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harvard-art-museum-data-pipeline

Automate ETL pipelines for Harvard Art Museums API data with Python and Streamlit.

5|1|Updated May 16, 2026
Search Tags:#data visualization#data pipeline#ETL#Streamlit#MySQL#Python#Harvard Art Museums
One-click install
npx skills add https://github.com/Aradotso/data-skills --skill harvard-art-museum-data-pipeline
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: harvard-art-museum-data-pipeline
Source: https://github.com/Aradotso/data-skills/tree/main/skills/harvard-art-museum-data-pipeline
Command: npx skills add https://github.com/Aradotso/data-skills --skill harvard-art-museum-data-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the creation of data pipelines for the Harvard Art Museums, simplifying the process of extracting, transforming, and loading artifact data.

Core Features & Use Cases

  • ETL Automation: Automates the Extract, Transform, Load process for Harvard Art Museums API data.
  • Database Integration: Integrates with MySQL/TiDB Cloud for data storage and analysis.
  • Interactive Visualization: Provides interactive dashboards for data visualization using Streamlit and Plotly.
  • Use Case: Quickly set up a data pipeline to analyze and visualize artifact data from the Harvard Art Museums.

Quick Start

Use the harvard-art-museum-data-pipeline skill to create a data pipeline for the Harvard Art Museums and visualize the data using Streamlit.

Frequently Asked Questions about harvard-art-museum-data-pipeline

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

FAQPage Schema
How do I build a data pipeline for the Harvard Art Museums API?▼

You can build a data pipeline for the Harvard Art Museums API by using this Skill to automate the extraction, transformation, and loading of artifact data into a MySQL or TiDB database. It streamlines the ETL process using Python.

Can I visualize Harvard Art Museums data using Streamlit and Plotly?▼

Yes, you can visualize Harvard Art Museums data using Streamlit and Plotly. This Skill provides interactive dashboards that connect directly to your MySQL database to display and analyze the extracted artifact data.

Do I need a specific Python environment to run this ETL pipeline?▼

You need Python 3.8 or higher to run this ETL pipeline. The environment also requires a MySQL or TiDB Cloud database for storage and a valid Harvard Art Museums API key for data extraction.

What is the best way to automate extracting Harvard Art Museums artifact data?▼

The best way to automate extracting Harvard Art Museums artifact data is using an automated ETL pipeline. This Skill handles the extraction from the API, transformation via pandas, and loading into MySQL without manual intervention.

Does this data pipeline support TiDB Cloud for storage?▼

Yes, this data pipeline supports TiDB Cloud for storage. It uses the mysql-connector-python library to integrate with MySQL or TiDB Cloud, allowing you to store and manage the extracted Harvard Art Museums data effectively.

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