jm199504/Financial-Knowledge-Graphs resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

3125 stars · 568 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A tutorial-style Jupyter Notebook project demonstrating how to build a small financial knowledge graph using Python, Neo4j, and Cypher. It covers data acquisition from free financial APIs, preprocessing, graph construction, visualization queries, and Neo4j graph algorithms like centrality, community detection, and link prediction.

Use cases

• learn how to build a knowledge graph with neo4j and python
• construct a financial knowledge graph from stock data
• tutorial on cypher queries for graph databases
• run graph algorithms like link prediction and community detection on financial data
• fetch and preprocess stock market data from tushare
• visualize relationships between stocks and shareholders in a graph database

When to choose

• you want a hands-on, end-to-end walkthrough of building a knowledge graph in the financial domain
• you are learning Neo4j, Cypher, and graph algorithms with real stock market data
• you prefer notebook-based tutorials with explanations in Chinese

When to avoid

• you need a production-ready financial knowledge graph system or maintained library
• you require a permissively licensed project - this repository has no license
• you need English-language documentation or up-to-date API integrations

Facets

learning-resource · maturity active

database data-visualization search-engine machine-learning databases data-science tutorials big-data python cross-platform knowledge-graph neo4j cypher graph-database financial-data jupyter-notebook tutorial chinese-language finance docker

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markdown · JSON · MCP: product_card(name="jm199504/Financial-Knowledge-Graphs")