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datacommons-client

Query Data Commons statistical data via the Python API.

16|7|Updated Nov 20, 2025
Search Tags:#api#python#resolve#node#observation#datacommons
One-click install
npx skills add https://github.com/jackspace/ClaudeSkillz --skill datacommons-client
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: datacommons-client
Source: https://github.com/jackspace/ClaudeSkillz/tree/main/skills/scientific-pkg-datacommons-client
Command: npx skills add https://github.com/jackspace/ClaudeSkillz --skill datacommons-client

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Data Commons Python API v2 enables programmatic access to public statistical data, knowledge graph exploration, and entity resolution for a wide range of datasets and analytics workflows.

Core Features & Use Cases

  • Observe time-series statistics (population, GDP, health, environment)
  • Node/Resolve endpoints for graph exploration and DCID resolution
  • Integrate with Pandas for data analysis and reporting

Quick Start

Initialize a DataCommonsClient and fetch the latest population for geoId/06.

Frequently Asked Questions about datacommons-client

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

FAQPage Schema
How do I query statistical data from Data Commons using Python?▼

Query statistical data from Data Commons using the Python API by initializing a DataCommonsClient, then calling endpoints like Observation to fetch time-series data for demographics, economics, health, and environment across geographic or entity hierarchies.

Can I resolve Data Commons IDs (DCIDs) and explore the knowledge graph programmatically?▼

Yes, the Resolve and Node endpoints enable programmatic DCID resolution and knowledge graph exploration, letting you map entities to their identifiers and traverse relationships across Data Commons datasets.

How do I retrieve time-series statistics like population or GDP for specific regions?▼

Use the Observation endpoint to fetch time-series statistics by specifying entity identifiers (e.g., geoId/06) and variable types; results integrate directly with Pandas for analysis and reporting.

Does Data Commons Python API work with Pandas for data analysis and reporting?▼

Yes, the Data Commons Python API integrates with Pandas, allowing you to retrieve statistical observations and process them directly into DataFrames for analysis, visualization, and reporting workflows.

What datasets and domains does the Data Commons API cover?▼

The API provides access to demographic, economic, health, and environmental statistical datasets through a unified knowledge graph, supporting cross-entity comparisons and variable discovery across public data sources.

Do I need prior knowledge of Data Commons identifiers to use the API?▼

No; the Resolve endpoint handles DCID mapping and entity resolution, so you can work with common names or identifiers and let the API translate them to Data Commons IDs programmatically.

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