US County Economic and Demographic Indicators
2022 5-Year Estimates
Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- Not documented — confirm reuse terms with the seller
- Source / creator
- Supplier-cited: US Census Bureau ACS
- Collection method
- Supplier description: Reference-grade economic and demographic dataset covering all 3,222 US counties and county-equivalents, sourced from the US Census Bureau American Community Survey (ACS) 2022 5-Year Estimates. Each row represents one county with 20 fields including population, median household income, per capita income, poverty rate, unemployment rate, college degree attainment, median home value, median rent, homeownership rate, housing vacancy rate, income-to-home-value ratio, rent burden as percentage of income, long commute rates, and total housing units. Includes computed affordability and economic stress indicators derived from raw Census variables. Covers all 50 states plus DC and Puerto Rico with FIPS codes and Census region classifications. Ideal for market research, site selection analysis, economic policy research, real estate investment analysis, and demographic modeling. Data is public domain from the US Census Bureau.
- Coverage / snapshot
- 2022 5-Year Estimates
- Data last updated
- Not documented
- Update schedule
- Not documented
Source attribution is supplier-reported. The source link identifies publisher documentation; it does not independently verify this uploaded extract.
Sample structure score: 99.8 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 10 sample records (CSV) on 2026-10-09. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 49.8 / 50 | 199 of 200 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 30 / 30 | 199 of 199 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| fips_code | 0 / 10 | number | 0 / 10 |
| county_name | 0 / 10 | string | 0 / 10 |
| state | 0 / 10 | string | 0 / 10 |
| region | 0 / 10 | string | 0 / 10 |
| total_population | 0 / 10 | number | 0 / 10 |
| median_age | 0 / 10 | number | 0 / 10 |
| median_household_income_usd | 0 / 10 | number | 0 / 10 |
| per_capita_income_usd | 0 / 10 | number | 0 / 10 |
| poverty_rate_pct | 0 / 10 | number | 0 / 10 |
| unemployment_rate_pct | 0 / 10 | number | 0 / 10 |
| college_degree_pct | 0 / 10 | number | 0 / 10 |
| median_home_value_usd | 0 / 10 | number | 0 / 10 |
| median_gross_rent_usd | 0 / 10 | number | 0 / 10 |
| homeownership_rate_pct | 0 / 10 | number | 0 / 10 |
| vacancy_rate_pct | 0 / 10 | number | 0 / 10 |
| income_to_home_value_ratio | 0 / 10 | number | 0 / 10 |
| rent_burden_pct_of_income | 0 / 10 | number | 0 / 10 |
| long_commute_60plus_min_pct | 1 / 10 | number | 0 / 9 |
| total_housing_units | 0 / 10 | number | 0 / 10 |
| data_source | 0 / 10 | string | 0 / 10 |
About this data
County-level population, income, poverty, employment, education, housing and computed affordability indicators. Covers US counties and county-equivalents in the ACS 2022 five-year estimates, with FIPS codes and Census regions.
Retrieve with your agent or Python
Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.
Download the Python examplepython3 retrieve-dataset.py 03155b11-59e6-4def-9871-6fa2ac61e0ed --output dataset.bin
Full supplier documentation
Schema
| Name | Type | Description |
|---|---|---|
| fips_code | string | |
| county_name | string | |
| state | string | |
| region | string | |
| total_population | string | |
| median_age | string | |
| median_household_income_usd | string | |
| per_capita_income_usd | string | |
| poverty_rate_pct | string | |
| unemployment_rate_pct | string | |
| college_degree_pct | string | |
| median_home_value_usd | string | |
| median_gross_rent_usd | string | |
| homeownership_rate_pct | string | |
| vacancy_rate_pct | string | |
| income_to_home_value_ratio | string | |
| rent_burden_pct_of_income | string | |
| long_commute_60plus_min_pct | string | |
| total_housing_units | string | |
| data_source | string |
Sample Data
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For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "US County Economic and Demogra" })
// Found: 03155b11-59e6-4def-9871-6fa2ac61e0ed
get_download_url({ dataset_id: "03155b11-59e6-4def-9871-6fa2ac61e0ed" }) // free — sign in with MCP OAuth first# Free dataset — sign in or use your account API key: curl https://api.databazaar.io/datasets/03155b11-59e6-4def-9871-6fa2ac61e0ed/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"