Summary
This is a complete ETL reference implementation for working with the Harvard Art Museums API. It shows you how to handle paginated API requests with rate limiting, transform nested JSON into normalized SQL tables (metadata, media, colors), and build a Streamlit dashboard with 20+ analytical queries and Plotly visualizations. The code is practical and well-structured, covering the full pipeline from extraction to visualization. Use this when you need to see how a museum or cultural heritage data pipeline actually fits together, or as a template for similar API-to-database projects. The main value is seeing all the pieces (API pagination, DataFrame transformations, MySQL schema design, dashboard queries) in one working example rather than scattered across documentation.
Install to Claude Code
npx -y skills add aradotso/data-skills --skill harvard-artifacts-collection-etl-analytics --agent claude-codeInstalls into .claude/skills of the current project.
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Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
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