Graph Data Modeling in Python
Graph Data Modeling with Python is your guide to building real-world use cases of how to prepare graph data for modeling, converting tabular to graph data structures, and working through simple graph use cases using degree centrality. Using the Python packages igraph and NetworkX, you’ll build your skills in various types of graph analytics.
Offered by
Difficulty Level
Intermediate
Completion Time
7h52m
Language
English
About Book
Who Is This Book For?
If you are a data analyst or database developer interested in learning graph databases and how to curate and extract data from them, this is the book for you. It is also beneficial for data scientists and Python developers looking to get started with graph data modeling. Although knowledge of Python is assumed, no prior experience in graph data modeling theory and techniques is required.
Graph Data Modeling in Python
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 7h52m total length
PI
Introducing Graphs in the Real World
Working with Graph Data Models
Data Model Transformation – Relational to Graph Databases
Building a Knowledge Graph
Working with Graph Databases
Pipeline Development
Refactoring and Evolving Schemas
Perfect Projections
Common Errors and Debugging
Related Resources
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