Dictionary

This page is generated at build time — the measures table and the provenance table are queried at build time from the latest release, and every table’s column docs come straight from the declared schemas (cancerbasemap.schemas) in this repository, not hand-copied. If a release adds a measure or a schema gains a column, this page’s next render shows it.

Measures

Every measure the latest release defines, by source. Type in the search box to filter.

230 measures across 14 sources.

measures = transpose(measures_data)

viewof measureSearch = Inputs.search(measures, { placeholder: "Search measures (id, label, source)…" })

Inputs.table(measureSearch, {
  columns: ["source", "measure_id", "label", "units", "rate_basis", "method"],
  rows: 20
})

Tables

Every table this repository declares (cancerbasemap.schemas.TABLES), grouped by namespace, with its comment, its business key, and every column’s own doc string. A table not yet populated in the release still appears here — this section is the declared schema, not a scan of what happens to exist right now. A release holds current rows only, so the validity columns the writers keep (valid_from, valid_to) are not shown: they are not in the release.

`raw` — Sources as landed, verbatim, per source release.

`raw.acs__county`

US Census ACS 5-year Summary File detailed tables (B01003, B09001, B09020, B03002, B15003, B19013, C17002, B23025, B25044, B25002, B25070, C16002, B19083, B27001, C27007), landed verbatim per (level, acs_year): every estimate and margin-of-error variable of each requested table, as the jam-value strings ACS publishes (see census_acs.py for the sentinel meanings and the CIF-indicator decision). Public domain (U.S. Government work, 17 U.S.C. Sec 105).

