skills.rest
Aradotso
AradotsoOFFICIAL
Explore all skills by this author →
Website𝕏@aradotsoGitHub

harvard-artifacts-data-engineering-app

Extract Harvard Art Museums API data into SQL tables and Plotly dashboards.

5|1|Updated May 16, 2026
Search Tags:#SQL#ETL#Streamlit#data engineering#art analytics
One-click install
npx skills add https://github.com/Aradotso/data-skills --skill harvard-artifacts-data-engineering-app
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: harvard-artifacts-data-engineering-app
Source: https://github.com/Aradotso/data-skills/tree/main/skills/harvard-artifacts-data-engineering-app
Command: npx skills add https://github.com/Aradotso/data-skills --skill harvard-artifacts-data-engineering-app

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, requests, pymysql, plotly, python-dotenv, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides an end-to-end solution for building ETL pipelines and analytics dashboards using the Harvard Art Museums API, making it easier to work with art collection data.

Core Features & Use Cases

  • ETL Pipeline: Extracts and transforms artifact data into relational tables.
  • SQL Storage: Stores data in SQL databases (MySQL/TiDB).
  • Analytics Queries: Predefined SQL queries for artifact insights.
  • Interactive Visualization: Streamlit dashboards with Plotly charts.
  • Use Case: Ideal for data analysts and engineers looking to create analytics dashboards for art museum collections.

Quick Start

Use the 'harvard-artifacts-data-engineering-app' skill to extract and visualize data from the Harvard Art Museums API.

Frequently Asked Questions about harvard-artifacts-data-engineering-app

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build an ETL pipeline for the Harvard Art Museums API?▼

This Skill provides a complete ETL pipeline for the Harvard Art Museums API, extracting artifact data and storing it in SQL databases like MySQL. Predefined analytics queries are included to help you extract meaningful insights from the collection.

How do I visualize art collection data in a Streamlit dashboard?▼

You can visualize art collection data using the integrated Streamlit dashboard with Plotly charts. The Skill connects directly to your SQL database to display interactive analytics for the extracted Harvard Art Museums artifacts.

Do I need a MySQL database to store extracted art analytics data?▼

Yes, you need a SQL database like MySQL or TiDB to store the extracted art analytics data. The Skill uses the pymysql dependency to connect and load the transformed artifact records into relational tables.

Can I use pandas to transform API data into relational tables for SQL?▼

Yes, you can use pandas to transform API data into relational tables for SQL. This Skill uses pandas to structure the extracted Harvard Art Museums API responses before loading them into your SQL database.

What's the best way to extract and transform art collection data for analytics?▼

The best way to extract and transform art collection data for analytics is using an automated ETL pipeline. This Skill handles the extraction from the Harvard Art Museums API, transforms the data with pandas, and prepares it for interactive Plotly visualization.

Related Skills

Explore More Data & Analytics Skills→
AradotsoAradotso
5

harvard-artifacts-collection-analytics

Extract, transform, and analyze Harvard Art Museums API data with Python and SQL.

Official
Intermediate
AradotsoAradotso
5

harvard-artifacts-collection-analytics-app

Extract and transform Harvard Art Museums API data into a Streamlit dashboard.

Official
Advanced
AradotsoAradotso
5

harvard-artifacts-collection-data-engineering-analytics

Automate ETL, SQL analytics, and interactive dashboards for Harvard Art Museums API data.

Official
Advanced
AradotsoAradotso
5

harvard-art-museum-data-engineering

Automate ETL from the Harvard Art Museums API into SQL databases with Streamlit dashboards.

Official
Advanced