist or developer, you'll find step-by-step guidance on converting traditional data into effective graph data structures.
What this Book will help me do
- Understand and apply graph data modeling principles using Python.
- Learn to effectively store, query, and transform graph structures using libraries like NetworkX and igraph.
- Master schema design for graph databases with real-world examples and use cases.
- Implement and practice graph analytics for insights like community detection and recommendation engines.
- Transition from relational or tabular data models to graph-based solutions and workflows.
Author(s)
Gary Hutson and Matt Jackson are skilled data scientists and software developers with substantial experience in Python programming and graph data analysis. They combine their technical expertise with a passion for teaching to make graph data modeling accessible and practical. Their pragmatic approach allows readers to quickly apply learned techniques to real-world projects.
Who is it for?
This book is ideal for data analysts and database developers eager to harness the power of graph databases and for Python developers starting their journey in data science. If you're looking to understand and novelly use data frameworks, and are comfortable with Python basics, this book will guide you to the next level in your graph modeling knowledge.
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