Sorted by: acs_year, geo_id

Column	Type	Required	Doc
`geo_id`	string	yes	Canonical geo_id: ‘county:<5-digit FIPS>’ or ‘tract:<11-digit FIPS>’, matching the raw table’s own level.
`acs_year`	int	yes	The 5-year release’s end year (e.g. 2023 for the 2019-2023 release) – the version column raw is scoped and overwritten by.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.
`B01003_E001`	string		ACS estimate (count): Total (Total Population).
`B01003_M001`	string		Margin of error (90% confidence) for the paired B01003_E001 estimate.
`B09001_E001`	string		ACS estimate (count): Total (Population Under 18 Years by Age).
`B09001_M001`	string		Margin of error (90% confidence) for the paired B09001_E001 estimate.
`B09001_E002`	string		ACS estimate (count): Total > In households (Population Under 18 Years by Age).
`B09001_M002`	string		Margin of error (90% confidence) for the paired B09001_E002 estimate.
`B09001_E003`	string		ACS estimate (count): Total > In households > Under 3 years (Population Under 18 Years by Age).
`B09001_M003`	string		Margin of error (90% confidence) for the paired B09001_E003 estimate.
`B09001_E004`	string		ACS estimate (count): Total > In households > 3 and 4 years (Population Under 18 Years by Age).
`B09001_M004`	string		Margin of error (90% confidence) for the paired B09001_E004 estimate.
`B09001_E005`	string		ACS estimate (count): Total > In households > 5 years (Population Under 18 Years by Age).
`B09001_M005`	string		Margin of error (90% confidence) for the paired B09001_E005 estimate.
`B09001_E006`	string		ACS estimate (count): Total > In households > 6 to 8 years (Population Under 18 Years by Age).
`B09001_M006`	string		Margin of error (90% confidence) for the paired B09001_E006 estimate.
`B09001_E007`	string		ACS estimate (count): Total > In households > 9 to 11 years (Population Under 18 Years by Age).
`B09001_M007`	string		Margin of error (90% confidence) for the paired B09001_E007 estimate.
`B09001_E008`	string		ACS estimate (count): Total > In households > 12 to 14 years (Population Under 18 Years by Age).
`B09001_M008`	string		Margin of error (90% confidence) for the paired B09001_E008 estimate.
`B09001_E009`	string		ACS estimate (count): Total > In households > 15 to 17 years (Population Under 18 Years by Age).
`B09001_M009`	string		Margin of error (90% confidence) for the paired B09001_E009 estimate.
`B09001_E010`	string		ACS estimate (count): Total > In group quarters (Population Under 18 Years by Age).
`B09001_M010`	string		Margin of error (90% confidence) for the paired B09001_E010 estimate.
`B09020_E001`	string		ACS estimate (count): Total (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M001`	string		Margin of error (90% confidence) for the paired B09020_E001 estimate.
`B09020_E002`	string		ACS estimate (count): Total > In households (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M002`	string		Margin of error (90% confidence) for the paired B09020_E002 estimate.
`B09020_E003`	string		ACS estimate (count): Total > In households > In family households (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M003`	string		Margin of error (90% confidence) for the paired B09020_E003 estimate.
`B09020_E004`	string		ACS estimate (count): Total > In households > In family households > Householder (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M004`	string		Margin of error (90% confidence) for the paired B09020_E004 estimate.
`B09020_E005`	string		ACS estimate (count): Total > In households > In family households > Householder > Male (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M005`	string		Margin of error (90% confidence) for the paired B09020_E005 estimate.
`B09020_E006`	string		ACS estimate (count): Total > In households > In family households > Householder > Female (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M006`	string		Margin of error (90% confidence) for the paired B09020_E006 estimate.
`B09020_E007`	string		ACS estimate (count): Total > In households > In family households > Spouse (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M007`	string		Margin of error (90% confidence) for the paired B09020_E007 estimate.
`B09020_E008`	string		ACS estimate (count): Total > In households > In family households > Parent (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M008`	string		Margin of error (90% confidence) for the paired B09020_E008 estimate.
`B09020_E009`	string		ACS estimate (count): Total > In households > In family households > Parent-in-law (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M009`	string		Margin of error (90% confidence) for the paired B09020_E009 estimate.
`B09020_E010`	string		ACS estimate (count): Total > In households > In family households > Other relatives (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M010`	string		Margin of error (90% confidence) for the paired B09020_E010 estimate.
`B09020_E011`	string		ACS estimate (count): Total > In households > In family households > Nonrelatives (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M011`	string		Margin of error (90% confidence) for the paired B09020_E011 estimate.
`B09020_E012`	string		ACS estimate (count): Total > In households > In nonfamily households (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M012`	string		Margin of error (90% confidence) for the paired B09020_E012 estimate.
`B09020_E013`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M013`	string		Margin of error (90% confidence) for the paired B09020_E013 estimate.
`B09020_E014`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Male (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M014`	string		Margin of error (90% confidence) for the paired B09020_E014 estimate.
`B09020_E015`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Male > Living alone (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M015`	string		Margin of error (90% confidence) for the paired B09020_E015 estimate.
`B09020_E016`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Male > Not living alone (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M016`	string		Margin of error (90% confidence) for the paired B09020_E016 estimate.
`B09020_E017`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Female (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M017`	string		Margin of error (90% confidence) for the paired B09020_E017 estimate.
`B09020_E018`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Female > Living alone (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M018`	string		Margin of error (90% confidence) for the paired B09020_E018 estimate.
`B09020_E019`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Female > Not living alone (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M019`	string		Margin of error (90% confidence) for the paired B09020_E019 estimate.
`B09020_E020`	string		ACS estimate (count): Total > In households > In nonfamily households > Nonrelatives (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M020`	string		Margin of error (90% confidence) for the paired B09020_E020 estimate.
`B09020_E021`	string		ACS estimate (count): Total > In group quarters (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M021`	string		Margin of error (90% confidence) for the paired B09020_E021 estimate.
`B03002_E001`	string		ACS estimate (count): Total (Hispanic or Latino Origin by Race).
`B03002_M001`	string		Margin of error (90% confidence) for the paired B03002_E001 estimate.
`B03002_E002`	string		ACS estimate (count): Total > Not Hispanic or Latino (Hispanic or Latino Origin by Race).
`B03002_M002`	string		Margin of error (90% confidence) for the paired B03002_E002 estimate.
`B03002_E003`	string		ACS estimate (count): Total > Not Hispanic or Latino > White alone (Hispanic or Latino Origin by Race).
`B03002_M003`	string		Margin of error (90% confidence) for the paired B03002_E003 estimate.
`B03002_E004`	string		ACS estimate (count): Total > Not Hispanic or Latino > Black or African American alone (Hispanic or Latino Origin by Race).
`B03002_M004`	string		Margin of error (90% confidence) for the paired B03002_E004 estimate.
`B03002_E005`	string		ACS estimate (count): Total > Not Hispanic or Latino > American Indian and Alaska Native alone (Hispanic or Latino Origin by Race).
`B03002_M005`	string		Margin of error (90% confidence) for the paired B03002_E005 estimate.
`B03002_E006`	string		ACS estimate (count): Total > Not Hispanic or Latino > Asian alone (Hispanic or Latino Origin by Race).
`B03002_M006`	string		Margin of error (90% confidence) for the paired B03002_E006 estimate.
`B03002_E007`	string		ACS estimate (count): Total > Not Hispanic or Latino > Native Hawaiian and Other Pacific Islander alone (Hispanic or Latino Origin by Race).
`B03002_M007`	string		Margin of error (90% confidence) for the paired B03002_E007 estimate.
`B03002_E008`	string		ACS estimate (count): Total > Not Hispanic or Latino > Some other race alone (Hispanic or Latino Origin by Race).
`B03002_M008`	string		Margin of error (90% confidence) for the paired B03002_E008 estimate.
`B03002_E009`	string		ACS estimate (count): Total > Not Hispanic or Latino > Two or more races (Hispanic or Latino Origin by Race).
`B03002_M009`	string		Margin of error (90% confidence) for the paired B03002_E009 estimate.
`B03002_E010`	string		ACS estimate (count): Total > Not Hispanic or Latino > Two or more races > Two races including Some other race (Hispanic or Latino Origin by Race).
`B03002_M010`	string		Margin of error (90% confidence) for the paired B03002_E010 estimate.
`B03002_E011`	string		ACS estimate (count): Total > Not Hispanic or Latino > Two or more races > Two races excluding Some other race, and three or more races (Hispanic or Latino Origin by Race).
`B03002_M011`	string		Margin of error (90% confidence) for the paired B03002_E011 estimate.
`B03002_E012`	string		ACS estimate (count): Total > Hispanic or Latino (Hispanic or Latino Origin by Race).
`B03002_M012`	string		Margin of error (90% confidence) for the paired B03002_E012 estimate.
`B03002_E013`	string		ACS estimate (count): Total > Hispanic or Latino > White alone (Hispanic or Latino Origin by Race).
`B03002_M013`	string		Margin of error (90% confidence) for the paired B03002_E013 estimate.
`B03002_E014`	string		ACS estimate (count): Total > Hispanic or Latino > Black or African American alone (Hispanic or Latino Origin by Race).
`B03002_M014`	string		Margin of error (90% confidence) for the paired B03002_E014 estimate.
`B03002_E015`	string		ACS estimate (count): Total > Hispanic or Latino > American Indian and Alaska Native alone (Hispanic or Latino Origin by Race).
`B03002_M015`	string		Margin of error (90% confidence) for the paired B03002_E015 estimate.
`B03002_E016`	string		ACS estimate (count): Total > Hispanic or Latino > Asian alone (Hispanic or Latino Origin by Race).
`B03002_M016`	string		Margin of error (90% confidence) for the paired B03002_E016 estimate.
`B03002_E017`	string		ACS estimate (count): Total > Hispanic or Latino > Native Hawaiian and Other Pacific Islander alone (Hispanic or Latino Origin by Race).
`B03002_M017`	string		Margin of error (90% confidence) for the paired B03002_E017 estimate.
`B03002_E018`	string		ACS estimate (count): Total > Hispanic or Latino > Some other race alone (Hispanic or Latino Origin by Race).
`B03002_M018`	string		Margin of error (90% confidence) for the paired B03002_E018 estimate.
`B03002_E019`	string		ACS estimate (count): Total > Hispanic or Latino > Two or more races (Hispanic or Latino Origin by Race).
`B03002_M019`	string		Margin of error (90% confidence) for the paired B03002_E019 estimate.
`B03002_E020`	string		ACS estimate (count): Total > Hispanic or Latino > Two or more races > Two races including Some other race (Hispanic or Latino Origin by Race).
`B03002_M020`	string		Margin of error (90% confidence) for the paired B03002_E020 estimate.
`B03002_E021`	string		ACS estimate (count): Total > Hispanic or Latino > Two or more races > Two races excluding Some other race, and three or more races (Hispanic or Latino Origin by Race).
`B03002_M021`	string		Margin of error (90% confidence) for the paired B03002_E021 estimate.
`B15003_E001`	string		ACS estimate (count): Total (Educational Attainment for the Population 25 Years and Over).
`B15003_M001`	string		Margin of error (90% confidence) for the paired B15003_E001 estimate.
`B15003_E002`	string		ACS estimate (count): Total > No schooling completed (Educational Attainment for the Population 25 Years and Over).
`B15003_M002`	string		Margin of error (90% confidence) for the paired B15003_E002 estimate.
`B15003_E003`	string		ACS estimate (count): Total > Nursery school (Educational Attainment for the Population 25 Years and Over).
`B15003_M003`	string		Margin of error (90% confidence) for the paired B15003_E003 estimate.
`B15003_E004`	string		ACS estimate (count): Total > Kindergarten (Educational Attainment for the Population 25 Years and Over).
`B15003_M004`	string		Margin of error (90% confidence) for the paired B15003_E004 estimate.
`B15003_E005`	string		ACS estimate (count): Total > 1st grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M005`	string		Margin of error (90% confidence) for the paired B15003_E005 estimate.
`B15003_E006`	string		ACS estimate (count): Total > 2nd grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M006`	string		Margin of error (90% confidence) for the paired B15003_E006 estimate.
`B15003_E007`	string		ACS estimate (count): Total > 3rd grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M007`	string		Margin of error (90% confidence) for the paired B15003_E007 estimate.
`B15003_E008`	string		ACS estimate (count): Total > 4th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M008`	string		Margin of error (90% confidence) for the paired B15003_E008 estimate.
`B15003_E009`	string		ACS estimate (count): Total > 5th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M009`	string		Margin of error (90% confidence) for the paired B15003_E009 estimate.
`B15003_E010`	string		ACS estimate (count): Total > 6th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M010`	string		Margin of error (90% confidence) for the paired B15003_E010 estimate.
`B15003_E011`	string		ACS estimate (count): Total > 7th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M011`	string		Margin of error (90% confidence) for the paired B15003_E011 estimate.
`B15003_E012`	string		ACS estimate (count): Total > 8th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M012`	string		Margin of error (90% confidence) for the paired B15003_E012 estimate.
`B15003_E013`	string		ACS estimate (count): Total > 9th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M013`	string		Margin of error (90% confidence) for the paired B15003_E013 estimate.
`B15003_E014`	string		ACS estimate (count): Total > 10th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M014`	string		Margin of error (90% confidence) for the paired B15003_E014 estimate.
`B15003_E015`	string		ACS estimate (count): Total > 11th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M015`	string		Margin of error (90% confidence) for the paired B15003_E015 estimate.
`B15003_E016`	string		ACS estimate (count): Total > 12th grade, no diploma (Educational Attainment for the Population 25 Years and Over).
`B15003_M016`	string		Margin of error (90% confidence) for the paired B15003_E016 estimate.
`B15003_E017`	string		ACS estimate (count): Total > Regular high school diploma (Educational Attainment for the Population 25 Years and Over).
`B15003_M017`	string		Margin of error (90% confidence) for the paired B15003_E017 estimate.
`B15003_E018`	string		ACS estimate (count): Total > GED or alternative credential (Educational Attainment for the Population 25 Years and Over).
`B15003_M018`	string		Margin of error (90% confidence) for the paired B15003_E018 estimate.
`B15003_E019`	string		ACS estimate (count): Total > Some college, less than 1 year (Educational Attainment for the Population 25 Years and Over).
`B15003_M019`	string		Margin of error (90% confidence) for the paired B15003_E019 estimate.
`B15003_E020`	string		ACS estimate (count): Total > Some college, 1 or more years, no degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M020`	string		Margin of error (90% confidence) for the paired B15003_E020 estimate.
`B15003_E021`	string		ACS estimate (count): Total > Associate’s degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M021`	string		Margin of error (90% confidence) for the paired B15003_E021 estimate.
`B15003_E022`	string		ACS estimate (count): Total > Bachelor’s degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M022`	string		Margin of error (90% confidence) for the paired B15003_E022 estimate.
`B15003_E023`	string		ACS estimate (count): Total > Master’s degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M023`	string		Margin of error (90% confidence) for the paired B15003_E023 estimate.
`B15003_E024`	string		ACS estimate (count): Total > Professional school degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M024`	string		Margin of error (90% confidence) for the paired B15003_E024 estimate.
`B15003_E025`	string		ACS estimate (count): Total > Doctorate degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M025`	string		Margin of error (90% confidence) for the paired B15003_E025 estimate.
`B19013_E001`	string		ACS estimate (count): Median household income in the past 12 months (in 2023 inflation-adjusted dollars) (Median Household Income in the Past 12 Months (in 2023 Inflation-Adjusted Dollars)).
`B19013_M001`	string		Margin of error (90% confidence) for the paired B19013_E001 estimate.
`C17002_E001`	string		ACS estimate (count): Total (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M001`	string		Margin of error (90% confidence) for the paired C17002_E001 estimate.
`C17002_E002`	string		ACS estimate (count): Total > Under .50 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M002`	string		Margin of error (90% confidence) for the paired C17002_E002 estimate.
`C17002_E003`	string		ACS estimate (count): Total > .50 to .99 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M003`	string		Margin of error (90% confidence) for the paired C17002_E003 estimate.
`C17002_E004`	string		ACS estimate (count): Total > 1.00 to 1.24 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M004`	string		Margin of error (90% confidence) for the paired C17002_E004 estimate.
`C17002_E005`	string		ACS estimate (count): Total > 1.25 to 1.49 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M005`	string		Margin of error (90% confidence) for the paired C17002_E005 estimate.
`C17002_E006`	string		ACS estimate (count): Total > 1.50 to 1.84 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M006`	string		Margin of error (90% confidence) for the paired C17002_E006 estimate.
`C17002_E007`	string		ACS estimate (count): Total > 1.85 to 1.99 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M007`	string		Margin of error (90% confidence) for the paired C17002_E007 estimate.
`C17002_E008`	string		ACS estimate (count): Total > 2.00 and over (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M008`	string		Margin of error (90% confidence) for the paired C17002_E008 estimate.
`B23025_E001`	string		ACS estimate (count): Total (Employment Status for the Population 16 Years and Over).
`B23025_M001`	string		Margin of error (90% confidence) for the paired B23025_E001 estimate.
`B23025_E002`	string		ACS estimate (count): Total > In labor force (Employment Status for the Population 16 Years and Over).
`B23025_M002`	string		Margin of error (90% confidence) for the paired B23025_E002 estimate.
`B23025_E003`	string		ACS estimate (count): Total > In labor force > Civilian labor force (Employment Status for the Population 16 Years and Over).
`B23025_M003`	string		Margin of error (90% confidence) for the paired B23025_E003 estimate.
`B23025_E004`	string		ACS estimate (count): Total > In labor force > Civilian labor force > Employed (Employment Status for the Population 16 Years and Over).
`B23025_M004`	string		Margin of error (90% confidence) for the paired B23025_E004 estimate.
`B23025_E005`	string		ACS estimate (count): Total > In labor force > Civilian labor force > Unemployed (Employment Status for the Population 16 Years and Over).
`B23025_M005`	string		Margin of error (90% confidence) for the paired B23025_E005 estimate.
`B23025_E006`	string		ACS estimate (count): Total > In labor force > Armed Forces (Employment Status for the Population 16 Years and Over).
`B23025_M006`	string		Margin of error (90% confidence) for the paired B23025_E006 estimate.
`B23025_E007`	string		ACS estimate (count): Total > Not in labor force (Employment Status for the Population 16 Years and Over).
`B23025_M007`	string		Margin of error (90% confidence) for the paired B23025_E007 estimate.
`B25044_E001`	string		ACS estimate (count): Total (Tenure by Vehicles Available).
`B25044_M001`	string		Margin of error (90% confidence) for the paired B25044_E001 estimate.
`B25044_E002`	string		ACS estimate (count): Total > Owner occupied (Tenure by Vehicles Available).
`B25044_M002`	string		Margin of error (90% confidence) for the paired B25044_E002 estimate.
`B25044_E003`	string		ACS estimate (count): Total > Owner occupied > No vehicle available (Tenure by Vehicles Available).
`B25044_M003`	string		Margin of error (90% confidence) for the paired B25044_E003 estimate.
`B25044_E004`	string		ACS estimate (count): Total > Owner occupied > 1 vehicle available (Tenure by Vehicles Available).
`B25044_M004`	string		Margin of error (90% confidence) for the paired B25044_E004 estimate.
`B25044_E005`	string		ACS estimate (count): Total > Owner occupied > 2 vehicles available (Tenure by Vehicles Available).
`B25044_M005`	string		Margin of error (90% confidence) for the paired B25044_E005 estimate.
`B25044_E006`	string		ACS estimate (count): Total > Owner occupied > 3 vehicles available (Tenure by Vehicles Available).
`B25044_M006`	string		Margin of error (90% confidence) for the paired B25044_E006 estimate.
`B25044_E007`	string		ACS estimate (count): Total > Owner occupied > 4 vehicles available (Tenure by Vehicles Available).
`B25044_M007`	string		Margin of error (90% confidence) for the paired B25044_E007 estimate.
`B25044_E008`	string		ACS estimate (count): Total > Owner occupied > 5 or more vehicles available (Tenure by Vehicles Available).
`B25044_M008`	string		Margin of error (90% confidence) for the paired B25044_E008 estimate.
`B25044_E009`	string		ACS estimate (count): Total > Renter occupied (Tenure by Vehicles Available).
`B25044_M009`	string		Margin of error (90% confidence) for the paired B25044_E009 estimate.
`B25044_E010`	string		ACS estimate (count): Total > Renter occupied > No vehicle available (Tenure by Vehicles Available).
`B25044_M010`	string		Margin of error (90% confidence) for the paired B25044_E010 estimate.
`B25044_E011`	string		ACS estimate (count): Total > Renter occupied > 1 vehicle available (Tenure by Vehicles Available).
`B25044_M011`	string		Margin of error (90% confidence) for the paired B25044_E011 estimate.
`B25044_E012`	string		ACS estimate (count): Total > Renter occupied > 2 vehicles available (Tenure by Vehicles Available).
`B25044_M012`	string		Margin of error (90% confidence) for the paired B25044_E012 estimate.
`B25044_E013`	string		ACS estimate (count): Total > Renter occupied > 3 vehicles available (Tenure by Vehicles Available).
`B25044_M013`	string		Margin of error (90% confidence) for the paired B25044_E013 estimate.
`B25044_E014`	string		ACS estimate (count): Total > Renter occupied > 4 vehicles available (Tenure by Vehicles Available).
`B25044_M014`	string		Margin of error (90% confidence) for the paired B25044_E014 estimate.
`B25044_E015`	string		ACS estimate (count): Total > Renter occupied > 5 or more vehicles available (Tenure by Vehicles Available).
`B25044_M015`	string		Margin of error (90% confidence) for the paired B25044_E015 estimate.
`B25002_E001`	string		ACS estimate (count): Total (Occupancy Status).
`B25002_M001`	string		Margin of error (90% confidence) for the paired B25002_E001 estimate.
`B25002_E002`	string		ACS estimate (count): Total > Occupied (Occupancy Status).
`B25002_M002`	string		Margin of error (90% confidence) for the paired B25002_E002 estimate.
`B25002_E003`	string		ACS estimate (count): Total > Vacant (Occupancy Status).
`B25002_M003`	string		Margin of error (90% confidence) for the paired B25002_E003 estimate.
`B25070_E001`	string		ACS estimate (count): Total (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M001`	string		Margin of error (90% confidence) for the paired B25070_E001 estimate.
`B25070_E002`	string		ACS estimate (count): Total > Less than 10.0 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M002`	string		Margin of error (90% confidence) for the paired B25070_E002 estimate.
`B25070_E003`	string		ACS estimate (count): Total > 10.0 to 14.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M003`	string		Margin of error (90% confidence) for the paired B25070_E003 estimate.
`B25070_E004`	string		ACS estimate (count): Total > 15.0 to 19.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M004`	string		Margin of error (90% confidence) for the paired B25070_E004 estimate.
`B25070_E005`	string		ACS estimate (count): Total > 20.0 to 24.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M005`	string		Margin of error (90% confidence) for the paired B25070_E005 estimate.
`B25070_E006`	string		ACS estimate (count): Total > 25.0 to 29.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M006`	string		Margin of error (90% confidence) for the paired B25070_E006 estimate.
`B25070_E007`	string		ACS estimate (count): Total > 30.0 to 34.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M007`	string		Margin of error (90% confidence) for the paired B25070_E007 estimate.
`B25070_E008`	string		ACS estimate (count): Total > 35.0 to 39.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M008`	string		Margin of error (90% confidence) for the paired B25070_E008 estimate.
`B25070_E009`	string		ACS estimate (count): Total > 40.0 to 49.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M009`	string		Margin of error (90% confidence) for the paired B25070_E009 estimate.
`B25070_E010`	string		ACS estimate (count): Total > 50.0 percent or more (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M010`	string		Margin of error (90% confidence) for the paired B25070_E010 estimate.
`B25070_E011`	string		ACS estimate (count): Total > Not computed (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M011`	string		Margin of error (90% confidence) for the paired B25070_E011 estimate.
`C16002_E001`	string		ACS estimate (count): Total (Household Language by Household Limited English Speaking Status).
`C16002_M001`	string		Margin of error (90% confidence) for the paired C16002_E001 estimate.
`C16002_E002`	string		ACS estimate (count): Total > English only (Household Language by Household Limited English Speaking Status).
`C16002_M002`	string		Margin of error (90% confidence) for the paired C16002_E002 estimate.
`C16002_E003`	string		ACS estimate (count): Total > Spanish (Household Language by Household Limited English Speaking Status).
`C16002_M003`	string		Margin of error (90% confidence) for the paired C16002_E003 estimate.
`C16002_E004`	string		ACS estimate (count): Total > Spanish > Limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M004`	string		Margin of error (90% confidence) for the paired C16002_E004 estimate.
`C16002_E005`	string		ACS estimate (count): Total > Spanish > Not a limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M005`	string		Margin of error (90% confidence) for the paired C16002_E005 estimate.
`C16002_E006`	string		ACS estimate (count): Total > Other Indo-European languages (Household Language by Household Limited English Speaking Status).
`C16002_M006`	string		Margin of error (90% confidence) for the paired C16002_E006 estimate.
`C16002_E007`	string		ACS estimate (count): Total > Other Indo-European languages > Limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M007`	string		Margin of error (90% confidence) for the paired C16002_E007 estimate.
`C16002_E008`	string		ACS estimate (count): Total > Other Indo-European languages > Not a limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M008`	string		Margin of error (90% confidence) for the paired C16002_E008 estimate.
`C16002_E009`	string		ACS estimate (count): Total > Asian and Pacific Island languages (Household Language by Household Limited English Speaking Status).
`C16002_M009`	string		Margin of error (90% confidence) for the paired C16002_E009 estimate.
`C16002_E010`	string		ACS estimate (count): Total > Asian and Pacific Island languages > Limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M010`	string		Margin of error (90% confidence) for the paired C16002_E010 estimate.
`C16002_E011`	string		ACS estimate (count): Total > Asian and Pacific Island languages > Not a limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M011`	string		Margin of error (90% confidence) for the paired C16002_E011 estimate.
`C16002_E012`	string		ACS estimate (count): Total > Other languages (Household Language by Household Limited English Speaking Status).
`C16002_M012`	string		Margin of error (90% confidence) for the paired C16002_E012 estimate.
`C16002_E013`	string		ACS estimate (count): Total > Other languages > Limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M013`	string		Margin of error (90% confidence) for the paired C16002_E013 estimate.
`C16002_E014`	string		ACS estimate (count): Total > Other languages > Not a limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M014`	string		Margin of error (90% confidence) for the paired C16002_E014 estimate.
`B19083_E001`	string		ACS estimate (count): Gini Index (Gini Index of Income Inequality).
`B19083_M001`	string		Margin of error (90% confidence) for the paired B19083_E001 estimate.
`B27001_E001`	string		ACS estimate (count): Total (Health Insurance Coverage Status by Sex by Age).
`B27001_M001`	string		Margin of error (90% confidence) for the paired B27001_E001 estimate.
`B27001_E002`	string		ACS estimate (count): Total > Male (Health Insurance Coverage Status by Sex by Age).
`B27001_M002`	string		Margin of error (90% confidence) for the paired B27001_E002 estimate.
`B27001_E003`	string		ACS estimate (count): Total > Male > Under 6 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M003`	string		Margin of error (90% confidence) for the paired B27001_E003 estimate.
`B27001_E004`	string		ACS estimate (count): Total > Male > Under 6 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M004`	string		Margin of error (90% confidence) for the paired B27001_E004 estimate.
`B27001_E005`	string		ACS estimate (count): Total > Male > Under 6 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M005`	string		Margin of error (90% confidence) for the paired B27001_E005 estimate.
`B27001_E006`	string		ACS estimate (count): Total > Male > 6 to 18 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M006`	string		Margin of error (90% confidence) for the paired B27001_E006 estimate.
`B27001_E007`	string		ACS estimate (count): Total > Male > 6 to 18 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M007`	string		Margin of error (90% confidence) for the paired B27001_E007 estimate.
`B27001_E008`	string		ACS estimate (count): Total > Male > 6 to 18 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M008`	string		Margin of error (90% confidence) for the paired B27001_E008 estimate.
`B27001_E009`	string		ACS estimate (count): Total > Male > 19 to 25 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M009`	string		Margin of error (90% confidence) for the paired B27001_E009 estimate.
`B27001_E010`	string		ACS estimate (count): Total > Male > 19 to 25 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M010`	string		Margin of error (90% confidence) for the paired B27001_E010 estimate.
`B27001_E011`	string		ACS estimate (count): Total > Male > 19 to 25 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M011`	string		Margin of error (90% confidence) for the paired B27001_E011 estimate.
`B27001_E012`	string		ACS estimate (count): Total > Male > 26 to 34 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M012`	string		Margin of error (90% confidence) for the paired B27001_E012 estimate.
`B27001_E013`	string		ACS estimate (count): Total > Male > 26 to 34 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M013`	string		Margin of error (90% confidence) for the paired B27001_E013 estimate.
`B27001_E014`	string		ACS estimate (count): Total > Male > 26 to 34 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M014`	string		Margin of error (90% confidence) for the paired B27001_E014 estimate.
`B27001_E015`	string		ACS estimate (count): Total > Male > 35 to 44 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M015`	string		Margin of error (90% confidence) for the paired B27001_E015 estimate.
`B27001_E016`	string		ACS estimate (count): Total > Male > 35 to 44 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M016`	string		Margin of error (90% confidence) for the paired B27001_E016 estimate.
`B27001_E017`	string		ACS estimate (count): Total > Male > 35 to 44 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M017`	string		Margin of error (90% confidence) for the paired B27001_E017 estimate.
`B27001_E018`	string		ACS estimate (count): Total > Male > 45 to 54 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M018`	string		Margin of error (90% confidence) for the paired B27001_E018 estimate.
`B27001_E019`	string		ACS estimate (count): Total > Male > 45 to 54 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M019`	string		Margin of error (90% confidence) for the paired B27001_E019 estimate.
`B27001_E020`	string		ACS estimate (count): Total > Male > 45 to 54 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M020`	string		Margin of error (90% confidence) for the paired B27001_E020 estimate.
`B27001_E021`	string		ACS estimate (count): Total > Male > 55 to 64 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M021`	string		Margin of error (90% confidence) for the paired B27001_E021 estimate.
`B27001_E022`	string		ACS estimate (count): Total > Male > 55 to 64 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M022`	string		Margin of error (90% confidence) for the paired B27001_E022 estimate.
`B27001_E023`	string		ACS estimate (count): Total > Male > 55 to 64 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M023`	string		Margin of error (90% confidence) for the paired B27001_E023 estimate.
`B27001_E024`	string		ACS estimate (count): Total > Male > 65 to 74 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M024`	string		Margin of error (90% confidence) for the paired B27001_E024 estimate.
`B27001_E025`	string		ACS estimate (count): Total > Male > 65 to 74 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M025`	string		Margin of error (90% confidence) for the paired B27001_E025 estimate.
`B27001_E026`	string		ACS estimate (count): Total > Male > 65 to 74 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M026`	string		Margin of error (90% confidence) for the paired B27001_E026 estimate.
`B27001_E027`	string		ACS estimate (count): Total > Male > 75 years and over (Health Insurance Coverage Status by Sex by Age).
`B27001_M027`	string		Margin of error (90% confidence) for the paired B27001_E027 estimate.
`B27001_E028`	string		ACS estimate (count): Total > Male > 75 years and over > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M028`	string		Margin of error (90% confidence) for the paired B27001_E028 estimate.
`B27001_E029`	string		ACS estimate (count): Total > Male > 75 years and over > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M029`	string		Margin of error (90% confidence) for the paired B27001_E029 estimate.
`B27001_E030`	string		ACS estimate (count): Total > Female (Health Insurance Coverage Status by Sex by Age).
`B27001_M030`	string		Margin of error (90% confidence) for the paired B27001_E030 estimate.
`B27001_E031`	string		ACS estimate (count): Total > Female > Under 6 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M031`	string		Margin of error (90% confidence) for the paired B27001_E031 estimate.
`B27001_E032`	string		ACS estimate (count): Total > Female > Under 6 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M032`	string		Margin of error (90% confidence) for the paired B27001_E032 estimate.
`B27001_E033`	string		ACS estimate (count): Total > Female > Under 6 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M033`	string		Margin of error (90% confidence) for the paired B27001_E033 estimate.
`B27001_E034`	string		ACS estimate (count): Total > Female > 6 to 18 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M034`	string		Margin of error (90% confidence) for the paired B27001_E034 estimate.
`B27001_E035`	string		ACS estimate (count): Total > Female > 6 to 18 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M035`	string		Margin of error (90% confidence) for the paired B27001_E035 estimate.
`B27001_E036`	string		ACS estimate (count): Total > Female > 6 to 18 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M036`	string		Margin of error (90% confidence) for the paired B27001_E036 estimate.
`B27001_E037`	string		ACS estimate (count): Total > Female > 19 to 25 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M037`	string		Margin of error (90% confidence) for the paired B27001_E037 estimate.
`B27001_E038`	string		ACS estimate (count): Total > Female > 19 to 25 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M038`	string		Margin of error (90% confidence) for the paired B27001_E038 estimate.
`B27001_E039`	string		ACS estimate (count): Total > Female > 19 to 25 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M039`	string		Margin of error (90% confidence) for the paired B27001_E039 estimate.
`B27001_E040`	string		ACS estimate (count): Total > Female > 26 to 34 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M040`	string		Margin of error (90% confidence) for the paired B27001_E040 estimate.
`B27001_E041`	string		ACS estimate (count): Total > Female > 26 to 34 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M041`	string		Margin of error (90% confidence) for the paired B27001_E041 estimate.
`B27001_E042`	string		ACS estimate (count): Total > Female > 26 to 34 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M042`	string		Margin of error (90% confidence) for the paired B27001_E042 estimate.
`B27001_E043`	string		ACS estimate (count): Total > Female > 35 to 44 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M043`	string		Margin of error (90% confidence) for the paired B27001_E043 estimate.
`B27001_E044`	string		ACS estimate (count): Total > Female > 35 to 44 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M044`	string		Margin of error (90% confidence) for the paired B27001_E044 estimate.
`B27001_E045`	string		ACS estimate (count): Total > Female > 35 to 44 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M045`	string		Margin of error (90% confidence) for the paired B27001_E045 estimate.
`B27001_E046`	string		ACS estimate (count): Total > Female > 45 to 54 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M046`	string		Margin of error (90% confidence) for the paired B27001_E046 estimate.
`B27001_E047`	string		ACS estimate (count): Total > Female > 45 to 54 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M047`	string		Margin of error (90% confidence) for the paired B27001_E047 estimate.
`B27001_E048`	string		ACS estimate (count): Total > Female > 45 to 54 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M048`	string		Margin of error (90% confidence) for the paired B27001_E048 estimate.
`B27001_E049`	string		ACS estimate (count): Total > Female > 55 to 64 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M049`	string		Margin of error (90% confidence) for the paired B27001_E049 estimate.
`B27001_E050`	string		ACS estimate (count): Total > Female > 55 to 64 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M050`	string		Margin of error (90% confidence) for the paired B27001_E050 estimate.
`B27001_E051`	string		ACS estimate (count): Total > Female > 55 to 64 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M051`	string		Margin of error (90% confidence) for the paired B27001_E051 estimate.
`B27001_E052`	string		ACS estimate (count): Total > Female > 65 to 74 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M052`	string		Margin of error (90% confidence) for the paired B27001_E052 estimate.
`B27001_E053`	string		ACS estimate (count): Total > Female > 65 to 74 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M053`	string		Margin of error (90% confidence) for the paired B27001_E053 estimate.
`B27001_E054`	string		ACS estimate (count): Total > Female > 65 to 74 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M054`	string		Margin of error (90% confidence) for the paired B27001_E054 estimate.
`B27001_E055`	string		ACS estimate (count): Total > Female > 75 years and over (Health Insurance Coverage Status by Sex by Age).
`B27001_M055`	string		Margin of error (90% confidence) for the paired B27001_E055 estimate.
`B27001_E056`	string		ACS estimate (count): Total > Female > 75 years and over > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M056`	string		Margin of error (90% confidence) for the paired B27001_E056 estimate.
`B27001_E057`	string		ACS estimate (count): Total > Female > 75 years and over > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M057`	string		Margin of error (90% confidence) for the paired B27001_E057 estimate.
`C27007_E001`	string		ACS estimate (count): Total (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M001`	string		Margin of error (90% confidence) for the paired C27007_E001 estimate.
`C27007_E002`	string		ACS estimate (count): Total > Male (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M002`	string		Margin of error (90% confidence) for the paired C27007_E002 estimate.
`C27007_E003`	string		ACS estimate (count): Total > Male > Under 19 years (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M003`	string		Margin of error (90% confidence) for the paired C27007_E003 estimate.
`C27007_E004`	string		ACS estimate (count): Total > Male > Under 19 years > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M004`	string		Margin of error (90% confidence) for the paired C27007_E004 estimate.
`C27007_E005`	string		ACS estimate (count): Total > Male > Under 19 years > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M005`	string		Margin of error (90% confidence) for the paired C27007_E005 estimate.
`C27007_E006`	string		ACS estimate (count): Total > Male > 19 to 64 years (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M006`	string		Margin of error (90% confidence) for the paired C27007_E006 estimate.
`C27007_E007`	string		ACS estimate (count): Total > Male > 19 to 64 years > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M007`	string		Margin of error (90% confidence) for the paired C27007_E007 estimate.
`C27007_E008`	string		ACS estimate (count): Total > Male > 19 to 64 years > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M008`	string		Margin of error (90% confidence) for the paired C27007_E008 estimate.
`C27007_E009`	string		ACS estimate (count): Total > Male > 65 years and over (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M009`	string		Margin of error (90% confidence) for the paired C27007_E009 estimate.
`C27007_E010`	string		ACS estimate (count): Total > Male > 65 years and over > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M010`	string		Margin of error (90% confidence) for the paired C27007_E010 estimate.
`C27007_E011`	string		ACS estimate (count): Total > Male > 65 years and over > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M011`	string		Margin of error (90% confidence) for the paired C27007_E011 estimate.
`C27007_E012`	string		ACS estimate (count): Total > Female (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M012`	string		Margin of error (90% confidence) for the paired C27007_E012 estimate.
`C27007_E013`	string		ACS estimate (count): Total > Female > Under 19 years (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M013`	string		Margin of error (90% confidence) for the paired C27007_E013 estimate.
`C27007_E014`	string		ACS estimate (count): Total > Female > Under 19 years > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M014`	string		Margin of error (90% confidence) for the paired C27007_E014 estimate.
`C27007_E015`	string		ACS estimate (count): Total > Female > Under 19 years > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M015`	string		Margin of error (90% confidence) for the paired C27007_E015 estimate.
`C27007_E016`	string		ACS estimate (count): Total > Female > 19 to 64 years (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M016`	string		Margin of error (90% confidence) for the paired C27007_E016 estimate.
`C27007_E017`	string		ACS estimate (count): Total > Female > 19 to 64 years > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M017`	string		Margin of error (90% confidence) for the paired C27007_E017 estimate.
`C27007_E018`	string		ACS estimate (count): Total > Female > 19 to 64 years > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M018`	string		Margin of error (90% confidence) for the paired C27007_E018 estimate.
`C27007_E019`	string		ACS estimate (count): Total > Female > 65 years and over (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M019`	string		Margin of error (90% confidence) for the paired C27007_E019 estimate.
`C27007_E020`	string		ACS estimate (count): Total > Female > 65 years and over > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M020`	string		Margin of error (90% confidence) for the paired C27007_E020 estimate.
`C27007_E021`	string		ACS estimate (count): Total > Female > 65 years and over > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M021`	string		Margin of error (90% confidence) for the paired C27007_E021 estimate.

