Agent skill · data analytics · aradotso
harvard-artifacts-etl-streamlit
ETL pipeline and analytics app for Harvard Art Museums API with SQL storage and Streamlit visualization
Why this skill is useful
Adds a complete ETL pipeline with SQL schema and Streamlit dashboard for visualizing Harvard Art Museums data, which the AI cannot generate on its own.
What it needs
Requires mysql-connector-python, pandas, plotly, python-dotenv, requests, streamlit installed locally. Requires harvard-art-museums account access. About 5k tokens when loaded. Last updated 2026-08-05. 5 stars on the source repository.
What this skill does
Harvard Artifacts ETL & Analytics Skill Skill by ara.so — Data Skills collection. This skill enables AI agents to build and work with end-to-end data engineering pipelines using the Harvard Art Museums API. It demonstrates ETL workflows, SQL database design, analytics queries, and interactive Streamlit dashboards with Plotly visualizations. What This Project Does The Harvard Artifacts Collection Data Engineering & Analytics App provides: API Integration: Fetch artifact data from Harvard Art Museums API with pagination and rate limiting ETL Pipeline: Extract, transform, and load museum artifact data into relational SQL databases SQL Database: Store artifacts metadata, media details, and color information with proper relationships Analytics Queries: 20+ predefined SQL queries for insights on culture, century, media, colors, and departments Interactive Dashboard: Streamlit-based UI with Plotly visualizations for real-time analytics Installation Required Dependencies Configuration Environment Variables Create a .env file or set environment variables: API Key Setup Get your free API key from Harvard Art Museums API: Database Schema Tables Structure ETL Pipeline Implementation 1. Extract Data from API 2. Transform Data 3. Load to SQL Database Analytics Queries Sample SQL Analytics Streamlit Dashboard Main Application Structure Running the Application Common Patterns Complete ETL Workflow Troubleshooting API Rate Limiting Database Connection Issues Handling Missing Data This skill provides complete ETL pipeline implementation for museum artifact data with SQL analytics and interactive visualization capabilities.
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/harvard-artifacts-etl-streamlit