How does entity resolution work?

It provides a Resolve endpoint that translates common place names, Wikidata IDs, or latitude/longitude coordinates into unique Data Commons IDs (DCIDs) to ensure query precision.

What data sources does this skill access?

It accesses the Data Commons knowledge graph, which aggregates data from census bureaus (like the US Census), health organizations (WHO), environmental agencies (EPA), and other authoritative global sources.

Can this skill export data to Pandas?

Absolutely. The skill is specifically designed to integrate with Pandas, allowing you to convert statistical responses into DataFrames using methods like to_observations_as_records() for immediate analysis.

Do I need an API key to use the Data Commons Client?

Yes, for the default datacommons.org instance, you need a free API key which can be obtained from the Data Commons website and set as the DC_API_KEY environment variable.

What types of statistical variables can I query?

You can query thousands of variables including total population, median household income, unemployment rates, mean temperature, and specific disease prevalence metrics.

Data Commons Client

Name: Data Commons Client
Author: Activer007

byActiver007

0•

数据科学与机器学习

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

The Data Commons Client skill enables Claude to programmatically query massive datasets covering demographics, economics, health, and environmental statistics from authoritative global sources. By integrating the Data Commons Python API v2, it allows users to resolve entity identifiers, navigate geographic hierarchies, and fetch time-series observations directly into analysis-ready formats like Pandas DataFrames. This skill is essential for researchers, data scientists, and developers who need verified, structured public data for trend analysis, comparative studies, or building data-driven applications without manual data cleaning.

主要功能

01Explore the knowledge graph to discover relationships between statistical entities

02Retrieve time-series data for economic, demographic, and health indicators

03Resolve place names and coordinates to standardized Data Commons IDs (DCIDs)

04Navigate complex geographic hierarchies to query contained entities automatically

050 GitHub stars

06Convert statistical observations directly into Pandas DataFrames for seamless analysis

使用场景

01Building automated reports that compare demographic trends between cities or counties

02Analyzing historical unemployment rates and GDP growth across different global regions

03Mapping disease prevalence or health statistics to specific geographic coordinates

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add activer007/ordinary-claude-skills datacommons-client

For use in Claude.ai and ChatGPT

主要功能

01Explore the knowledge graph to discover relationships between statistical entities

02Retrieve time-series data for economic, demographic, and health indicators

03Resolve place names and coordinates to standardized Data Commons IDs (DCIDs)

04Navigate complex geographic hierarchies to query contained entities automatically

050 GitHub stars

06Convert statistical observations directly into Pandas DataFrames for seamless analysis

使用场景

01Building automated reports that compare demographic trends between cities or counties

02Analyzing historical unemployment rates and GDP growth across different global regions

03Mapping disease prevalence or health statistics to specific geographic coordinates