`raw.acs__tract`

Sorted by: acs_year, geo_id

Column	Type	Required	Doc
`geo_id`	string	yes	Canonical geo_id: ‘county:<5-digit FIPS>’ or ‘tract:<11-digit FIPS>’, matching the raw table’s own level.
`acs_year`	int	yes	The 5-year release’s end year (e.g. 2023 for the 2019-2023 release) – the version column raw is scoped and overwritten by.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.
`B01003_E001`	string		ACS estimate (count): Total (Total Population).
`B01003_M001`	string		Margin of error (90% confidence) for the paired B01003_E001 estimate.
`B09001_E001`	string		ACS estimate (count): Total (Population Under 18 Years by Age).
`B09001_M001`	string		Margin of error (90% confidence) for the paired B09001_E001 estimate.
`B09001_E002`	string		ACS estimate (count): Total > In households (Population Under 18 Years by Age).
`B09001_M002`	string		Margin of error (90% confidence) for the paired B09001_E002 estimate.
`B09001_E003`	string		ACS estimate (count): Total > In households > Under 3 years (Population Under 18 Years by Age).
`B09001_M003`	string		Margin of error (90% confidence) for the paired B09001_E003 estimate.
`B09001_E004`	string		ACS estimate (count): Total > In households > 3 and 4 years (Population Under 18 Years by Age).
`B09001_M004`	string		Margin of error (90% confidence) for the paired B09001_E004 estimate.
`B09001_E005`	string		ACS estimate (count): Total > In households > 5 years (Population Under 18 Years by Age).
`B09001_M005`	string		Margin of error (90% confidence) for the paired B09001_E005 estimate.
`B09001_E006`	string		ACS estimate (count): Total > In households > 6 to 8 years (Population Under 18 Years by Age).
`B09001_M006`	string		Margin of error (90% confidence) for the paired B09001_E006 estimate.
`B09001_E007`	string		ACS estimate (count): Total > In households > 9 to 11 years (Population Under 18 Years by Age).
`B09001_M007`	string		Margin of error (90% confidence) for the paired B09001_E007 estimate.
`B09001_E008`	string		ACS estimate (count): Total > In households > 12 to 14 years (Population Under 18 Years by Age).
`B09001_M008`	string		Margin of error (90% confidence) for the paired B09001_E008 estimate.
`B09001_E009`	string		ACS estimate (count): Total > In households > 15 to 17 years (Population Under 18 Years by Age).
`B09001_M009`	string		Margin of error (90% confidence) for the paired B09001_E009 estimate.
`B09001_E010`	string		ACS estimate (count): Total > In group quarters (Population Under 18 Years by Age).
`B09001_M010`	string		Margin of error (90% confidence) for the paired B09001_E010 estimate.
`B09020_E001`	string		ACS estimate (count): Total (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M001`	string		Margin of error (90% confidence) for the paired B09020_E001 estimate.
`B09020_E002`	string		ACS estimate (count): Total > In households (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M002`	string		Margin of error (90% confidence) for the paired B09020_E002 estimate.
`B09020_E003`	string		ACS estimate (count): Total > In households > In family households (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M003`	string		Margin of error (90% confidence) for the paired B09020_E003 estimate.
`B09020_E004`	string		ACS estimate (count): Total > In households > In family households > Householder (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M004`	string		Margin of error (90% confidence) for the paired B09020_E004 estimate.
`B09020_E005`	string		ACS estimate (count): Total > In households > In family households > Householder > Male (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M005`	string		Margin of error (90% confidence) for the paired B09020_E005 estimate.
`B09020_E006`	string		ACS estimate (count): Total > In households > In family households > Householder > Female (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M006`	string		Margin of error (90% confidence) for the paired B09020_E006 estimate.
`B09020_E007`	string		ACS estimate (count): Total > In households > In family households > Spouse (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M007`	string		Margin of error (90% confidence) for the paired B09020_E007 estimate.
`B09020_E008`	string		ACS estimate (count): Total > In households > In family households > Parent (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M008`	string		Margin of error (90% confidence) for the paired B09020_E008 estimate.
`B09020_E009`	string		ACS estimate (count): Total > In households > In family households > Parent-in-law (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M009`	string		Margin of error (90% confidence) for the paired B09020_E009 estimate.
`B09020_E010`	string		ACS estimate (count): Total > In households > In family households > Other relatives (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M010`	string		Margin of error (90% confidence) for the paired B09020_E010 estimate.
`B09020_E011`	string		ACS estimate (count): Total > In households > In family households > Nonrelatives (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M011`	string		Margin of error (90% confidence) for the paired B09020_E011 estimate.
`B09020_E012`	string		ACS estimate (count): Total > In households > In nonfamily households (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M012`	string		Margin of error (90% confidence) for the paired B09020_E012 estimate.
`B09020_E013`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M013`	string		Margin of error (90% confidence) for the paired B09020_E013 estimate.
`B09020_E014`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Male (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M014`	string		Margin of error (90% confidence) for the paired B09020_E014 estimate.
`B09020_E015`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Male > Living alone (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M015`	string		Margin of error (90% confidence) for the paired B09020_E015 estimate.
`B09020_E016`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Male > Not living alone (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M016`	string		Margin of error (90% confidence) for the paired B09020_E016 estimate.
`B09020_E017`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Female (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M017`	string		Margin of error (90% confidence) for the paired B09020_E017 estimate.
`B09020_E018`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Female > Living alone (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M018`	string		Margin of error (90% confidence) for the paired B09020_E018 estimate.
`B09020_E019`	string		ACS estimate (count): Total > In households > In nonfamily households > Householder > Female > Not living alone (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M019`	string		Margin of error (90% confidence) for the paired B09020_E019 estimate.
`B09020_E020`	string		ACS estimate (count): Total > In households > In nonfamily households > Nonrelatives (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M020`	string		Margin of error (90% confidence) for the paired B09020_E020 estimate.
`B09020_E021`	string		ACS estimate (count): Total > In group quarters (Relationship by Household Type (Including Living Alone) for the Population 65 Years and Over).
`B09020_M021`	string		Margin of error (90% confidence) for the paired B09020_E021 estimate.
`B03002_E001`	string		ACS estimate (count): Total (Hispanic or Latino Origin by Race).
`B03002_M001`	string		Margin of error (90% confidence) for the paired B03002_E001 estimate.
`B03002_E002`	string		ACS estimate (count): Total > Not Hispanic or Latino (Hispanic or Latino Origin by Race).
`B03002_M002`	string		Margin of error (90% confidence) for the paired B03002_E002 estimate.
`B03002_E003`	string		ACS estimate (count): Total > Not Hispanic or Latino > White alone (Hispanic or Latino Origin by Race).
`B03002_M003`	string		Margin of error (90% confidence) for the paired B03002_E003 estimate.
`B03002_E004`	string		ACS estimate (count): Total > Not Hispanic or Latino > Black or African American alone (Hispanic or Latino Origin by Race).
`B03002_M004`	string		Margin of error (90% confidence) for the paired B03002_E004 estimate.
`B03002_E005`	string		ACS estimate (count): Total > Not Hispanic or Latino > American Indian and Alaska Native alone (Hispanic or Latino Origin by Race).
`B03002_M005`	string		Margin of error (90% confidence) for the paired B03002_E005 estimate.
`B03002_E006`	string		ACS estimate (count): Total > Not Hispanic or Latino > Asian alone (Hispanic or Latino Origin by Race).
`B03002_M006`	string		Margin of error (90% confidence) for the paired B03002_E006 estimate.
`B03002_E007`	string		ACS estimate (count): Total > Not Hispanic or Latino > Native Hawaiian and Other Pacific Islander alone (Hispanic or Latino Origin by Race).
`B03002_M007`	string		Margin of error (90% confidence) for the paired B03002_E007 estimate.
`B03002_E008`	string		ACS estimate (count): Total > Not Hispanic or Latino > Some other race alone (Hispanic or Latino Origin by Race).
`B03002_M008`	string		Margin of error (90% confidence) for the paired B03002_E008 estimate.
`B03002_E009`	string		ACS estimate (count): Total > Not Hispanic or Latino > Two or more races (Hispanic or Latino Origin by Race).
`B03002_M009`	string		Margin of error (90% confidence) for the paired B03002_E009 estimate.
`B03002_E010`	string		ACS estimate (count): Total > Not Hispanic or Latino > Two or more races > Two races including Some other race (Hispanic or Latino Origin by Race).
`B03002_M010`	string		Margin of error (90% confidence) for the paired B03002_E010 estimate.
`B03002_E011`	string		ACS estimate (count): Total > Not Hispanic or Latino > Two or more races > Two races excluding Some other race, and three or more races (Hispanic or Latino Origin by Race).
`B03002_M011`	string		Margin of error (90% confidence) for the paired B03002_E011 estimate.
`B03002_E012`	string		ACS estimate (count): Total > Hispanic or Latino (Hispanic or Latino Origin by Race).
`B03002_M012`	string		Margin of error (90% confidence) for the paired B03002_E012 estimate.
`B03002_E013`	string		ACS estimate (count): Total > Hispanic or Latino > White alone (Hispanic or Latino Origin by Race).
`B03002_M013`	string		Margin of error (90% confidence) for the paired B03002_E013 estimate.
`B03002_E014`	string		ACS estimate (count): Total > Hispanic or Latino > Black or African American alone (Hispanic or Latino Origin by Race).
`B03002_M014`	string		Margin of error (90% confidence) for the paired B03002_E014 estimate.
`B03002_E015`	string		ACS estimate (count): Total > Hispanic or Latino > American Indian and Alaska Native alone (Hispanic or Latino Origin by Race).
`B03002_M015`	string		Margin of error (90% confidence) for the paired B03002_E015 estimate.
`B03002_E016`	string		ACS estimate (count): Total > Hispanic or Latino > Asian alone (Hispanic or Latino Origin by Race).
`B03002_M016`	string		Margin of error (90% confidence) for the paired B03002_E016 estimate.
`B03002_E017`	string		ACS estimate (count): Total > Hispanic or Latino > Native Hawaiian and Other Pacific Islander alone (Hispanic or Latino Origin by Race).
`B03002_M017`	string		Margin of error (90% confidence) for the paired B03002_E017 estimate.
`B03002_E018`	string		ACS estimate (count): Total > Hispanic or Latino > Some other race alone (Hispanic or Latino Origin by Race).
`B03002_M018`	string		Margin of error (90% confidence) for the paired B03002_E018 estimate.
`B03002_E019`	string		ACS estimate (count): Total > Hispanic or Latino > Two or more races (Hispanic or Latino Origin by Race).
`B03002_M019`	string		Margin of error (90% confidence) for the paired B03002_E019 estimate.
`B03002_E020`	string		ACS estimate (count): Total > Hispanic or Latino > Two or more races > Two races including Some other race (Hispanic or Latino Origin by Race).
`B03002_M020`	string		Margin of error (90% confidence) for the paired B03002_E020 estimate.
`B03002_E021`	string		ACS estimate (count): Total > Hispanic or Latino > Two or more races > Two races excluding Some other race, and three or more races (Hispanic or Latino Origin by Race).
`B03002_M021`	string		Margin of error (90% confidence) for the paired B03002_E021 estimate.
`B15003_E001`	string		ACS estimate (count): Total (Educational Attainment for the Population 25 Years and Over).
`B15003_M001`	string		Margin of error (90% confidence) for the paired B15003_E001 estimate.
`B15003_E002`	string		ACS estimate (count): Total > No schooling completed (Educational Attainment for the Population 25 Years and Over).
`B15003_M002`	string		Margin of error (90% confidence) for the paired B15003_E002 estimate.
`B15003_E003`	string		ACS estimate (count): Total > Nursery school (Educational Attainment for the Population 25 Years and Over).
`B15003_M003`	string		Margin of error (90% confidence) for the paired B15003_E003 estimate.
`B15003_E004`	string		ACS estimate (count): Total > Kindergarten (Educational Attainment for the Population 25 Years and Over).
`B15003_M004`	string		Margin of error (90% confidence) for the paired B15003_E004 estimate.
`B15003_E005`	string		ACS estimate (count): Total > 1st grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M005`	string		Margin of error (90% confidence) for the paired B15003_E005 estimate.
`B15003_E006`	string		ACS estimate (count): Total > 2nd grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M006`	string		Margin of error (90% confidence) for the paired B15003_E006 estimate.
`B15003_E007`	string		ACS estimate (count): Total > 3rd grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M007`	string		Margin of error (90% confidence) for the paired B15003_E007 estimate.
`B15003_E008`	string		ACS estimate (count): Total > 4th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M008`	string		Margin of error (90% confidence) for the paired B15003_E008 estimate.
`B15003_E009`	string		ACS estimate (count): Total > 5th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M009`	string		Margin of error (90% confidence) for the paired B15003_E009 estimate.
`B15003_E010`	string		ACS estimate (count): Total > 6th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M010`	string		Margin of error (90% confidence) for the paired B15003_E010 estimate.
`B15003_E011`	string		ACS estimate (count): Total > 7th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M011`	string		Margin of error (90% confidence) for the paired B15003_E011 estimate.
`B15003_E012`	string		ACS estimate (count): Total > 8th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M012`	string		Margin of error (90% confidence) for the paired B15003_E012 estimate.
`B15003_E013`	string		ACS estimate (count): Total > 9th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M013`	string		Margin of error (90% confidence) for the paired B15003_E013 estimate.
`B15003_E014`	string		ACS estimate (count): Total > 10th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M014`	string		Margin of error (90% confidence) for the paired B15003_E014 estimate.
`B15003_E015`	string		ACS estimate (count): Total > 11th grade (Educational Attainment for the Population 25 Years and Over).
`B15003_M015`	string		Margin of error (90% confidence) for the paired B15003_E015 estimate.
`B15003_E016`	string		ACS estimate (count): Total > 12th grade, no diploma (Educational Attainment for the Population 25 Years and Over).
`B15003_M016`	string		Margin of error (90% confidence) for the paired B15003_E016 estimate.
`B15003_E017`	string		ACS estimate (count): Total > Regular high school diploma (Educational Attainment for the Population 25 Years and Over).
`B15003_M017`	string		Margin of error (90% confidence) for the paired B15003_E017 estimate.
`B15003_E018`	string		ACS estimate (count): Total > GED or alternative credential (Educational Attainment for the Population 25 Years and Over).
`B15003_M018`	string		Margin of error (90% confidence) for the paired B15003_E018 estimate.
`B15003_E019`	string		ACS estimate (count): Total > Some college, less than 1 year (Educational Attainment for the Population 25 Years and Over).
`B15003_M019`	string		Margin of error (90% confidence) for the paired B15003_E019 estimate.
`B15003_E020`	string		ACS estimate (count): Total > Some college, 1 or more years, no degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M020`	string		Margin of error (90% confidence) for the paired B15003_E020 estimate.
`B15003_E021`	string		ACS estimate (count): Total > Associate’s degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M021`	string		Margin of error (90% confidence) for the paired B15003_E021 estimate.
`B15003_E022`	string		ACS estimate (count): Total > Bachelor’s degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M022`	string		Margin of error (90% confidence) for the paired B15003_E022 estimate.
`B15003_E023`	string		ACS estimate (count): Total > Master’s degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M023`	string		Margin of error (90% confidence) for the paired B15003_E023 estimate.
`B15003_E024`	string		ACS estimate (count): Total > Professional school degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M024`	string		Margin of error (90% confidence) for the paired B15003_E024 estimate.
`B15003_E025`	string		ACS estimate (count): Total > Doctorate degree (Educational Attainment for the Population 25 Years and Over).
`B15003_M025`	string		Margin of error (90% confidence) for the paired B15003_E025 estimate.
`B19013_E001`	string		ACS estimate (count): Median household income in the past 12 months (in 2023 inflation-adjusted dollars) (Median Household Income in the Past 12 Months (in 2023 Inflation-Adjusted Dollars)).
`B19013_M001`	string		Margin of error (90% confidence) for the paired B19013_E001 estimate.
`C17002_E001`	string		ACS estimate (count): Total (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M001`	string		Margin of error (90% confidence) for the paired C17002_E001 estimate.
`C17002_E002`	string		ACS estimate (count): Total > Under .50 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M002`	string		Margin of error (90% confidence) for the paired C17002_E002 estimate.
`C17002_E003`	string		ACS estimate (count): Total > .50 to .99 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M003`	string		Margin of error (90% confidence) for the paired C17002_E003 estimate.
`C17002_E004`	string		ACS estimate (count): Total > 1.00 to 1.24 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M004`	string		Margin of error (90% confidence) for the paired C17002_E004 estimate.
`C17002_E005`	string		ACS estimate (count): Total > 1.25 to 1.49 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M005`	string		Margin of error (90% confidence) for the paired C17002_E005 estimate.
`C17002_E006`	string		ACS estimate (count): Total > 1.50 to 1.84 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M006`	string		Margin of error (90% confidence) for the paired C17002_E006 estimate.
`C17002_E007`	string		ACS estimate (count): Total > 1.85 to 1.99 (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M007`	string		Margin of error (90% confidence) for the paired C17002_E007 estimate.
`C17002_E008`	string		ACS estimate (count): Total > 2.00 and over (Ratio of Income to Poverty Level in the Past 12 Months).
`C17002_M008`	string		Margin of error (90% confidence) for the paired C17002_E008 estimate.
`B23025_E001`	string		ACS estimate (count): Total (Employment Status for the Population 16 Years and Over).
`B23025_M001`	string		Margin of error (90% confidence) for the paired B23025_E001 estimate.
`B23025_E002`	string		ACS estimate (count): Total > In labor force (Employment Status for the Population 16 Years and Over).
`B23025_M002`	string		Margin of error (90% confidence) for the paired B23025_E002 estimate.
`B23025_E003`	string		ACS estimate (count): Total > In labor force > Civilian labor force (Employment Status for the Population 16 Years and Over).
`B23025_M003`	string		Margin of error (90% confidence) for the paired B23025_E003 estimate.
`B23025_E004`	string		ACS estimate (count): Total > In labor force > Civilian labor force > Employed (Employment Status for the Population 16 Years and Over).
`B23025_M004`	string		Margin of error (90% confidence) for the paired B23025_E004 estimate.
`B23025_E005`	string		ACS estimate (count): Total > In labor force > Civilian labor force > Unemployed (Employment Status for the Population 16 Years and Over).
`B23025_M005`	string		Margin of error (90% confidence) for the paired B23025_E005 estimate.
`B23025_E006`	string		ACS estimate (count): Total > In labor force > Armed Forces (Employment Status for the Population 16 Years and Over).
`B23025_M006`	string		Margin of error (90% confidence) for the paired B23025_E006 estimate.
`B23025_E007`	string		ACS estimate (count): Total > Not in labor force (Employment Status for the Population 16 Years and Over).
`B23025_M007`	string		Margin of error (90% confidence) for the paired B23025_E007 estimate.
`B25044_E001`	string		ACS estimate (count): Total (Tenure by Vehicles Available).
`B25044_M001`	string		Margin of error (90% confidence) for the paired B25044_E001 estimate.
`B25044_E002`	string		ACS estimate (count): Total > Owner occupied (Tenure by Vehicles Available).
`B25044_M002`	string		Margin of error (90% confidence) for the paired B25044_E002 estimate.
`B25044_E003`	string		ACS estimate (count): Total > Owner occupied > No vehicle available (Tenure by Vehicles Available).
`B25044_M003`	string		Margin of error (90% confidence) for the paired B25044_E003 estimate.
`B25044_E004`	string		ACS estimate (count): Total > Owner occupied > 1 vehicle available (Tenure by Vehicles Available).
`B25044_M004`	string		Margin of error (90% confidence) for the paired B25044_E004 estimate.
`B25044_E005`	string		ACS estimate (count): Total > Owner occupied > 2 vehicles available (Tenure by Vehicles Available).
`B25044_M005`	string		Margin of error (90% confidence) for the paired B25044_E005 estimate.
`B25044_E006`	string		ACS estimate (count): Total > Owner occupied > 3 vehicles available (Tenure by Vehicles Available).
`B25044_M006`	string		Margin of error (90% confidence) for the paired B25044_E006 estimate.
`B25044_E007`	string		ACS estimate (count): Total > Owner occupied > 4 vehicles available (Tenure by Vehicles Available).
`B25044_M007`	string		Margin of error (90% confidence) for the paired B25044_E007 estimate.
`B25044_E008`	string		ACS estimate (count): Total > Owner occupied > 5 or more vehicles available (Tenure by Vehicles Available).
`B25044_M008`	string		Margin of error (90% confidence) for the paired B25044_E008 estimate.
`B25044_E009`	string		ACS estimate (count): Total > Renter occupied (Tenure by Vehicles Available).
`B25044_M009`	string		Margin of error (90% confidence) for the paired B25044_E009 estimate.
`B25044_E010`	string		ACS estimate (count): Total > Renter occupied > No vehicle available (Tenure by Vehicles Available).
`B25044_M010`	string		Margin of error (90% confidence) for the paired B25044_E010 estimate.
`B25044_E011`	string		ACS estimate (count): Total > Renter occupied > 1 vehicle available (Tenure by Vehicles Available).
`B25044_M011`	string		Margin of error (90% confidence) for the paired B25044_E011 estimate.
