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datacommons-client

Query Data Commons API v2 for statistical observations and entity identifiers.

Updated Dec 17, 2025
Search Tags:#knowledge graph#statistical analysis#entity resolution#data commons#public data
One-click install
npx skills add https://github.com/robotlearning123/claude-scientific-skills --skill datacommons-client-robotlearning123
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: datacommons-client
Source: https://github.com/robotlearning123/claude-scientific-skills/tree/main/scientific-skills/datacommons-client
Command: npx skills add https://github.com/robotlearning123/claude-scientific-skills --skill datacommons-client-robotlearning123

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill simplifies accessing and querying extensive public statistical datasets from Data Commons, making complex data analysis more accessible.

Core Features & Use Cases

  • Statistical Data Queries: Retrieve and analyze time-series statistical data for any entity.
  • Knowledge Graph Exploration: Navigate and explore the relationships between entities within the Data Commons knowledge graph.
  • Entity Identification: Translate entity names, coordinates, or external IDs into Data Commons IDs (DCIDs).
  • Use Case: Quickly obtain the latest population statistics for a specific country or compare economic indicators across multiple regions.

Quick Start

Initialize the datacommons-client skill and retrieve the latest unemployment rate for the United States.

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 observations from public datasets using Data Commons API v2?▼

Explore the Data Commons knowledge graph by navigating relationships between entities. This allows you to traverse structured public data connections to discover related statistical variables and geographic entities.

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

Resolve entity names, coordinates, or external IDs into Data Commons IDs (DCIDs) using the entity resolution feature. This translates standard geographic references into the required identifiers for querying statistical data.

Do I need Pandas and datacommons-client to analyze public statistical data?▼

Yes, you need Pandas and datacommons-client installed to analyze public statistical data. These Python client libraries provide the necessary framework to query the API and structure the returned time-series observations for analysis.

Can I compare economic indicators across multiple regions with Data Commons?▼

You can compare economic indicators across multiple regions with Data Commons by retrieving time-series statistical observations for various resolved entities. This allows direct comparison of variables like unemployment rates across different geographic areas.

What are the limitations of using Data Commons for statistical analysis?▼

Limitations of using Data Commons for statistical analysis include dependency on the availability of public datasets within the knowledge graph and the requirement of Python libraries like Pandas for advanced data manipulation.

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