Skills datacommons-client
📊
datacommons-client
Low Risk ⚙️
External commands🌐
Network access🔑
Env variables
Query public statistics from Data Commons
Also available from: davila7
Access global statistical data from Data Commons including demographics, economics, health, and environmental indicators. Query population figures, GDP, unemployment rates, and geographic relationships using Python client methods.
Supports: Claude Codex Code(CC)
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Test it
Using "datacommons-client". Get the population of France and Germany
Expected outcome:
- France: 67,848,156 people (2023)
- Germany: 84,358,845 people (2023)
- Data source: World Bank
Using "datacommons-client". Show US unemployment trend from 2018 to 2023
Expected outcome:
- 2018: 3.9%
- 2019: 3.7%
- 2020: 8.1%
- 2021: 5.4%
- 2022: 3.6%
- 2023: 3.6%
Security Audit
Low Riskv4 • 1/17/2026
This skill is a documentation wrapper for the Data Commons Python client library. All static findings are FALSE POSITIVES: the scanner misinterprets markdown code block delimiters as shell commands, API call examples as network threats, and legitimate documentation patterns as credential exposure. The skill enables read-only access to public statistical data with no code execution capabilities beyond package installation documentation.
6
Files scanned
2,822
Lines analyzed
3
findings
4
Total audits
Risk Factors
⚙️ External commands (200)
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🌐 Network access (46)
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Audited by: claude View Audit History →
Quality Score
45
Architecture
100
Maintainability
85
Content
20
Community
90
Security
100
Spec Compliance
What You Can Build
Compare regional statistics
Query and compare population, income, and unemployment data across multiple states or countries.
Access historical trends
Retrieve time-series data for economic indicators, health statistics, or environmental measurements.
Build data-driven applications
Integrate public statistical data into applications using Python client library methods.
Try These Prompts
Basic query
Get the latest population for California, Texas, and New York using the Data Commons client.
Time series
Query the unemployment rate time series for the United States from 2010 to 2023.
Geographic hierarchy
Get median household income for all counties in California for year 2020.
Multi-variable
Compare population, median income, and median age across Florida, Georgia, and South Carolina.
Best Practices
- Always resolve place names to DCIDs before querying to handle ambiguous names
- Use entity expressions to query hierarchies efficiently (all counties in a state at once)
- Cache DCID resolutions when querying the same entities repeatedly
Avoid
- Hardcoding DCIDs instead of resolving names dynamically
- Making individual queries for each entity instead of batch queries
- Ignoring data source facets when consistency matters
Frequently Asked Questions
What is Data Commons?
Data Commons is a platform aggregating public statistical data from sources like census bureaus and health organizations into a unified knowledge graph.
Do I need an API key?
Yes, for datacommons.org. Request one at apikeys.datacommons.org and set it via DC_API_KEY environment variable.
What data types are available?
Population, income, unemployment, health statistics, environmental data, and geographic relationships for places worldwide.
How do I find statistical variables?
Use fetch_available_statistical_variables() to check what data exists for an entity, or browse at datacommons.org/tools/statvar.
Can I query historical data?
Yes, set date parameter to 'all' to retrieve complete time series for trend analysis.
What are DCIDs?
Data Commons Identifiers are unique keys for entities. Use the Resolve API to convert place names to DCIDs.