`B25044_E012`	string		ACS estimate (count): Total > Renter occupied > 2 vehicles available (Tenure by Vehicles Available).
`B25044_M012`	string		Margin of error (90% confidence) for the paired B25044_E012 estimate.
`B25044_E013`	string		ACS estimate (count): Total > Renter occupied > 3 vehicles available (Tenure by Vehicles Available).
`B25044_M013`	string		Margin of error (90% confidence) for the paired B25044_E013 estimate.
`B25044_E014`	string		ACS estimate (count): Total > Renter occupied > 4 vehicles available (Tenure by Vehicles Available).
`B25044_M014`	string		Margin of error (90% confidence) for the paired B25044_E014 estimate.
`B25044_E015`	string		ACS estimate (count): Total > Renter occupied > 5 or more vehicles available (Tenure by Vehicles Available).
`B25044_M015`	string		Margin of error (90% confidence) for the paired B25044_E015 estimate.
`B25002_E001`	string		ACS estimate (count): Total (Occupancy Status).
`B25002_M001`	string		Margin of error (90% confidence) for the paired B25002_E001 estimate.
`B25002_E002`	string		ACS estimate (count): Total > Occupied (Occupancy Status).
`B25002_M002`	string		Margin of error (90% confidence) for the paired B25002_E002 estimate.
`B25002_E003`	string		ACS estimate (count): Total > Vacant (Occupancy Status).
`B25002_M003`	string		Margin of error (90% confidence) for the paired B25002_E003 estimate.
`B25070_E001`	string		ACS estimate (count): Total (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M001`	string		Margin of error (90% confidence) for the paired B25070_E001 estimate.
`B25070_E002`	string		ACS estimate (count): Total > Less than 10.0 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M002`	string		Margin of error (90% confidence) for the paired B25070_E002 estimate.
`B25070_E003`	string		ACS estimate (count): Total > 10.0 to 14.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M003`	string		Margin of error (90% confidence) for the paired B25070_E003 estimate.
`B25070_E004`	string		ACS estimate (count): Total > 15.0 to 19.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M004`	string		Margin of error (90% confidence) for the paired B25070_E004 estimate.
`B25070_E005`	string		ACS estimate (count): Total > 20.0 to 24.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M005`	string		Margin of error (90% confidence) for the paired B25070_E005 estimate.
`B25070_E006`	string		ACS estimate (count): Total > 25.0 to 29.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M006`	string		Margin of error (90% confidence) for the paired B25070_E006 estimate.
`B25070_E007`	string		ACS estimate (count): Total > 30.0 to 34.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M007`	string		Margin of error (90% confidence) for the paired B25070_E007 estimate.
`B25070_E008`	string		ACS estimate (count): Total > 35.0 to 39.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M008`	string		Margin of error (90% confidence) for the paired B25070_E008 estimate.
`B25070_E009`	string		ACS estimate (count): Total > 40.0 to 49.9 percent (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M009`	string		Margin of error (90% confidence) for the paired B25070_E009 estimate.
`B25070_E010`	string		ACS estimate (count): Total > 50.0 percent or more (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M010`	string		Margin of error (90% confidence) for the paired B25070_E010 estimate.
`B25070_E011`	string		ACS estimate (count): Total > Not computed (Gross Rent as a Percentage of Household Income in the Past 12 Months).
`B25070_M011`	string		Margin of error (90% confidence) for the paired B25070_E011 estimate.
`C16002_E001`	string		ACS estimate (count): Total (Household Language by Household Limited English Speaking Status).
`C16002_M001`	string		Margin of error (90% confidence) for the paired C16002_E001 estimate.
`C16002_E002`	string		ACS estimate (count): Total > English only (Household Language by Household Limited English Speaking Status).
`C16002_M002`	string		Margin of error (90% confidence) for the paired C16002_E002 estimate.
`C16002_E003`	string		ACS estimate (count): Total > Spanish (Household Language by Household Limited English Speaking Status).
`C16002_M003`	string		Margin of error (90% confidence) for the paired C16002_E003 estimate.
`C16002_E004`	string		ACS estimate (count): Total > Spanish > Limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M004`	string		Margin of error (90% confidence) for the paired C16002_E004 estimate.
`C16002_E005`	string		ACS estimate (count): Total > Spanish > Not a limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M005`	string		Margin of error (90% confidence) for the paired C16002_E005 estimate.
`C16002_E006`	string		ACS estimate (count): Total > Other Indo-European languages (Household Language by Household Limited English Speaking Status).
`C16002_M006`	string		Margin of error (90% confidence) for the paired C16002_E006 estimate.
`C16002_E007`	string		ACS estimate (count): Total > Other Indo-European languages > Limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M007`	string		Margin of error (90% confidence) for the paired C16002_E007 estimate.
`C16002_E008`	string		ACS estimate (count): Total > Other Indo-European languages > Not a limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M008`	string		Margin of error (90% confidence) for the paired C16002_E008 estimate.
`C16002_E009`	string		ACS estimate (count): Total > Asian and Pacific Island languages (Household Language by Household Limited English Speaking Status).
`C16002_M009`	string		Margin of error (90% confidence) for the paired C16002_E009 estimate.
`C16002_E010`	string		ACS estimate (count): Total > Asian and Pacific Island languages > Limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M010`	string		Margin of error (90% confidence) for the paired C16002_E010 estimate.
`C16002_E011`	string		ACS estimate (count): Total > Asian and Pacific Island languages > Not a limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M011`	string		Margin of error (90% confidence) for the paired C16002_E011 estimate.
`C16002_E012`	string		ACS estimate (count): Total > Other languages (Household Language by Household Limited English Speaking Status).
`C16002_M012`	string		Margin of error (90% confidence) for the paired C16002_E012 estimate.
`C16002_E013`	string		ACS estimate (count): Total > Other languages > Limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M013`	string		Margin of error (90% confidence) for the paired C16002_E013 estimate.
`C16002_E014`	string		ACS estimate (count): Total > Other languages > Not a limited English speaking household (Household Language by Household Limited English Speaking Status).
`C16002_M014`	string		Margin of error (90% confidence) for the paired C16002_E014 estimate.
`B19083_E001`	string		ACS estimate (count): Gini Index (Gini Index of Income Inequality).
`B19083_M001`	string		Margin of error (90% confidence) for the paired B19083_E001 estimate.
`B27001_E001`	string		ACS estimate (count): Total (Health Insurance Coverage Status by Sex by Age).
`B27001_M001`	string		Margin of error (90% confidence) for the paired B27001_E001 estimate.
`B27001_E002`	string		ACS estimate (count): Total > Male (Health Insurance Coverage Status by Sex by Age).
`B27001_M002`	string		Margin of error (90% confidence) for the paired B27001_E002 estimate.
`B27001_E003`	string		ACS estimate (count): Total > Male > Under 6 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M003`	string		Margin of error (90% confidence) for the paired B27001_E003 estimate.
`B27001_E004`	string		ACS estimate (count): Total > Male > Under 6 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M004`	string		Margin of error (90% confidence) for the paired B27001_E004 estimate.
`B27001_E005`	string		ACS estimate (count): Total > Male > Under 6 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M005`	string		Margin of error (90% confidence) for the paired B27001_E005 estimate.
`B27001_E006`	string		ACS estimate (count): Total > Male > 6 to 18 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M006`	string		Margin of error (90% confidence) for the paired B27001_E006 estimate.
`B27001_E007`	string		ACS estimate (count): Total > Male > 6 to 18 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M007`	string		Margin of error (90% confidence) for the paired B27001_E007 estimate.
`B27001_E008`	string		ACS estimate (count): Total > Male > 6 to 18 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M008`	string		Margin of error (90% confidence) for the paired B27001_E008 estimate.
`B27001_E009`	string		ACS estimate (count): Total > Male > 19 to 25 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M009`	string		Margin of error (90% confidence) for the paired B27001_E009 estimate.
`B27001_E010`	string		ACS estimate (count): Total > Male > 19 to 25 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M010`	string		Margin of error (90% confidence) for the paired B27001_E010 estimate.
`B27001_E011`	string		ACS estimate (count): Total > Male > 19 to 25 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M011`	string		Margin of error (90% confidence) for the paired B27001_E011 estimate.
`B27001_E012`	string		ACS estimate (count): Total > Male > 26 to 34 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M012`	string		Margin of error (90% confidence) for the paired B27001_E012 estimate.
`B27001_E013`	string		ACS estimate (count): Total > Male > 26 to 34 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M013`	string		Margin of error (90% confidence) for the paired B27001_E013 estimate.
`B27001_E014`	string		ACS estimate (count): Total > Male > 26 to 34 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M014`	string		Margin of error (90% confidence) for the paired B27001_E014 estimate.
`B27001_E015`	string		ACS estimate (count): Total > Male > 35 to 44 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M015`	string		Margin of error (90% confidence) for the paired B27001_E015 estimate.
`B27001_E016`	string		ACS estimate (count): Total > Male > 35 to 44 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M016`	string		Margin of error (90% confidence) for the paired B27001_E016 estimate.
`B27001_E017`	string		ACS estimate (count): Total > Male > 35 to 44 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M017`	string		Margin of error (90% confidence) for the paired B27001_E017 estimate.
`B27001_E018`	string		ACS estimate (count): Total > Male > 45 to 54 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M018`	string		Margin of error (90% confidence) for the paired B27001_E018 estimate.
`B27001_E019`	string		ACS estimate (count): Total > Male > 45 to 54 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M019`	string		Margin of error (90% confidence) for the paired B27001_E019 estimate.
`B27001_E020`	string		ACS estimate (count): Total > Male > 45 to 54 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M020`	string		Margin of error (90% confidence) for the paired B27001_E020 estimate.
`B27001_E021`	string		ACS estimate (count): Total > Male > 55 to 64 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M021`	string		Margin of error (90% confidence) for the paired B27001_E021 estimate.
`B27001_E022`	string		ACS estimate (count): Total > Male > 55 to 64 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M022`	string		Margin of error (90% confidence) for the paired B27001_E022 estimate.
`B27001_E023`	string		ACS estimate (count): Total > Male > 55 to 64 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M023`	string		Margin of error (90% confidence) for the paired B27001_E023 estimate.
`B27001_E024`	string		ACS estimate (count): Total > Male > 65 to 74 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M024`	string		Margin of error (90% confidence) for the paired B27001_E024 estimate.
`B27001_E025`	string		ACS estimate (count): Total > Male > 65 to 74 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M025`	string		Margin of error (90% confidence) for the paired B27001_E025 estimate.
`B27001_E026`	string		ACS estimate (count): Total > Male > 65 to 74 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M026`	string		Margin of error (90% confidence) for the paired B27001_E026 estimate.
`B27001_E027`	string		ACS estimate (count): Total > Male > 75 years and over (Health Insurance Coverage Status by Sex by Age).
`B27001_M027`	string		Margin of error (90% confidence) for the paired B27001_E027 estimate.
`B27001_E028`	string		ACS estimate (count): Total > Male > 75 years and over > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M028`	string		Margin of error (90% confidence) for the paired B27001_E028 estimate.
`B27001_E029`	string		ACS estimate (count): Total > Male > 75 years and over > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M029`	string		Margin of error (90% confidence) for the paired B27001_E029 estimate.
`B27001_E030`	string		ACS estimate (count): Total > Female (Health Insurance Coverage Status by Sex by Age).
`B27001_M030`	string		Margin of error (90% confidence) for the paired B27001_E030 estimate.
`B27001_E031`	string		ACS estimate (count): Total > Female > Under 6 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M031`	string		Margin of error (90% confidence) for the paired B27001_E031 estimate.
`B27001_E032`	string		ACS estimate (count): Total > Female > Under 6 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M032`	string		Margin of error (90% confidence) for the paired B27001_E032 estimate.
`B27001_E033`	string		ACS estimate (count): Total > Female > Under 6 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M033`	string		Margin of error (90% confidence) for the paired B27001_E033 estimate.
`B27001_E034`	string		ACS estimate (count): Total > Female > 6 to 18 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M034`	string		Margin of error (90% confidence) for the paired B27001_E034 estimate.
`B27001_E035`	string		ACS estimate (count): Total > Female > 6 to 18 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M035`	string		Margin of error (90% confidence) for the paired B27001_E035 estimate.
`B27001_E036`	string		ACS estimate (count): Total > Female > 6 to 18 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M036`	string		Margin of error (90% confidence) for the paired B27001_E036 estimate.
`B27001_E037`	string		ACS estimate (count): Total > Female > 19 to 25 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M037`	string		Margin of error (90% confidence) for the paired B27001_E037 estimate.
`B27001_E038`	string		ACS estimate (count): Total > Female > 19 to 25 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M038`	string		Margin of error (90% confidence) for the paired B27001_E038 estimate.
`B27001_E039`	string		ACS estimate (count): Total > Female > 19 to 25 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M039`	string		Margin of error (90% confidence) for the paired B27001_E039 estimate.
`B27001_E040`	string		ACS estimate (count): Total > Female > 26 to 34 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M040`	string		Margin of error (90% confidence) for the paired B27001_E040 estimate.
`B27001_E041`	string		ACS estimate (count): Total > Female > 26 to 34 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M041`	string		Margin of error (90% confidence) for the paired B27001_E041 estimate.
`B27001_E042`	string		ACS estimate (count): Total > Female > 26 to 34 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M042`	string		Margin of error (90% confidence) for the paired B27001_E042 estimate.
`B27001_E043`	string		ACS estimate (count): Total > Female > 35 to 44 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M043`	string		Margin of error (90% confidence) for the paired B27001_E043 estimate.
`B27001_E044`	string		ACS estimate (count): Total > Female > 35 to 44 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M044`	string		Margin of error (90% confidence) for the paired B27001_E044 estimate.
`B27001_E045`	string		ACS estimate (count): Total > Female > 35 to 44 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M045`	string		Margin of error (90% confidence) for the paired B27001_E045 estimate.
`B27001_E046`	string		ACS estimate (count): Total > Female > 45 to 54 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M046`	string		Margin of error (90% confidence) for the paired B27001_E046 estimate.
`B27001_E047`	string		ACS estimate (count): Total > Female > 45 to 54 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M047`	string		Margin of error (90% confidence) for the paired B27001_E047 estimate.
`B27001_E048`	string		ACS estimate (count): Total > Female > 45 to 54 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M048`	string		Margin of error (90% confidence) for the paired B27001_E048 estimate.
`B27001_E049`	string		ACS estimate (count): Total > Female > 55 to 64 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M049`	string		Margin of error (90% confidence) for the paired B27001_E049 estimate.
`B27001_E050`	string		ACS estimate (count): Total > Female > 55 to 64 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M050`	string		Margin of error (90% confidence) for the paired B27001_E050 estimate.
`B27001_E051`	string		ACS estimate (count): Total > Female > 55 to 64 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M051`	string		Margin of error (90% confidence) for the paired B27001_E051 estimate.
`B27001_E052`	string		ACS estimate (count): Total > Female > 65 to 74 years (Health Insurance Coverage Status by Sex by Age).
`B27001_M052`	string		Margin of error (90% confidence) for the paired B27001_E052 estimate.
`B27001_E053`	string		ACS estimate (count): Total > Female > 65 to 74 years > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M053`	string		Margin of error (90% confidence) for the paired B27001_E053 estimate.
`B27001_E054`	string		ACS estimate (count): Total > Female > 65 to 74 years > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M054`	string		Margin of error (90% confidence) for the paired B27001_E054 estimate.
`B27001_E055`	string		ACS estimate (count): Total > Female > 75 years and over (Health Insurance Coverage Status by Sex by Age).
`B27001_M055`	string		Margin of error (90% confidence) for the paired B27001_E055 estimate.
`B27001_E056`	string		ACS estimate (count): Total > Female > 75 years and over > With health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M056`	string		Margin of error (90% confidence) for the paired B27001_E056 estimate.
`B27001_E057`	string		ACS estimate (count): Total > Female > 75 years and over > No health insurance coverage (Health Insurance Coverage Status by Sex by Age).
`B27001_M057`	string		Margin of error (90% confidence) for the paired B27001_E057 estimate.
`C27007_E001`	string		ACS estimate (count): Total (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M001`	string		Margin of error (90% confidence) for the paired C27007_E001 estimate.
`C27007_E002`	string		ACS estimate (count): Total > Male (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M002`	string		Margin of error (90% confidence) for the paired C27007_E002 estimate.
`C27007_E003`	string		ACS estimate (count): Total > Male > Under 19 years (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M003`	string		Margin of error (90% confidence) for the paired C27007_E003 estimate.
`C27007_E004`	string		ACS estimate (count): Total > Male > Under 19 years > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M004`	string		Margin of error (90% confidence) for the paired C27007_E004 estimate.
`C27007_E005`	string		ACS estimate (count): Total > Male > Under 19 years > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M005`	string		Margin of error (90% confidence) for the paired C27007_E005 estimate.
`C27007_E006`	string		ACS estimate (count): Total > Male > 19 to 64 years (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M006`	string		Margin of error (90% confidence) for the paired C27007_E006 estimate.
`C27007_E007`	string		ACS estimate (count): Total > Male > 19 to 64 years > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M007`	string		Margin of error (90% confidence) for the paired C27007_E007 estimate.
`C27007_E008`	string		ACS estimate (count): Total > Male > 19 to 64 years > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M008`	string		Margin of error (90% confidence) for the paired C27007_E008 estimate.
`C27007_E009`	string		ACS estimate (count): Total > Male > 65 years and over (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M009`	string		Margin of error (90% confidence) for the paired C27007_E009 estimate.
`C27007_E010`	string		ACS estimate (count): Total > Male > 65 years and over > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M010`	string		Margin of error (90% confidence) for the paired C27007_E010 estimate.
`C27007_E011`	string		ACS estimate (count): Total > Male > 65 years and over > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M011`	string		Margin of error (90% confidence) for the paired C27007_E011 estimate.
`C27007_E012`	string		ACS estimate (count): Total > Female (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M012`	string		Margin of error (90% confidence) for the paired C27007_E012 estimate.
`C27007_E013`	string		ACS estimate (count): Total > Female > Under 19 years (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M013`	string		Margin of error (90% confidence) for the paired C27007_E013 estimate.
`C27007_E014`	string		ACS estimate (count): Total > Female > Under 19 years > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M014`	string		Margin of error (90% confidence) for the paired C27007_E014 estimate.
`C27007_E015`	string		ACS estimate (count): Total > Female > Under 19 years > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M015`	string		Margin of error (90% confidence) for the paired C27007_E015 estimate.
`C27007_E016`	string		ACS estimate (count): Total > Female > 19 to 64 years (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M016`	string		Margin of error (90% confidence) for the paired C27007_E016 estimate.
`C27007_E017`	string		ACS estimate (count): Total > Female > 19 to 64 years > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M017`	string		Margin of error (90% confidence) for the paired C27007_E017 estimate.
`C27007_E018`	string		ACS estimate (count): Total > Female > 19 to 64 years > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M018`	string		Margin of error (90% confidence) for the paired C27007_E018 estimate.
`C27007_E019`	string		ACS estimate (count): Total > Female > 65 years and over (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M019`	string		Margin of error (90% confidence) for the paired C27007_E019 estimate.
`C27007_E020`	string		ACS estimate (count): Total > Female > 65 years and over > With Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M020`	string		Margin of error (90% confidence) for the paired C27007_E020 estimate.
`C27007_E021`	string		ACS estimate (count): Total > Female > 65 years and over > No Medicaid/means-tested public coverage (Medicaid/Means-Tested Public Coverage by Sex by Age).
`C27007_M021`	string		Margin of error (90% confidence) for the paired C27007_E021 estimate.

