datacommons-client
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
Author
Category
Business AnalysisInstall
Hot:18
Download and extract to your skills directory
Copy command and send to OpenClaw for auto-install:
Download and install this skill https://openskills.cc/api/download?slug=k-dense-ai-scientific-skills-datacommons-client&locale=en&source=copy
Data Commons Client - Public Statistical Data Python API Client
Overview of Capabilities
Access Data Commons' global public statistical data through a unified Python interface, including authoritative sources for population, economy, health, environment, and more.
Use Cases
Core Features
Frequently Asked Questions
Is the Data Commons API free?
Yes, the Data Commons API is open and free for public data queries, but you need to register to obtain an API key. You can apply at apikeys.datacommons.org. For custom Data Commons instances, an API key is not required.
How do I get started with statistical data?
A typical workflow is: first use the Resolve endpoint to convert place names into DCID identifiers, then query statistical variable data through the Observation endpoint. If you're not sure which statistical variables are available, you can use the
fetch_available_statistical_variables() method to view the list of available variables.What types of statistical data are supported?
Data Commons aggregates data from authoritative sources such as census bureaus, the World Bank, health organizations, and environmental agencies. It supports a wide range of statistical variables including demographics (Count_Person, Median_Age_Person), economic indicators (GDP, unemployment rate, median income), health data (mortality rates, disease incidence), and environmental metrics.