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datacommons-client

Query time-series statistical data and resolve entities via Data Commons Python API v2.

8|Updated Jan 13, 2026
Search Tags:#api#data access#statistics#economic data#demographics#data commons#public data
One-click install
npx skills add https://github.com/hxk622/TokenDance --skill datacommons-client-hxk622
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: datacommons-client
Source: https://github.com/hxk622/TokenDance/tree/main/backend/app/skills/builtin/scientific/database/datacommons-client
Command: npx skills add https://github.com/hxk622/TokenDance --skill datacommons-client-hxk622

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires datacommons-client, and includes references (resource) components.

What problem does it solve?

This Skill provides programmatic access to a vast repository of public statistical data from global sources, simplifying the retrieval and analysis of demographic, economic, health, and environmental information.

Core Features & Use Cases

  • Statistical Data Queries: Retrieve time-series data for entities (e.g., population, GDP, unemployment rates).
  • Knowledge Graph Exploration: Discover entity relationships, properties, and hierarchies.
  • Entity Resolution: Translate entity names, coordinates, or external IDs into Data Commons IDs (DCIDs).
  • Use Case: Analyze the correlation between median household income and unemployment rates across different US states over the past decade.

Quick Start

Use the datacommons-client skill to fetch the latest population data for California and Texas.

Frequently Asked Questions about datacommons-client

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

FAQPage Schema
How do I access public statistical data for demographic and economic analysis?▼

You can access public statistical data by querying Data Commons, a platform aggregating global sources. This skill facilitates retrieving time-series observations for demographics and economics using the Python API v2.

How do I resolve entity names or coordinates into Data Commons IDs?▼

To resolve entity identifiers, the skill translates entity names, coordinates, or external IDs into Data Commons IDs (DCIDs). This allows you to accurately target specific geographic or demographic entities for your queries.

Can I explore the knowledge graph to discover entity relationships and hierarchies?▼

Yes, you can explore the Data Commons knowledge graph to discover entity relationships, properties, and hierarchies. This helps map connections between different demographic, health, and environmental datasets.

Does the datacommons-client support querying time-series observations like GDP and unemployment rates?▼

The datacommons-client supports querying time-series observations for entities, allowing you to retrieve variables like GDP, population, and unemployment rates. It uses Python API v2 for these statistical data queries.

What are the limitations of using Data Commons for global public data retrieval?▼

Data Commons limits retrieval to aggregated public statistical data from global sources. It requires resolving entities to DCIDs and relies on Python API v2, meaning data availability depends on underlying source coverage.

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