`raw.airtoxscreen__tract_risk`

EPA AirToxScreen 2018/2019 assessment, by-source-group cancer risk file (‘…CancerRisk_by_tract_srcgrp.xlsx’), landed verbatim and whole per assessment_year. Carries national, state, county AND census-tract rows (module docstring); measure.observation derives only the real tract rows. Public domain (17 U.S.C. Sec 105; https://edg.epa.gov/epa_data_license.html).

Sorted by: assessment_year, fips, tract

Column	Type	Required	Doc
`state`	string		USPS 2-letter state abbreviation, as published (also “US” for the one national-total row).
`epa_region`	string		EPA region name (e.g. ‘EPA Region 4’), or ‘Entire US’ on the national row.
`county`	string		County name, or ‘Entire State’/‘Entire US’ on the state/national aggregate rows.
`fips`	string		5-digit county FIPS code (state rows: state FIPS + “000”; the national row: “00000”).
`tract`	string		11-digit tract FIPS code for a real tract row; the county’s own code + “000000” for a county-aggregate row, or “00000000000”/state-FIPS+“000000000” for the national/state rows (module docstring: derive uses only real tract rows, `tract NOT LIKE '%000000'`).
`population`	string		Resident population the estimate covers, as published.
`total_cancer_risk`	string		Total modeled lifetime cancer risk from ambient air toxics (all source groups, all pollutants combined), chances per million, as published under the header ‘Total Cancer Risk (per million)’. Published rounded to a small set of risk bins (5, 6, 7, 8, 9, 10, 20, 30, …, 100, 200, 300, 400 – verified against the real file), not a continuous value; that rounding is EPA’s own publication convention, not a landing defect. Identical between raw.airtoxscreen__tract_risk and raw.airtoxscreen__tract_risk_pollutant for the same (fips, tract) (verified 2026-09-19).
`pt_stationarypoint`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘PT-StationaryPoint’ source-group category, a point (stationary facility) source. EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`or_lightduty_offnetwork_gas`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘OR-LightDuty-OffNetwork-Gas’ source-group category, an onroad mobile source (motor vehicles on public roads). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`or_lightduty_offnetwork_diesel`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘OR-LightDuty-OffNetwork-Diesel’ source-group category, an onroad mobile source (motor vehicles on public roads). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`or_heavyduty_offnetwork_gas`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘OR-HeavyDuty-OffNetwork-Gas’ source-group category, an onroad mobile source (motor vehicles on public roads). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`or_heavyduty_offnetwork_diesel`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘OR-HeavyDuty-OffNetwork-Diesel’ source-group category, an onroad mobile source (motor vehicles on public roads). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`or_lightduty_onnetwork_gas`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘OR-LightDuty-OnNetwork-Gas’ source-group category, an onroad mobile source (motor vehicles on public roads). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`or_lightduty_onnetwork_diesel`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘OR-LightDuty-OnNetwork-Diesel’ source-group category, an onroad mobile source (motor vehicles on public roads). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`or_heavyduty_onnetwork_gas`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘OR-HeavyDuty-OnNetwork-Gas’ source-group category, an onroad mobile source (motor vehicles on public roads). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`or_heavyduty_onnetwork_diesel`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘OR-HeavyDuty-OnNetwork-Diesel’ source-group category, an onroad mobile source (motor vehicles on public roads). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`or_refueling`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘OR-Refueling’ source-group category, an onroad mobile source (motor vehicles on public roads). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`or_heavyduty_hoteling`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘OR-HeavyDuty-Hoteling’ source-group category, an onroad mobile source (motor vehicles on public roads). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_recreational_inc_pleasurecraft`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-Recreational-inc-PleasureCraft’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_construction`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-Construction’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_commerciallawngarden`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-CommercialLawnGarden’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_residentiallawngarden`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-ResidentialLawnGarden’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_agriculture`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-Agriculture’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_commercialequipment`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-CommercialEquipment’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_allother`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-AllOther’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_cmv_c1c2_ports`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-CMV_C1C2_ports’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_cmv_c3_ports`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-CMV_C3_ports’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_cmv_c1c2c3_underway`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-CMV_C1C2C3_underway’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_locomotives`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-Locomotives’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_point_airports`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR-Point-Airports’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`nr_point_railyards`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NR- Point-Railyards’ source-group category, a nonroad mobile source (e.g. construction/farm equipment, marine vessels, aircraft, locomotives). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`np_industrial`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NP-industrial’ source-group category, a nonpoint (area) source (small, diffuse sources such as consumer products, small facilities and combustion not individually inventoried). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`np_commercialcooking`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NP-CommercialCooking’ source-group category, a nonpoint (area) source (small, diffuse sources such as consumer products, small facilities and combustion not individually inventoried). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`np_oilgas`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NP-OilGas’ source-group category, a nonpoint (area) source (small, diffuse sources such as consumer products, small facilities and combustion not individually inventoried). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`np_solventscoatings`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NP-SolventsCoatings’ source-group category, a nonpoint (area) source (small, diffuse sources such as consumer products, small facilities and combustion not individually inventoried). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`np_storagetransfer_bulkterminals_gasstage1`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NP-StorageTransfer_BulkTerminals_GasStage1’ source-group category, a nonpoint (area) source (small, diffuse sources such as consumer products, small facilities and combustion not individually inventoried). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`np_miscellaneousnonindustrial`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NP-MiscellaneousNonindustrial’ source-group category, a nonpoint (area) source (small, diffuse sources such as consumer products, small facilities and combustion not individually inventoried). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`np_fuelcombustion_not_rwc`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NP-FuelCombustion_not_RWC’ source-group category, a nonpoint (area) source (small, diffuse sources such as consumer products, small facilities and combustion not individually inventoried). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`np_residentialwoodcombustionrwc`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NP-ResidentialWoodCombustionRWC’ source-group category, a nonpoint (area) source (small, diffuse sources such as consumer products, small facilities and combustion not individually inventoried). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`np_wastedisposal`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NP-WasteDisposal’ source-group category, a nonpoint (area) source (small, diffuse sources such as consumer products, small facilities and combustion not individually inventoried). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`np_agriculturelivestock`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘NP-AgricultureLivestock’ source-group category, a nonpoint (area) source (small, diffuse sources such as consumer products, small facilities and combustion not individually inventoried). EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`fire`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘FIRE’ source-group category. EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`biogenics`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘BIOGENICS’ source-group category. EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`secondary`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘SECONDARY’ source-group category. EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`background`	string		Modeled lifetime cancer risk (chances per million) attributable to the ‘BACKGROUND’ source-group category. EPA’s own AirToxScreen source-group taxonomy; see the technical support document (epa.gov/AirToxScreen/airtoxscreen-technical-support-document) for this category’s exact definition. Not derived into measure.observation (module docstring: only the total and three named pollutants are).
`assessment_year`	string	yes	The AirToxScreen assessment year (‘2018’ or ‘2019’ – the only years this module lands; see module docstring), the raw overwrite-scope column and source_release downstream.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.airtoxscreen__tract_risk_pollutant`

EPA AirToxScreen 2018/2019 assessment, by-pollutant cancer risk file (‘…CancerRisk_by_tract_poll.xlsx’), landed verbatim and whole per assessment_year. Same row shape as raw.airtoxscreen__tract_risk (module docstring); only benzene, formaldehyde and ethylene_oxide are derived. Public domain (17 U.S.C. Sec 105; https://edg.epa.gov/epa_data_license.html).

Sorted by: assessment_year, fips, tract

Column	Type	Required	Doc
`state`	string		USPS 2-letter state abbreviation, as published (also “US” for the one national-total row).
`epa_region`	string		EPA region name (e.g. ‘EPA Region 4’), or ‘Entire US’ on the national row.
`county`	string		County name, or ‘Entire State’/‘Entire US’ on the state/national aggregate rows.
`fips`	string		5-digit county FIPS code (state rows: state FIPS + “000”; the national row: “00000”).
`tract`	string		11-digit tract FIPS code for a real tract row; the county’s own code + “000000” for a county-aggregate row, or “00000000000”/state-FIPS+“000000000” for the national/state rows (module docstring: derive uses only real tract rows, `tract NOT LIKE '%000000'`).
`population`	string		Resident population the estimate covers, as published.
`total_cancer_risk`	string		Total modeled lifetime cancer risk from ambient air toxics (all source groups, all pollutants combined), chances per million, as published under the header ‘Total Cancer Risk (per million)’. Published rounded to a small set of risk bins (5, 6, 7, 8, 9, 10, 20, 30, …, 100, 200, 300, 400 – verified against the real file), not a continuous value; that rounding is EPA’s own publication convention, not a landing defect. Identical between raw.airtoxscreen__tract_risk and raw.airtoxscreen__tract_risk_pollutant for the same (fips, tract) (verified 2026-09-19).
`1_1_2_trichloroethane`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘1,1,2-TRICHLOROETHANE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`1_2_dibromo_3_chloropropane`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘1,2-DIBROMO-3-CHLOROPROPANE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`1_2_diphenylhydrazine`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘1,2-DIPHENYLHYDRAZINE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`1_2_3_4_5_6_hexachlorocyclyhexane`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘1,2,3,4,5,6-HEXACHLOROCYCLYHEXANE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`1_3_butadiene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘1,3-BUTADIENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`1_3_dichloropropene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘1,3-DICHLOROPROPENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`1_3_propane_sultone`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘1,3-PROPANE SULTONE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`1_4_dichlorobenzene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘1,4-DICHLOROBENZENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`2_acetylaminofluorene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘2-ACETYLAMINOFLUORENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`2_nitropropane`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘2-NITROPROPANE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`2_4_dinitrotoluene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘2,4-DINITROTOLUENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`2_4_toluene_diisocyanate`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘2,4-TOLUENE DIISOCYANATE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`2_4_6_trichlorophenol`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘2,4,6-TRICHLOROPHENOL’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`3_3_dichlorobenzidine`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘3,3’-DICHLOROBENZIDINE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`4_dimethylaminoazobenzene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘4-DIMETHYLAMINOAZOBENZENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`4_4_methylene_bis_2_chloroaniline`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘4,4’-METHYLENE BIS(2-CHLOROANILINE)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`4_4_methylenedianiline`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘4,4’-METHYLENEDIANILINE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`acetaldehyde`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ACETALDEHYDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`acetamide`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ACETAMIDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`acrylamide`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ACRYLAMIDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`acrylonitrile`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ACRYLONITRILE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`allyl_chloride`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ALLYL CHLORIDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`aniline`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ANILINE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`arsenic_compounds_inorganic_including_arsine`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ARSENIC COMPOUNDS(INORGANIC INCLUDING ARSINE)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`benzoapyrene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘BENZOAPYRENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`benzene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘BENZENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`benzidine`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘BENZIDINE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`benzyl_chloride`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘BENZYL CHLORIDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`beryllium_compounds`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘BERYLLIUM COMPOUNDS’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`bis_2_ethylhexyl_phthalate_dehp`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘BIS(2-ETHYLHEXYL)PHTHALATE (DEHP)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`bis_chloromethyl_ether`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘BIS(CHLOROMETHYL) ETHER’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`bromoform`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘BROMOFORM’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`chromium_vi_hexavalent`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘CHROMIUM VI (HEXAVALENT)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`cadmium_compounds`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘CADMIUM COMPOUNDS’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`carbon_tetrachloride`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘CARBON TETRACHLORIDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`chlordane`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘CHLORDANE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`chlorobenzilate`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘CHLOROBENZILATE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`chloroprene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘CHLOROPRENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`coke_oven_emissions`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘COKE OVEN EMISSIONS’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`dichloroethyl_ether_bis_2_chloroethyl_ether`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘DICHLOROETHYL ETHER (BIS[2-CHLOROETHYL]ETHER)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`epichlorohydrin`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘EPICHLOROHYDRIN’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`ethylbenzene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ETHYLBENZENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`ethyl_carbamate_urethane_chloride_chloroethane`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ETHYL CARBAMATE (URETHANE) CHLORIDE (CHLOROETHANE)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`ethylene_dibromide_dibromoethane`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ETHYLENE DIBROMIDE (DIBROMOETHANE)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`ethylene_dichloride_1_2_dichloroethane`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ETHYLENE DICHLORIDE (1,2-DICHLOROETHANE)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`ethylene_oxide`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ETHYLENE OXIDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`ethylene_thiourea`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ETHYLENE THIOUREA’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`ethylidene_dichloride_1_1_dichloroethane`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘ETHYLIDENE DICHLORIDE (1,1-DICHLOROETHANE)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`formaldehyde`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘FORMALDEHYDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`heptachlor`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘HEPTACHLOR’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`hexachlorobenzene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘HEXACHLOROBENZENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`hexachlorobutadiene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘HEXACHLOROBUTADIENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`hydrazine`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘HYDRAZINE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`methyl_tert_butyl_ether`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘METHYL TERT-BUTYL ETHER’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`methylene_chloride`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘METHYLENE CHLORIDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`n_nitrosodimethylamine`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘N-NITROSODIMETHYLAMINE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`n_nitrosomorpholine`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘N-NITROSOMORPHOLINE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`nickel_compounds`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘NICKEL COMPOUNDS’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`naphthalene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘NAPHTHALENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`nitrobenzene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘NITROBENZENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`polychlorinated_biphenyls_aroclors`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘POLYCHLORINATED BIPHENYLS (AROCLORS)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`pentachlorophenol`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘PENTACHLOROPHENOL’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`propylene_oxide`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘PROPYLENE OXIDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`tetrachloroethylene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘TETRACHLOROETHYLENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`2_4_toluene_diamine`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘2,4-TOLUENE DIAMINE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`toxaphene_chlorinated_camphene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘TOXAPHENE (CHLORINATED CAMPHENE)’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`trichloroethylene`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘TRICHLOROETHYLENE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`vinyl_bromide`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘VINYL BROMIDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`vinyl_chloride`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘VINYL CHLORIDE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`o_toluidine`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘O-TOLUIDINE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`1_4_dioxane`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘1,4-DIOXANE’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`pahpom`	string		Modeled lifetime cancer risk (chances per million) attributable to ambient ‘PAHPOM’, one of the hazardous air pollutants EPA’s AirToxScreen assesses; see the technical support document for the toxicity value used. Not derived into measure.observation unless it is one of the three named pollutants (benzene, formaldehyde, ethylene oxide – module docstring).
`assessment_year`	string	yes	The AirToxScreen assessment year (‘2018’ or ‘2019’ – the only years this module lands; see module docstring), the raw overwrite-scope column and source_release downstream.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.bls__laus_area`

BLS LAUS area code lookup (la.area), landed verbatim and whole per vintage.

Sorted by: laus_vintage, area_type_code, area_code

Column	Type	Required	Doc
`area_type_code`	string	yes	BLS area classification letter. ‘F’ is county/county-equivalent – the only level this module derives from; other codes (state, metropolitan area, balance-of-state, etc.) are landed for reference but not used.
`area_code`	string	yes	‘CN’ + 2-digit state FIPS + 3-digit county FIPS + 8 zeros for a county-equivalent area, e.g. ‘CN0100100000000’ (Autauga County, AL).
`area_text`	string	yes	Human-readable area name.
`display_level`	string		BLS display grouping, as published.
`selectable`	string		‘T’/‘F’, as published.
`sort_sequence`	string		BLS display sort order, as published.
`laus_vintage`	string	yes	See raw.bls__laus_county.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.bls__laus_county`

BLS LAUS county-level (area_type_code=‘F’) monthly + annual-average data, landed verbatim and whole from la.data.64.County. Public domain (BLS is a federal agency).

