What data is accessible through the Data Commons Client?

The client provides access to a unified knowledge graph containing data from census bureaus, health organizations (like WHO), environmental agencies, and economic institutions (like the World Bank).

Is it possible to query data for all cities within a specific state?

Yes, the skill supports entity expressions that allow you to query hierarchies, such as fetching data for all entities contained within a specific parent geography.

Do I need an API key to use this Claude Code skill?

Yes, to use the default Data Commons instance, you must request a free API key from apikeys.datacommons.org and set it as an environment variable.

How does entity resolution work in this skill?

It uses the Resolve Endpoint to translate human-readable names (like 'California') or geographic coordinates into unique Data Commons IDs (DCIDs) required for accurate querying.

Can I use this skill to create data visualizations?

While the skill focuses on data retrieval, it includes built-in Pandas support, making it easy to convert fetched data into DataFrames for plotting and visualization.

Data Commons Statistical Client

Name: Data Commons Statistical Client
Author: x-cmd

byx-cmd

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数据科学与机器学习

Accesses and analyzes global public statistical data from authoritative sources via the Data Commons knowledge graph.

关于

This skill provides Claude with the ability to programmatically query trillions of data points from the Data Commons knowledge graph, covering demographics, economics, health, and environmental statistics. It streamlines the workflow of resolving geographic entities, navigating complex hierarchical datasets, and fetching time-series observations directly into analysis pipelines. By integrating with the Data Commons Python API, it enables AI-driven data exploration, allowing users to compare statistics across countries, states, or cities and convert results into Pandas DataFrames for immediate processing and visualization.

主要功能

Resolve place names and coordinates into persistent Data Commons IDs (DCIDs)
Access authoritative data from the Census Bureau, WHO, World Bank, and UN
8 GitHub stars
Navigate geographic hierarchies to compare states, counties, or cities
Direct integration with Pandas for seamless data analysis and reshaping
Query time-series statistical data for global entities and variables

使用场景

Generating economic reports and trend analyses using historical GDP and unemployment data
Cross-referencing environmental indicators with health outcomes across different populations
Automating demographic research for specific geographic regions or municipal hierarchies

关于

主要功能

Resolve place names and coordinates into persistent Data Commons IDs (DCIDs)
Access authoritative data from the Census Bureau, WHO, World Bank, and UN
8 GitHub stars
Navigate geographic hierarchies to compare states, counties, or cities
Direct integration with Pandas for seamless data analysis and reshaping
Query time-series statistical data for global entities and variables

使用场景

Generating economic reports and trend analyses using historical GDP and unemployment data
Cross-referencing environmental indicators with health outcomes across different populations
Automating demographic research for specific geographic regions or municipal hierarchies