Welcome to gastrodon’s documentation!

Release 0.9.3

About Gastrodon

Gastrodon links databases that support the SPARQL protocol (more than ten!) to Pandas, a popular Python library for analysis of tabular data. Pandas, in turn, is connected to a vast number of visualization, statistics, and machine learning tools, all of which work with Jupyter notebooks. The result is an ideal environment for telling stories that reveal the value of data, ontologies, taxonomies, and models.

In addition to remote databases, Gastrodon can do SPARQL queries over in-memory RDF graphs (from rdflib). It has facilities to copy subgraphs from one graph to another, making it possible to assemble local graphs that contain facts relevant to a particular decision, work on them intimately, and then store results in a permanent triple store.

Learning to use Gastrodon

This manual contains detailed API documentation for Gastrodon. For examples of Jupyter notebooks that use Gastrodon, see the Example notebooks.

The following reference documentation should be helpful:

• Pandas
• Jupyter
• rdflib
• SPARQL

Table of Contents

Table of Contents:

• API Reference
  • Endpoints
  • Endpoint Implementations
  • Supporting Classes and Functions
  • Objects Created Only By Gastrodon

Indices and tables

• Index
• Module Index
• Search Page