Sorted by: laus_vintage, series_id, year, period

Column	Type	Required	Doc
`series_id`	string	yes	BLS series id, ‘LAUCN<5-digit FIPS>00000000’ – e.g. ‘LAUCN010010000000003’ is Autauga County AL (01001), measure 03. Every row of this file carries the ‘LAUCN’ county prefix (verified against the full real file, 3,225 areas).
`year`	string	yes	4-digit calendar year.
`period`	string	yes	‘M01’-‘M12’ for a calendar month, ‘M13’ for the annual average (la.period, landed in raw.bls__laus_measure’s sibling la.period is not landed separately – its 13 values are exactly M01-M13, not worth a lookup table of its own).
`value`	string		The published value, unparsed. A literal ‘-’ means not available (footnote_codes explains why); never silently cast to a number.
`footnote_codes`	string		FK to raw.bls__laus_footnote.footnote_code; NULL when the value carries no footnote.
`laus_vintage`	string	yes	Retrieval-date vintage (SPEC.md’s versioning model: BLS revises prior months in place, so the flat file’s version axis is when it was retrieved, not a label BLS publishes). Raw is replaced wholesale per value of this column; several retrievals with identical bytes are one vintage (bls_laus.py skips landing a repeat).
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.bls__laus_footnote`

BLS LAUS footnote code lookup (la.footnote), landed verbatim and whole per vintage – the real, complete set of sentinel/reliability codes this source publishes (bls_laus.py’s FOOTNOTE_TEXT mirrors it and SystemExits on a code not in this table).

Sorted by: laus_vintage, footnote_code

Column	Type	Required	Doc
`footnote_code`	string	yes	Single-letter footnote code, e.g. ‘N’ = not available.
`footnote_text`	string	yes	Footnote text, as published.
`laus_vintage`	string	yes	See raw.bls__laus_county.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.bls__laus_measure`

BLS LAUS measure code lookup (la.measure), landed verbatim and whole per vintage.

Sorted by: laus_vintage, measure_code

Column	Type	Required	Doc
`measure_code`	string	yes	2-digit measure code, e.g. ‘03’ = unemployment rate.
`measure_text`	string	yes	Human-readable measure name.
`laus_vintage`	string	yes	See raw.bls__laus_county.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.bls__laus_series`

BLS LAUS series identification lookup (la.series), landed verbatim and whole per vintage. Not read by this module’s derive step – the county data file’s own series_id already encodes area + measure (raw.bls__laus_county’s doc) – landed for reference and for a future series-title/date-range lookup need.

Sorted by: laus_vintage, series_id

Column	Type	Required	Doc
`series_id`	string	yes	See raw.bls__laus_county.
`area_type_code`	string	yes	See raw.bls__laus_area.
`area_code`	string	yes	FK raw.bls__laus_area.
`measure_code`	string	yes	FK raw.bls__laus_measure.
`seasonal`	string	yes	‘S’ seasonally adjusted, ‘U’ not. Every county-level series is ‘U’ (verified against the full real file) – LAUS publishes no seasonally-adjusted county series.
`srd_code`	string		BLS state/regional division code, as published.
`series_title`	string	yes	Human-readable series title.
`footnote_codes`	string		Footnote(s) on the series overall, if any.
`begin_year`	string		First year this series has data.
`begin_period`	string		First period this series has data.
`end_year`	string		Last year this series has data, as of this vintage.
`end_period`	string		Last period this series has data, as of this vintage.
`laus_vintage`	string	yes	See raw.bls__laus_county.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.canceronice__cancer_site_group`

Curated CSV of cancer-site groupings (data/cancer_site_groups.csv, committed in the package – this project’s own compilation of CDC/USPSTF/NCI/Surgeon General citations, like raw.geography__county_recodes), landed verbatim and whole. Replaced wholesale each time it is re-curated – there is no upstream edition to key an overwrite scope on.

Sorted by: group_id, cancer_site_code

Column	Type	Required	Doc
`group_id`	string	yes	Snake_case grouping id, e.g. ‘tobacco_associated’, exactly as curated (see data/cancer_site_groups.csv).
`group_label`	string	yes	Human-readable label for the grouping, as curated.
`cancer_site_code`	string	yes	A measure.cancer_site.cancer_site_code this grouping includes.
`mapping_relation`	string	yes	‘exact’ \| ‘broader’ – same vocabulary as measure.cancer_site’s column of the same name (#90): whether this cancer_site_code is exactly what the citation names, or a broader SEER code standing in for a histology/subsite the citation names more narrowly (e.g. HPV-associated oropharynx) or a narrower one the citation names more broadly (e.g. a single subsite folded under a citation that names the whole combined category).
`basis`	string	yes	The citation: publisher, page title, checked/updated date, and the verbatim sentence establishing this (group, cancer_site_code) membership. One citation per row (SPEC.md § Licence gate discipline applied to grouping membership, not just ingest) – never from memory.
`source_url`	string	yes	URL of the page `basis` quotes.
`note`	string		Caveats a plain (group_id, cancer_site_code, mapping_relation) row can’t carry: why a mapping is ‘broader’, evidence-strength language the citation itself uses (e.g. CDC’s ‘some studies indicate’ versus its core causal list), or where another authority’s evidence grading differs. NULL where there is nothing to add.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.census__gazetteer_cd`

Census Gazetteer congressional-district (CD) file landed verbatim and whole, one row per district per vintage year (SPEC.md § Geography; #104). No NAME column (census_gazetteer.transform synthesizes one). Licence: U.S. government work, public domain (17 U.S.C. § 105).

Sorted by: gazetteer_year, geoid

Column	Type	Required	Doc
`usps`	string		Two-letter USPS state/territory abbreviation.
`geoid`	string	yes	4-digit state+district FIPS-style code, e.g. ‘0101’ (Alabama’s 1st). The last two digits are ‘00’ for an at-large (single-district) state. Unique per row within one gazetteer_year.
`geoidfq`	string		Fully qualified GEOID used to join data.census.gov tables. Only present from the 2025 gazetteer layout; NULL in earlier vintages.
`aland`	string		Land area, square meters, as published.
`awater`	string		Water area, square meters, as published.
`aland_sqmi`	string		Land area, square miles, as published.
`awater_sqmi`	string		Water area, square miles, as published.
`intptlat`	string		Internal point latitude, as published.
`intptlong`	string		Internal point longitude, as published.
`gazetteer_year`	int	yes	The gazetteer vintage year this row was published under. Census labels the underlying CD file with the Congress number that vintage serves (census_gazetteer.CD_CONGRESS), not this year — this column is geography.unit’s boundary vintage, kept parallel to every other level. Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.census__gazetteer_counties`

Census Gazetteer county file landed verbatim and whole, every column, one row per county-equivalent per vintage year. Three real upstream layouts (2010 with POP10/HU10, 2011-2024 without them, 2025+ with GEOIDFQ and a pipe delimiter) land into this one union schema; absent columns are NULL. Licence: U.S. government work, public domain (17 U.S.C. § 105).

Sorted by: gazetteer_year, geoid

Column	Type	Required	Doc
`usps`	string		Two-letter USPS state/territory abbreviation.
`geoid`	string	yes	5-digit state+county FIPS code, e.g. ‘08031’. Unique per row within one gazetteer_year.
`geoidfq`	string		Fully qualified GEOID used to join data.census.gov tables, e.g. ‘0500000US08031’. Only present from the 2025 gazetteer layout; NULL in earlier vintages.
`ansicode`	string		ANSI feature code for the unit.
`name`	string		County (or state-equivalent) name.
`pop10`	string		2010 Census population count. Only the 2010 gazetteer layout carries this column; NULL in every other vintage.
`hu10`	string		2010 Census housing unit count. Only the 2010 gazetteer layout carries this column; NULL in every other vintage.
`aland`	string		Land area, square meters, as published.
`awater`	string		Water area, square meters, as published.
`aland_sqmi`	string		Land area, square miles, as published.
`awater_sqmi`	string		Water area, square miles, as published.
`intptlat`	string		Internal point latitude, as published.
`intptlong`	string		Internal point longitude, as published.
`gazetteer_year`	int	yes	The gazetteer vintage year this row was published under, e.g. 2024. Version column: raw is replaced wholesale per value of this column, so every landed vintage accumulates rather than overwrites the last.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.census__gazetteer_sldl`

Census Gazetteer state-legislative lower-chamber (SLDL) file landed verbatim and whole, one row per district per vintage year (SPEC.md § Geography; #104). Licence: U.S. government work, public domain (17 U.S.C. § 105).

Sorted by: gazetteer_year, geoid

Column	Type	Required	Doc
`usps`	string		Two-letter USPS state/territory abbreviation.
`geoid`	string	yes	5-digit state+district code, e.g. ‘01001’ (Alabama House District 1). Unique per row within one gazetteer_year.
`geoidfq`	string		Fully qualified GEOID used to join data.census.gov tables. Only present from the 2025 gazetteer layout; NULL in earlier vintages.
`name`	string		District name, as published, e.g. ‘State House District 1’.
`aland`	string		Land area, square meters, as published.
`awater`	string		Water area, square meters, as published.
`aland_sqmi`	string		Land area, square miles, as published.
`awater_sqmi`	string		Water area, square miles, as published.
`intptlat`	string		Internal point latitude, as published.
`intptlong`	string		Internal point longitude, as published.
`gazetteer_year`	int	yes	The gazetteer vintage year this row was published under. Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.census__gazetteer_sldu`

Census Gazetteer state-legislative upper-chamber (SLDU) file landed verbatim and whole, one row per district per vintage year (SPEC.md § Geography; #104). Licence: U.S. government work, public domain (17 U.S.C. § 105).

Sorted by: gazetteer_year, geoid

Column	Type	Required	Doc
`usps`	string		Two-letter USPS state/territory abbreviation.
`geoid`	string	yes	5-digit state+district code, e.g. ‘01001’ (Alabama Senate District 1). Unique per row within one gazetteer_year.
`geoidfq`	string		Fully qualified GEOID used to join data.census.gov tables. Only present from the 2025 gazetteer layout; NULL in earlier vintages.
`name`	string		District name, as published, e.g. ‘State Senate District 1’.
`aland`	string		Land area, square meters, as published.
`awater`	string		Water area, square meters, as published.
`aland_sqmi`	string		Land area, square miles, as published.
`awater_sqmi`	string		Water area, square miles, as published.
`intptlat`	string		Internal point latitude, as published.
`intptlong`	string		Internal point longitude, as published.
`gazetteer_year`	int	yes	The gazetteer vintage year this row was published under. Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.census__gazetteer_tracts`

Census Gazetteer tract file landed verbatim and whole, every column, one row per census tract per vintage year. The tract file carries no NAME column — tracts are numbered, not named. Three real upstream layouts, same union-schema treatment as raw.census__gazetteer_counties. Licence: U.S. government work, public domain (17 U.S.C. § 105).

Sorted by: gazetteer_year, geoid

Column	Type	Required	Doc
`usps`	string		Two-letter USPS state/territory abbreviation.
`geoid`	string	yes	11-digit state+county+tract FIPS code, e.g. ‘08031000100’. Unique per row within one gazetteer_year.
`geoidfq`	string		Fully qualified GEOID used to join data.census.gov tables, e.g. ‘1400000US08031000100’. Only present from the 2025 gazetteer layout; NULL in earlier vintages.
`pop10`	string		2010 Census population count. Only the 2010 gazetteer layout carries this column; NULL in every other vintage.
`hu10`	string		2010 Census housing unit count. Only the 2010 gazetteer layout carries this column; NULL in every other vintage.
`aland`	string		Land area, square meters, as published.
`awater`	string		Water area, square meters, as published.
`aland_sqmi`	string		Land area, square miles, as published.
`awater_sqmi`	string		Water area, square miles, as published.
`intptlat`	string		Internal point latitude, as published.
`intptlong`	string		Internal point longitude, as published.
`gazetteer_year`	int	yes	The gazetteer vintage year this row was published under, e.g. 2024. Version column: raw is replaced wholesale per value of this column, so every landed vintage accumulates rather than overwrites the last.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.census__state_fips`

Census’s state/state-equivalent FIPS code reference (https://www2.census.gov/geo/docs/reference/state.txt), landed whole and replaced wholesale each time — not versioned by gazetteer year, since FIPS-to-state assignment doesn’t move on that cadence. Feeds geography.unit’s state-level names. Licence: U.S. government work, public domain (17 U.S.C. § 105).

Sorted by: state

Column	Type	Required	Doc
`state`	string	yes	2-digit state/territory FIPS code, e.g. ‘09’.
`stusab`	string		Two-letter USPS abbreviation, e.g. ‘CT’.
`state_name`	string		Full state/territory name, e.g. ‘Connecticut’.
`statens`	string		GNIS ANSI feature code for the state.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.ejscreen__blockgroup`

EPA EJScreen block group file, landed verbatim and whole per edition (SPEC.md Sources: ‘land every published edition’). CC-BY-4.0 (Zenodo doi:10.5281/zenodo.14767363) over U.S. Government (EPA) geospatial data, public domain by default (17 U.S.C. Sec 105).

Sorted by: ejscreen_edition, geo_id

Column	Type	Required	Doc
`geo_id`	string	yes	Block group GEOID as published (12-digit numeric string, e.g. ‘010010201001’). NOT yet a geography.unit FK – census_gazetteer.py lands county/tract only, no block_group level (ejscreen.py module docstring); Iceberg enforces no FK either way.
`pm25`	string		PM2.5 concentration (annual mean), modeled, unparsed as published.
`ozone`	string		Ozone concentration (seasonal average), modeled, unparsed as published.
`dslpm`	string		Diesel particulate matter concentration, modeled (NATA), unparsed as published.
`cancer`	string		Air toxics cancer risk, modeled (NATA), unparsed as published. Not published from the 2024 edition onward (replaced by rsei_air) – NULL there.
`resp`	string		Air toxics respiratory hazard index, modeled (NATA), unparsed as published. Not published from the 2024 edition onward (replaced by rsei_air) – NULL there.
`rsei_air`	string		Air toxics concentration score (RSEI-based), unparsed as published. Published from the 2023 edition onward only – NULL before.
`ptraf`	string		Traffic proximity and volume near major roads, unparsed as published.
`pre1960pct`	string		Percent of housing units built before 1960 (lead-paint exposure indicator), unparsed as published.
`pnpl`	string		Proximity to National Priorities List (Superfund) sites, unparsed as published.
`prmp`	string		Proximity to Risk Management Plan (RMP) facilities, unparsed as published.
`ptsdf`	string		Proximity to hazardous waste treatment/storage/disposal facilities, unparsed as published.
`ust`	string		Proximity to leaking/underground storage tanks, unparsed as published. Published from the 2021 edition onward only – NULL before.
`pwdis`	string		Proximity-weighted modeled toxic concentration from NPDES wastewater dischargers, unparsed as published.
`no2`	string		NO2 (nitrogen dioxide) concentration, modeled, unparsed as published. Published in the 2024 edition only – NULL before.
`dwater`	string		Drinking water non-compliance indicator, unparsed as published. Published in the 2024 edition only – NULL before.
`ejscreen_edition`	string	yes	The EJScreen edition (2015-2024) – the version axis for this source. Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.
`extra_json`	string		Every other column this edition’s file publishes (demographic bases, percentile/statistical-comparison breakdown columns, geometry bookkeeping – ~130-380 columns whose exact set shifts release to release), as one JSON object per row, text-valued, verbatim – including geo_id and the columns broken out above. Same ‘declared columns for what’s used, JSON for the rest’ shape as facility.site.attributes_json (ejscreen.py module docstring).

`raw.ejscreen__tract`

EPA EJScreen tract file, landed verbatim and whole per edition (2021-2024 only – EPA’s own separate tract product, not a block-group aggregation this module computes). Same licence as raw.ejscreen__blockgroup. The only level derived into measure.observation today (ejscreen.py module docstring).

Sorted by: ejscreen_edition, geo_id

Column	Type	Required	Doc
`geo_id`	string	yes	Tract GEOID as published (11-digit numeric string, e.g. ‘01001020100’). FK geography.unit (census_gazetteer.py lands tract), together with the edition’s GEO_VINTAGE.
`pm25`	string		See raw.ejscreen__blockgroup.
`ozone`	string		See raw.ejscreen__blockgroup.
`dslpm`	string		See raw.ejscreen__blockgroup.
`cancer`	string		See raw.ejscreen__blockgroup.
`resp`	string		See raw.ejscreen__blockgroup.
`rsei_air`	string		See raw.ejscreen__blockgroup.
`ptraf`	string		See raw.ejscreen__blockgroup.
`pre1960pct`	string		See raw.ejscreen__blockgroup.
`pnpl`	string		See raw.ejscreen__blockgroup.
`prmp`	string		See raw.ejscreen__blockgroup.
`ptsdf`	string		See raw.ejscreen__blockgroup.
`ust`	string		See raw.ejscreen__blockgroup.
`pwdis`	string		See raw.ejscreen__blockgroup.
`no2`	string		See raw.ejscreen__blockgroup.
`dwater`	string		See raw.ejscreen__blockgroup.
`ejscreen_edition`	string	yes	See raw.ejscreen__blockgroup. Only landed for editions 2021-2024 – EPA published no separate tract file before.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.
`extra_json`	string		See raw.ejscreen__blockgroup.

`raw.epa__radon_zones`

EPA Map of Radon Zones, county-level predicted indoor radon screening zone (SPEC.md #101), landed verbatim and whole from both of the source spreadsheet’s data sheets. Single, ever-only 1993 edition (developed by EPA + USGS; the file itself is periodically corrected for administrative geography, not re-assessed), so raw is replaced wholesale each time, like raw.geography__county_recodes. Public domain (U.S. Government work, 17 U.S.C. Sec 105).

Sorted by: state, county_state

Column	Type	Required	Doc
`county_state`	string	yes	‘County,State’ column as published, e.g. ‘Autauga, AL’ – a state-summary row (e.g. ‘ALABAMA’) or a blank trailer row is never landed (radon.py module docstring: neither carries a real Zone value, so neither is a county-or-equivalent row).
`county_label`	string	yes	‘COUNTY LABEL’ column as published, e.g. ‘.Autauga County’ – the leading period is the source’s own row-type marker for a real county-level row. Virginia’s independent cities carry no leading period; see the ‘state’ column doc.
`state`	string	yes	‘STATE’ column as published: the full state name (e.g. ‘Alabama’) for almost every row, or the literal ‘VA-CITY’ marker the source uses instead of ‘Virginia’ on its 41 Virginia independent-city rows (radon.py module docstring).
`zone_unfiltered`	double		EPA Radon Zone (1-3) from the file’s ‘un-filtered-raw-data’ sheet. Differs from zone_filtered for 9 of 3,144 counties (radon.py module docstring lists them); not itself derived into any measure.
`zone_filtered`	double	yes	EPA Radon Zone (1-3) from the file’s ‘filtered-raw data’ sheet – the version measure.observation is derived from (radon.py module docstring on why ‘filtered’ was chosen).
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.epa__tri_basic`

EPA TRI Basic Data Files, landed verbatim and whole, one national file per reporting year, replaced wholesale per value of YEAR (SPEC.md § Sources – second tranche). Public domain (17 U.S.C. § 105; EPA_Data_License.html). No individual-contact columns exist in this file (checked against the real header across 1987-2023, see epa_tri.py’s module docstring) – every name column is a facility or company, not a person.

Sorted by: YEAR, TRIFD, CHEMICAL

Column	Type	Required	Doc
`YEAR`	string	yes	4-digit reporting year – the version axis (raw is replaced wholesale per value of this column; also measure.observation’s source_release for this source, per issue #100).
`TRIFD`	string	yes	EPA’s own stable per-facility TRI Facility ID. facility.site.facility_id.
`FRS ID`	string		EPA Facility Registry Service id, when assigned.
`FACILITY NAME`	string		Facility’s own name. facility.site.name.
`STREET ADDRESS`	string		Part of facility.site.address.
`CITY`	string		Part of facility.site.address.
`COUNTY`	string		County (or parish/municipio/borough/census area) name as EPA publishes it – no FIPS column exists in this file. Matched against geography.unit by normalised name + state to derive facility.site.geo_id / measure.observation.geo_id; see epa_tri.py’s module docstring for the match rule and its real, reported miss rate.
`ST`	string		USPS state/territory abbreviation.
`ZIP`	string		Part of facility.site.address.
`BIA`	string		Bureau of Indian Affairs reservation code, when applicable.
`TRIBE`	string		Tribal name, when BIA is populated.
`LATITUDE`	string		Unparsed; facility.site.lat (TRY_CAST to double).
`LONGITUDE`	string		Unparsed; facility.site.lon (TRY_CAST to double).
`HORIZONTAL DATUM`	string		Geodetic datum of LATITUDE/LONGITUDE, as published.
`PARENT CO NAME`	string		Parent company’s own name, as self-reported. An organisation, not an individual (verified against the real header and EPA’s field definitions 2026-09-19 – see module docstring).
`PARENT CO DB NUM`	string		Parent company D&B number, when reported.
`STANDARD PARENT CO NAME`	string		EPA-standardised form of PARENT CO NAME.
`FOREIGN PARENT CO NAME`	string		Foreign parent company name, when applicable.
`FOREIGN PARENT CO DB NUM`	string		Foreign parent company D&B number, when reported.
`STANDARD FOREIGN PARENT CO NAME`	string		EPA-standardised form of FOREIGN PARENT CO NAME.
`FEDERAL FACILITY`	string		‘YES’/‘NO’, as published.
`INDUSTRY SECTOR CODE`	string		NAICS-sector-derived TRI industry sector code.
`INDUSTRY SECTOR`	string		TRI industry sector name.
`PRIMARY SIC`	string		Primary Standard Industrial Classification code.
`SIC 2`	string		Secondary SIC code, when reported.
`SIC 3`	string		Secondary SIC code, when reported.
`SIC 4`	string		Secondary SIC code, when reported.
`SIC 5`	string		Secondary SIC code, when reported.
`SIC 6`	string		Secondary SIC code, when reported.
`PRIMARY NAICS`	string		Primary North American Industry Classification code.
`NAICS 2`	string		Secondary NAICS code, when reported.
`NAICS 3`	string		Secondary NAICS code, when reported.
`NAICS 4`	string		Secondary NAICS code, when reported.
`NAICS 5`	string		Secondary NAICS code, when reported.
`NAICS 6`	string		Secondary NAICS code, when reported.
`DOC_CTRL_NUM`	string		EPA’s internal document control number for this submission.
`CHEMICAL`	string		Chemical or chemical-category name being reported.
`ELEMENTAL METAL INCLUDED`	string		‘YES’/‘NO’, as published.
`TRI CHEMICAL/COMPOUND ID`	string		TRI’s own chemical/compound id.
`CAS#`	string		Chemical Abstracts Service registry number, when the chemical has one.
`SRS ID`	string		EPA Substance Registry Services id.
`CLEAN AIR ACT CHEMICAL`	string		‘YES’/‘NO’, as published.
`CLASSIFICATION`	string		‘TRI’ \| ‘PBT’ \| ‘Dioxin’ – which reporting list the chemical is on. Dioxin-classified rows report in Grams (see UNIT OF MEASURE); everything else reports in Pounds (verified against the real file, every year checked).
`METAL`	string		‘YES’/‘NO’, as published.
`METAL CATEGORY`	string		Metal category name, when METAL=‘YES’.
`CARCINOGEN`	string		‘YES’/‘NO’ – TRI’s own carcinogen flag (verified: the only two real values in the live file). measure.observation’s TRI:onsite_carcinogen_release_total sums ON-SITE RELEASE TOTAL where this is ‘YES’; a republished flag, not an independent hazard assessment.
`PBT`	string		‘YES’/‘NO’ – on the Persistent Bioaccumulative Toxic chemical list.
`PFAS`	string		‘YES’/‘NO’ – on the PFAS chemical list.
`FORM TYPE`	string		‘R’ (full Form R) or ‘A’ (certification statement, filed when the facility is below the threshold that requires quantities – every real Form A row’s release/transfer columns are ‘0.000’, verified against the live file).
`UNIT OF MEASURE`	string		‘Pounds’ or ‘Grams’ – see CLASSIFICATION.
`5.1 - FUGITIVE AIR`	string		On-site fugitive/non-point air release, unparsed, in UNIT OF MEASURE.
`5.2 - STACK AIR`	string		On-site stack/point air release, unparsed.
`5.3 - WATER`	string		On-site surface water release, unparsed.
`5.4 - UNDERGROUND`	string		On-site underground injection, total, unparsed.
`5.4.1 - UNDERGROUND CL I`	string		On-site Class I underground injection, unparsed.
`5.4.2 - UNDERGROUND C II-V`	string		On-site Class II-V underground injection, unparsed.
`5.5.1 - LANDFILLS`	string		On-site landfill disposal, total, unparsed.
`5.5.1A - RCRA C LANDFILL`	string		On-site RCRA Subtitle C landfill disposal, unparsed.
`5.5.1B - OTHER LANDFILLS`	string		On-site other landfill disposal, unparsed.
`5.5.2 - LAND TREATMENT`	string		On-site land treatment/application, unparsed.
`5.5.3 - SURFACE IMPNDMNT`	string		On-site surface impoundment disposal, total, unparsed.
`5.5.3A - RCRA SURFACE IM`	string		On-site RCRA Subtitle C surface impoundment, unparsed.
`5.5.3B - OTHER SURFACE I`	string		On-site other surface impoundment, unparsed.
`5.5.4 - OTHER DISPOSAL`	string		On-site other land disposal, unparsed.
`ON-SITE RELEASE TOTAL`	string		Sum of columns 51-64 (fugitive+stack air, water, underground, land disposal), unparsed, in UNIT OF MEASURE. measure.observation’s TRI:onsite_release_total sums this per (county, year), converting Grams rows to pounds (module docstring).
`6.1 - POTW - TRNS RLSE`	string		Transferred to a POTW, released by it, unparsed.
`6.1 - POTW - TRNS TRT`	string		Transferred to a POTW, treated by it, unparsed.
`POTW - TOTAL TRANSFERS`	string		Total transferred to POTWs, unparsed.
`6.2 - M10`	string		Off-site transfer, EPA waste-management method code M10, unparsed.
`6.2 - M41`	string		Off-site transfer, method code M41, unparsed.
`6.2 - M62`	string		Off-site transfer, method code M62, unparsed.
`6.2 - M40 METAL`	string		Off-site transfer, method code M40 (metals), unparsed.
`6.2 - M61 METAL`	string		Off-site transfer, method code M61 (metals), unparsed.
`6.2 - M71`	string		Off-site transfer, method code M71, unparsed.
`6.2 - M81`	string		Off-site transfer, method code M81, unparsed.
`6.2 - M82`	string		Off-site transfer, method code M82, unparsed.
`6.2 - M72`	string		Off-site transfer, method code M72, unparsed.
`6.2 - M63`	string		Off-site transfer, method code M63, unparsed.
`6.2 - M66`	string		Off-site transfer, method code M66, unparsed.
`6.2 - M67`	string		Off-site transfer, method code M67, unparsed.
`6.2 - M64`	string		Off-site transfer, method code M64, unparsed.
`6.2 - M65`	string		Off-site transfer, method code M65, unparsed.
`6.2 - M73`	string		Off-site transfer, method code M73, unparsed.
`6.2 - M79`	string		Off-site transfer, method code M79, unparsed.
`6.2 - M90`	string		Off-site transfer, method code M90, unparsed.
`6.2 - M94`	string		Off-site transfer, method code M94, unparsed.
`6.2 - M99`	string		Off-site transfer, method code M99 (unknown/other), unparsed.
`OFF-SITE RELEASE TOTAL`	string		Sum of off-site release method columns, unparsed. Not derived here (issue #100 asks for on-site totals only).
`6.2 - M20`	string		Off-site transfer, method code M20, unparsed.
`6.2 - M24`	string		Off-site transfer, method code M24, unparsed.
`6.2 - M26`	string		Off-site transfer, method code M26, unparsed.
`6.2 - M28`	string		Off-site transfer, method code M28, unparsed.
`6.2 - M93`	string		Off-site transfer, method code M93, unparsed.
`OFF-SITE RECYCLED TOTAL`	string		Sum of off-site recycling method columns, unparsed.
`6.2 - M56`	string		Off-site transfer, method code M56, unparsed.
`6.2 - M92`	string		Off-site transfer, method code M92, unparsed.
`OFF-SITE ENERGY RECOVERY T`	string		Sum of off-site energy-recovery method columns, unparsed.
`6.2 - M40 NON-METAL`	string		Off-site transfer, method code M40 (non-metals), unparsed.
`6.2 - M50`	string		Off-site transfer, method code M50, unparsed.
`6.2 - M54`	string		Off-site transfer, method code M54, unparsed.
`6.2 - M61 NON-METAL`	string		Off-site transfer, method code M61 (non-metals), unparsed.
`6.2 - M69`	string		Off-site transfer, method code M69, unparsed.
`6.2 - M95`	string		Off-site transfer, method code M95, unparsed.
`OFF-SITE TREATED TOTAL`	string		Sum of off-site treatment method columns, unparsed.
`6.2 - UNCLASSIFIED`	string		Off-site transfer, unclassified method, unparsed.
`6.2 - TOTAL TRANSFER`	string		Sum of every off-site transfer column (89-105), unparsed.
`TOTAL RELEASES`	string		ON-SITE RELEASE TOTAL + OFF-SITE RELEASE TOTAL, unparsed.
`8.1 - RELEASES`	string		Source Reduction and Recycling Act Section 8.1 releases total, unparsed.
`8.1A - ON-SITE CONTAINED`	string		8.1 releases, on-site contained, unparsed.
`8.1B - ON-SITE OTHER`	string		8.1 releases, on-site other, unparsed.
`8.1C - OFF-SITE CONTAIN`	string		8.1 releases, off-site contained, unparsed.
`8.1D - OFF-SITE OTHER R`	string		8.1 releases, off-site other, unparsed.
`8.2 - ENERGY RECOVER ON`	string		8.2 quantity used for on-site energy recovery, unparsed.
`8.3 - ENERGY RECOVER OF`	string		8.3 quantity used for off-site energy recovery, unparsed.
`8.4 - RECYCLING ON SITE`	string		8.4 quantity recycled on-site, unparsed.
`8.5 - RECYCLING OFF SIT`	string		8.5 quantity recycled off-site, unparsed.
`8.6 - TREATMENT ON SITE`	string		8.6 quantity treated on-site, unparsed.
`8.7 - TREATMENT OFF SITE`	string		8.7 quantity treated off-site, unparsed.
`PRODUCTION WSTE (8.1-8.7)`	string		Sum of 8.1-8.7, total production-related waste, unparsed.
`8.8 - ONE-TIME RELEASE`	string		8.8 one-time/catastrophic release included above, unparsed.
`PROD_RATIO_OR_ ACTIVITY`	string		8.9’s production ratio or activity index basis, as published.
`8.9 - PRODUCTION RATIO`	string		Facility-reported production ratio vs. the prior year, unparsed.
`retrieved_on`	string	yes	ISO date this ingest fetched the file – informational (EPA’s own ‘as of’ revision note, issue #100), not the merge scope: YEAR is, since EPA revises a reporting year’s data in place with no edition label of its own (module docstring).
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.ers__food_access`

USDA ERS Food Access Research Atlas landed verbatim and whole, every published column, one row per census tract per edition (SPEC.md § Sources – first tranche). 2019 and 2015 editions only – 2010 is a real third layout and the archived 2006 Food Desert Locator is a legacy .xls (see ers_food_access.py docstring). Public domain (17 U.S.C. § 105).

Sorted by: atlas_edition, CensusTract

Column	Type	Required	Doc
`CensusTract`	string	yes	Census tract: Census tract number.
`State`	string		State: State name.
`County`	string		County: County name.
`Urban`	string		Urban tract: Flag for urban tract.
`Pop2010`	string		Population, tract total: Population count from 2010 census.
`OHU2010`	string		Housing units, total: Occupied housing unit count from 2010 census.
`GroupQuartersFlag`	string		Group quarters, tract with high share: Flag for tract where >=67%.
`NUMGQTRS`	string		Group quarters, tract population residing in, number: Count of tract population residing in group quarters.
`PCTGQTRS`	string		Group quarters, tract population residing in, share: Percent of tract population residing in group quarters.
`LILATracts_1And10`	string		Low income and low access tract measured at 1 mile for urban areas and 10 miles for rural areas: Flag for low-income and low access when considering low accessibilty at 1 and 10 miles.
`LILATracts_halfAnd10`	string		Low income and low access tract measured at 1/2 mile for urban areas and 10 miles for rural areas: Flag for low-income and low access when considering low accessibilty at 1/2 and 10 miles.
`LILATracts_1And20`	string		Low income and low access tract measured at 1 mile for urban areas and 20 miles for rural areas: Flag for low-income and low access when considering low accessibilty at 1 and 20 miles.
`LILATracts_Vehicle`	string		Low income and low access tract using vehicle access or low income and low access tract measured at 20 miles: Flag for low-income and low access when considering vehicle access or at 20 miles.
`HUNVFlag`	string		Vehicle access, tract with low vehicle access: Flag for tract where >= 100 of households do not have a vehicle, and beyond 1/2 mile from supermarket.
`LowIncomeTracts`	string		Low income tract: Flag for low income tract.
`PovertyRate`	string		Tract poverty rate: Share of the tract population living with income at or below the Federal poverty thresholds for family size.
`MedianFamilyIncome`	string		Tract median family income: Tract median family income.
`LA1and10`	string		Low access tract at 1 mile for urban areas and 10 miles for rural areas: Flag for low access tract at 1 mile for urban areas or 10 miles for rural areas.
`LAhalfand10`	string		Low access tract at 1/2 mile for urban areas and 10 miles for rural areas: Flag for low access tract at 1/2 mile for urban areas or 10 miles for rural areas.
`LA1and20`	string		Low access tract at 1 mile for urban areas and 20 miles for rural areas: Flag for low access tract at 1 mile for urban areas or 20 miles for rural areas.
`LATracts_half`	string		Low access tract at 1/2 mile: Flag for low access tract when considering 1/2 mile distance.
`LATracts1`	string		Low access tract at 1 mile: Flag for low access tract when considering 1 mile distance.
`LATracts10`	string		Low access tract at 10 miles: Flag for low access tract when considering 10 mile distance.
`LATracts20`	string		Low access tract at 20 miles: Flag for low access tract when considering 20 mile distance.
`LATractsVehicle_20`	string		Low access tract using vehicle access and at 20 miles in rural areas: Flag for tract where >= 100 of households do not have a vehicle, and beyond 1/2 mile from supermarket; or >= 500 individuals are beyond 20 miles from supermarket ; or >= 33% of individuals are beyond 20 miles from supermarket.
`LAPOP1_10`	string		Low access, population at 1 mile for urban areas and 10 miles for rural areas, number: Population count beyond 1 mile for urban areas or 10 miles for rural areas from supermarket.
`LAPOP05_10`	string		Low access, population at 1/2 mile for urban areas and 10 miles for rural areas, number: Population count beyond 1/2 mile for urban areas or 10 miles for rural areas from supermarket.
`LAPOP1_20`	string		Low access, population at 1 mile for urban areas and 20 miles for rural areas, number: Population count beyond 1 mile for urban areas or 20 miles for rural areas from supermarket.
`LALOWI1_10`	string		Low access, low-income population at 1 mile for urban areas and 10 miles for rural areas, number: Low income population count beyond 1 mile for urban areas or 10 miles for rural areas from supermarket.
`LALOWI05_10`	string		Low access, low-income population at 1/2 mile for urban areas and 10 miles for rural areas, number: Low income population count beyond 1/2 mile for urban areas or 10 miles for rural areas from supermarket.
`LALOWI1_20`	string		Low access, low-income population at 1 mile for urban areas and 20 miles for rural areas, number: Low income population count beyond 1 mile for urban areas or 20 miles for rural areas from supermarket.
`lapophalf`	string		Low access, population at 1/2 mile, number: Population count beyond 1/2 mile from supermarket.
`lapophalfshare`	string		Low access, population at 1/2 mile, share: Share of tract population that are beyond 1/2 mile from supermarket.
`lalowihalf`	string		Low access, low-income population at 1/2 mile, number: Low income population count beyond 1/2 mile from supermarket.
`lalowihalfshare`	string		Low access, low-income population at 1/2 mile, share: Share of tract population that are low income individuals beyond 1/2 mile from supermarket.
`lakidshalf`	string		Low access, children age 0-17 at 1/2 mile, number: Kids population count beyond 1/2 mile from supermarket.
`lakidshalfshare`	string		Low access, children age 0-17 at 1/2 mile, share: Share of tract population that are kids beyond 1/2 mile from supermarket.
`laseniorshalf`	string		Low access, seniors age 65+ at 1/2 mile, number: Seniors population count beyond 1/2 mile from supermarket.
`laseniorshalfshare`	string		Low access, seniors age 65+ at 1/2 mile, share: Share of tract population that are seniors beyond 1/2 mile from supermarket.
`lawhitehalf`	string		Low access, White population at 1/2 mile, number: White population count beyond 1/2 mile from supermarket.
`lawhitehalfshare`	string		Low access, White population at 1/2 mile, share: Share of tract population that are white beyond 1/2 mile from supermarket.
`lablackhalf`	string		Low access, Black or African American population at 1/2 mile, number: Black or African American population count beyond 1/2 mile from supermarket.
`lablackhalfshare`	string		Low access, Black or African American population at 1/2 mile, share: Share of tract population that are Black or African American beyond 1/2 mile from supermarket.
`laasianhalf`	string		Low access, Asian population at 1/2 mile, number: Asian population count beyond 1/2 mile from supermarket.
`laasianhalfshare`	string		Low access, Asian population at 1/2 mile, share: Share of tract population that are Asian beyond 1/2 mile from supermarket.
`lanhopihalf`	string		Low access, Native Hawaiian or Other Pacific Islander population at 1/2 mile, number: Native Hawaiian or Other Pacific Islander population count beyond 1/2 mile from supermarket.
`lanhopihalfshare`	string		Low access, Native Hawaiian or Other Pacific Islander population at 1/2 mile, share: Share of tract population that are Native Hawaiian or Other Pacific Islander beyond 1/2 mile from supermarket.
`laaianhalf`	string		Low access, American Indian or Alaska Native population at 1/2 mile, number: American Indian or Alaska Native population count beyond 1/2 mile from supermarket.
`laaianhalfshare`	string		Low access, American Indian or Alaska Native population at 1/2 mile, share: Share of tract population that are American Indian or Alaska Native beyond 1/2 mile from supermarket.
`laomultirhalf`	string		Low access, Other/Multiple race population at 1/2 mile, number: Other/Multiple race population count beyond 1/2 mile from supermarket.
`laomultirhalfshare`	string		Low access, Other/Multiple race population at 1/2 mile, share: Share of tract population that are Other/Multiple race beyond 1/2 mile from supermarket.
`lahisphalf`	string		Low access, Hispanic or Latino population at 1/2 mile, number: Hispanic or Latino ethnicity population count beyond 1/2 mile from supermarket.
`lahisphalfshare`	string		Low access, Hispanic or Latino population at 1/2 mile, share: Share of tract population that are of Hispanic or Latino ethnicity beyond 1/2 mile from supermarket.
`lahunvhalf`	string		Vehicle access, housing units without and low access at 1/2 mile, number: Housing units without vehicle count beyond 1/2 mile from supermarket.
`lahunvhalfshare`	string		Vehicle access, housing units without and low access at 1/2 mile, share: Share of tract housing units that are without vehicle and beyond 1/2 mile from supermarket.
`lasnaphalf`	string		Low access, housing units receiving SNAP benefits at 1/2 mile, number: Housing units receiving SNAP benefits count beyond 1/2 mile from supermarket.
`lasnaphalfshare`	string		Low access, housing units receiving SNAP benefits at 1/2 mile, share: Share of tract housing units receiving SNAP benefits count beyond 1/2 mile from supermarket.
`lapop1`	string		Low access, population at 1 mile, number: Population count beyond 1 mile from supermarket.
`lapop1share`	string		Low access, population at 1 mile, share: Share of tract population that are beyond 1 mile from supermarket.
`lalowi1`	string		Low access, low-income population at 1 mile, number: Low income population count beyond 1 mile from supermarket.
`lalowi1share`	string		Low access, low-income population at 1 mile, share: Share of tract population that are low income individuals beyond 1 mile from supermarket.
`lakids1`	string		Low access, children age 0-17 at 1 mile, number: Kids population count beyond 1 mile from supermarket.
`lakids1share`	string		Low access, children age 0-17 at 1 mile, share: Share of tract population that are kids beyond 1 mile from supermarket.
`laseniors1`	string		Low access, seniors age 65+ at 1 mile, number: Seniors population count beyond 1 mile from supermarket.
`laseniors1share`	string		Low access, seniors age 65+ at 1 mile, share: Share of tract population that are seniors beyond 1 mile from supermarket.
`lawhite1`	string		Low access, White population at 1 mile, number: White population count beyond 1 mile from supermarket.
`lawhite1share`	string		Low access, White population at 1 mile, share: Share of tract population that are white beyond 1 mile from supermarket.
`lablack1`	string		Low access, Black or African American population at 1 mile, number: Black or African American population count beyond 1 mile from supermarket.
`lablack1share`	string		Low access, Black or African American population at 1 mile, share: Share of tract population that are Black or African American beyond 1 mile from supermarket.
`laasian1`	string		Low access, Asian population at 1 mile, number: Asian population count beyond 1 mile from supermarket.
`laasian1share`	string		Low access, Asian population at 1 mile, share: Share of tract population that are Asian beyond 1 mile from supermarket.
`lanhopi1`	string		Low access, Native Hawaiian and Other Pacific Islander population at 1 mile, number: Native Hawaiian or Other Pacific Islander population count beyond 1 mile from supermarket.
`lanhopi1share`	string		Low access, Native Hawaiian and Other Pacific Islander population at 1 mile, share: Share of tract population that are Native Hawaiian or Other Pacific Islander beyond 1 mile from supermarket.
`laaian1`	string		Low access, American Indian and Alaska Native population at 1 mile, number: American Indian or Alaska Native population count beyond 1 mile from supermarket.
`laaian1share`	string		Low access, American Indian and Alaska Native population at 1 mile, share: Share of tract population that are American Indian or Alaska Native beyond 1 mile from supermarket.
`laomultir1`	string		Low access, Other/Multiple race population at 1 mile, number: Other/Multiple race population count beyond 1 mile from supermarket.
`laomultir1share`	string		Low access, Other/Multiple race population at 1 mile, share: Share of tract population that are Other/Multiple race beyond 1 mile from supermarket.
`lahisp1`	string		Low access, Hispanic or Latino population at 1 mile, number: Hispanic or Latino ethnicity population count beyond 1 mile from supermarket.
`lahisp1share`	string		Low access, Hispanic or Latino population at 1 mile, share: Share of tract population that are of Hispanic or Latino ethnicity beyond 1 mile from supermarket.
`lahunv1`	string		Vehicle access, housing units without and low access at 1 mile, number: Housing units without vehicle count beyond 1 mile from supermarket.
`lahunv1share`	string		Vehicle access, housing units without and low access at 1 mile, share: Share of tract housing units that are without vehicle and beyond 1 mile from supermarket.
`lasnap1`	string		Low access, housing units receiving SNAP benefits at 1 mile, number: Housing units receiving SNAP benefits count beyond 1 mile from supermarket.
`lasnap1share`	string		Low access, housing units receiving SNAP benefits at 1 mile, share: Share of tract housing units receiving SNAP benefits count beyond 1 mile from supermarket.
`lapop10`	string		Low access, population at 10 miles, number: Population count beyond 10 miles from supermarket.
`lapop10share`	string		Low access, population at 10 miles, share: Share of tract population that are beyond 10 miles from supermarket.
`lalowi10`	string		Low access, low-income population at 10 miles, number: Low income population count beyond 10 miles from supermarket.
`lalowi10share`	string		Low access, low-income population at 10 miles, share: Share of tract population that are low income individuals beyond 10 miles from supermarket.
`lakids10`	string		Low access, children age 0-17 at 10 miles, number: Kids population count beyond 10 miles from supermarket.
`lakids10share`	string		Low access, children age 0-17 at 10 miles, share: Share of tract population that are kids beyond 10 miles from supermarket.
`laseniors10`	string		Low access, seniors age 65+ at 10 miles, number: Seniors population count beyond 10 miles from supermarket.
`laseniors10share`	string		Low access, seniors age 65+ at 10 miles, share: Share of tract population that are seniors beyond 10 miles from supermarket.
`lawhite10`	string		Low access, White population at 10 miles, number: White population count beyond 10 miles from supermarket.
`lawhite10share`	string		Low access, White population at 10 miles, share: Share of tract population that are white beyond 10 miles from supermarket.
`lablack10`	string		Low access, Black or African American population at 10 miles, number: Black or African American population count beyond 10 miles from supermarket.
`lablack10share`	string		Low access, Black or African American population at 10 miles, share: Share of tract population that are Black or African American beyond 10 miles from supermarket.
`laasian10`	string		Low access, Asian population at 10 miles, number: Asian population count beyond 10 miles from supermarket.
`laasian10share`	string		Low access, Asian population at 10 miles, share: Share of tract population that are Asian beyond 10 miles from supermarket.
`lanhopi10`	string		Low access, Native Hawaiian and Other Pacific Islander population at 10 miles, number: Native Hawaiian or Other Pacific Islander population count beyond 10 miles from supermarket.
`lanhopi10share`	string		Low access, Native Hawaiian and Other Pacific Islander population at 10 miles, share: Share of tract population that are Native Hawaiian or Other Pacific Islander beyond 10 miles from supermarket.
`laaian10`	string		Low access, American Indian and Alaska Native population at 10 miles, number: American Indian or Alaska Native population count beyond 10 miles from supermarket.
`laaian10share`	string		Low access, American Indian and Alaska Native population at 10 miles, share: Share of tract population that are American Indian or Alaska Native beyond 10 miles from supermarket.
`laomultir10`	string		Low access, Other/Multiple race population at 10 miles, number: Other/Multiple race population count beyond 10 miles from supermarket.
`laomultir10share`	string		Low access, Other/Multiple race population at 10 miles, share: Share of tract population that are Other/Multiple race beyond 10 miles from supermarket.
`lahisp10`	string		Low access, Hispanic or Latino population at 10 miles, number: Hispanic or Latino ethnicity population count beyond 10 miles from supermarket.
`lahisp10share`	string		Low access, Hispanic or Latino population at 10 miles, share: Share of tract population that are of Hispanic or Latino ethnicity beyond 10 miles from supermarket.
`lahunv10`	string		Vehicle access, housing units without and low access at 10 miles, number: Housing units without vehicle count beyond 10 miles from supermarket.
`lahunv10share`	string		Vehicle access, housing units without and low access at 10 miles, share: Share of tract housing units that are without vehicle and beyond 10 miles from supermarket.
`lasnap10`	string		Low access, housing units receiving SNAP benefits at 10 miles, number: Housing units receiving SNAP benefits count beyond 10 miles from supermarket.
`lasnap10share`	string		Low access,housing units receiving SNAP benefits at 10 miles, share: Share of tract housing units receiving SNAP benefits count beyond 10 miles from supermarket.
`lapop20`	string		Low access, population at 20 miles, number: Population count beyond 20 miles from supermarket.
`lapop20share`	string		Low access, population at 20 miles, share: Share of tract population that are beyond 20 miles from supermarket.
`lalowi20`	string		Low access, low-income population at 20 miles, number: Low income population count beyond 20 miles from supermarket.
`lalowi20share`	string		Low access, low-income population at 20 miles, share: Share of tract population that are low income individuals beyond 20 miles from supermarket.
`lakids20`	string		Low access, children age 0-17 at 20 miles, number: Kids population count beyond 20 miles from supermarket.
`lakids20share`	string		Low access, children age 0-17 at 20 miles, share: Share of tract population that are kids beyond 20 miles from supermarket.
`laseniors20`	string		Low access, seniors age 65+ at 20 miles, number: Seniors population count beyond 20 miles from supermarket.
`laseniors20share`	string		Low access, seniors age 65+ at 20 miles, share: Share of tract population that are seniors beyond 20 miles from supermarket.
`lawhite20`	string		Low access, White population at 20 miles, number: White population count beyond 20 miles from supermarket.
`lawhite20share`	string		Low access, White population at 20 miles, share: Share of tract population that are white beyond 20 miles from supermarket.
`lablack20`	string		Low access, Black or African American population at 20 miles, number: Black or African American population count beyond 20 miles from supermarket.
`lablack20share`	string		Low access, Black or African American population at 20 miles, share: Share of tract population that are Black or African American beyond 20 miles from supermarket.
`laasian20`	string		Low access, Asian population at 20 miles, number: Asian population count beyond 20 miles from supermarket.
`laasian20share`	string		Low access, Asian population at 20 miles, share: Share of tract population that are Asian beyond 20 miles from supermarket.
`lanhopi20`	string		Low access, Native Hawaiian and Other Pacific Islander population at 20 miles, number: Native Hawaiian or Other Pacific Islander population count beyond 20 miles from supermarket.
`lanhopi20share`	string		Low access, Native Hawaiian and Other Pacific Islander population at 20 miles, share: Share of tract population that are Native Hawaiian or Other Pacific Islander beyond 20 miles from supermarket.
`laaian20`	string		Low access, American Indian and Alaska Native population at 20 miles, number: American Indian or Alaska Native population count beyond 20 miles from supermarket.
`laaian20share`	string		Low access, American Indian and Alaska Native population at 20 miles, share: Share of tract population that are American Indian or Alaska Native beyond 20 miles from supermarket.
`laomultir20`	string		Low access, Other/Multiple race population at 20 miles, number: Other/Multiple race population count beyond 20 miles from supermarket.
`laomultir20share`	string		Low access, Other/Multiple race population at 20 miles, share: Share of tract population that are Other/Multiple race beyond 20 miles from supermarket.
`lahisp20`	string		Low access, Hispanic or Latino population at 20 miles, number: Hispanic or Latino ethnicity population count beyond 20 miles from supermarket.
`lahisp20share`	string		Low access, Hispanic or Latino population at 20 miles, share: Share of tract population that are of Hispanic or Latino ethnicity beyond 20 miles from supermarket.
`lahunv20`	string		Vehicle access, housing units without and low access at 20 miles, number: Housing units without vehicle count beyond 20 miles from supermarket.
`lahunv20share`	string		Vehicle access, housing units without and low access at 20 miles, share: Share of tract housing units that are without vehicle and beyond 20 miles from supermarket.
`lasnap20`	string		Low access, housing units receiving SNAP benefits at 20 miles, number: Housing units receiving SNAP benefits count beyond 20 miles from supermarket.
`lasnap20share`	string		Low access, housing units receiving SNAP benefits at 20 miles, share: Share of tract housing units receiving SNAP benefits count beyond 20 miles from supermarket.
`TractLOWI`	string		Tract low-income population, number: Total count of low-income population in tract.
`TractKids`	string		Tract children age 0-17, number: Total count of children age 0-17 in tract.
`TractSeniors`	string		Tract seniors age 65+, number: Total count of seniors age 65+ in tract.
`TractWhite`	string		Tract White population, number: Total count of White population in tract.
`TractBlack`	string		Tract Black or African American population, number: Total count of Black or African American population in tract.
`TractAsian`	string		Tract Asian population, number: Total count of Asian population in tract.
`TractNHOPI`	string		Tract Native Hawaiian and Other Pacific Islander population, number: Total count of Native Hawaiian and Other Pacific Islander population in tract.
`TractAIAN`	string		Tract American Indian and Alaska Native population, number: Total count of American Indian and Alaska Native population in tract.
`TractOMultir`	string		Tract Other/Multiple race population, number: Total count of Other/Multiple race population in tract.
`TractHispanic`	string		Tract Hispanic or Latino population, number: Total count of Hispanic or Latino population in tract.
`TractHUNV`	string		Tract housing units without a vehicle, number: Total count of housing units without a vehicle in tract.
`TractSNAP`	string		Tract housing units receiving SNAP benefits, number: Total count of housing units receiving SNAP benefits in tract.
`atlas_edition`	string	yes	The Food Access Research Atlas edition this row was published in, e.g. ‘2019’ – the version axis for this source (SPEC.md Versioning model). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.ers__food_access_sram`

USDA ERS Food Access Research Atlas, SNAP-authorized Retailer Access Map (SRAM) landed verbatim and whole, every published column from the General Tract Characteristics and Straight-Line Distance files joined on CensusTract20, one row per 2020 census tract per edition (issue #112). Driving (Network-Based) Distance file not landed – a new methodology axis with no analog in raw.ers__food_access, see ers_food_access.py docstring. Public domain (17 U.S.C. Sec 105).

Sorted by: atlas_edition, CensusTract20

Column	Type	Required	Doc
`CensusTract20`	string	yes	Census tract 2020: Census tract number in 2020.
`State`	string		State: State name.
`County20`	string		County 2020: County name in 2020.
`County24`	string		County 2024: County name in 2024.
`Urban`	string		Urban tract: Flag for urban tract.
`POP2020`	string		Population, tract total: Population count from 2020 census.
`OHU2020`	string		Housing units, total: Occupied housing unit count from 2020 census.
`GroupQuartersFlag`	string		Group quarters, tract with high share: Flag for tract where >=67%.
`NUMGQTRS`	string		Group quarters, tract population residing in, number: Count of tract population residing in group quarters.
`PCTGQTRS`	string		Group quarters, tract population residing in, share: Percent of tract population residing in group quarters.
`LowIncomeTracts`	string		Low income tract: Flag for low income tract.
`PovertyRate`	string		Tract poverty rate: Share of the tract population living with income at or below the Federal poverty thresholds for family size.
`MedianFamilyIncome`	string		Tract median family income: Tract median family income.
`TractLOWI`	string		Tract low-income population, number: Total count of low-income population in tract.
`TractKids`	string		Tract children age 0-17, number: Total count of children age 0-17 in tract.
`TractSeniors`	string		Tract seniors age 65+, number: Total count of seniors age 65+ in tract.
`TractWhite`	string		Tract White population, number: Total count of White population in tract.
`TractBlack`	string		Tract Black or African American population, number: Total count of Black or African American population in tract.
`TractAsian`	string		Tract Asian population, number: Total count of Asian population in tract.
`TractNHOPI`	string		Tract Native Hawaiian and Other Pacific Islander population, number: Total count of Native Hawaiian and Other Pacific Islander population in tract.
`TractAIAN`	string		Tract American Indian and Alaska Native population, number: Total count of American Indian and Alaska Native population in tract.
`TractOMultir`	string		Tract Other/Multiple race population, number: Total count of Other/Multiple race population in tract.
`TractHispanic`	string		Tract Hispanic or Latino population, number: Total count of Hispanic or Latino population in tract.
`TractHUNV`	string		Tract housing units without a vehicle, number: Total count of housing units without a vehicle in tract.
`TractSNAP`	string		Tract housing units receiving SNAP benefits, number: Total count of housing units receiving SNAP benefits in tract.
`TractVeteran`	string		Tract Veteran population, number: Total count of Veteran population in tract.
`TractTribalArea`	string		Tract Tribal area, share: Share of the tract that is American Indian tribal subdivision area (administrative subdivisions of federally recognized American Indian reservations/off-reservation trust lands or Oklahoma tribal statistical areas (OTSAs).
`SD_SRAM_LILATracts_1And10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low income and low access tract measured at 1 mile for urban areas and 10 miles for rural areas: Flag for low-income and low access when considering low accessibilty at 1 and 10 miles, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LILATracts_halfAnd10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low income and low access tract measured at 1/2 mile for urban areas and 10 miles for rural areas: Flag for low-income and low access when considering low accessibilty at 1/2 and 10 miles, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LILATracts_1And20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low income and low access tract measured at 1 mile for urban areas and 20 miles for rural areas: Flag for low-income and low access when considering low accessibilty at 1 and 20 miles, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LILATracts_Vehicle`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low income and low access tract using vehicle access or low income and low access tract measured at 20 miles: Flag for low-income and low access when considering vehicle access or at 20 miles, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_HUNVFlag`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Vehicle access, tract with low vehicle access: Flag for tract where >= 100 of households do not have a vehicle, and beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LA1and10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access tract at 1 mile for urban areas and 10 miles for rural areas: Flag for low access tract at 1 mile for urban areas or 10 miles for rural areas, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LAhalfand10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access tract at 1/2 mile for urban areas and 10 miles for rural areas: Flag for low access tract at 1/2 mile for urban areas or 10 miles for rural areas, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LA1and20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access tract at 1 mile for urban areas and 20 miles for rural areas: Flag for low access tract at 1 mile for urban areas or 20 miles for rural areas, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LATracts_half`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access tract at 1/2 mile: Flag for low access tract when considering 1/2 mile distance, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LATracts1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access tract at 1 mile: Flag for low access tract when considering 1 mile distance, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LATracts10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access tract at 10 miles: Flag for low access tract when considering 10 mile distance, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LATracts20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access tract at 20 miles: Flag for low access tract when considering 20 mile distance, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LATractsVehicle_20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access tract using vehicle access and at 20 miles in rural areas: Flag for tract where >= 100 of households do not have a vehicle, and beyond 1/2 mile from SNAP-authorized foodstore; or >= 500 individuals are beyond 20 miles from SNAP-authorized foodstore ; or >= 33% of individuals are beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LAPOP1_10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 1 mile for urban areas and 10 miles for rural areas, number: Population count beyond 1 mile for urban areas or 10 miles for rural areas from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LAPOP05_10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 1/2 mile for urban areas and 10 miles for rural areas, number: Population count beyond 1/2 mile for urban areas or 10 miles for rural areas from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LAPOP1_20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 1 mile for urban areas and 20 miles for rural areas, number: Population count beyond 1 mile for urban areas or 20 miles for rural areas from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LALOWI1_10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 1 mile for urban areas and 10 miles for rural areas, number: Low income population count beyond 1 mile for urban areas or 10 miles for rural areas from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LALOWI05_10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 1/2 mile for urban areas and 10 miles for rural areas, number: Low income population count beyond 1/2 mile for urban areas or 10 miles for rural areas from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_LALOWI1_20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 1 mile for urban areas and 20 miles for rural areas, number: Low income population count beyond 1 mile for urban areas or 20 miles for rural areas from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lapophalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 1/2 mile, number: Population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lapophalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 1/2 mile, share: Share of tract population that are beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lalowihalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 1/2 mile, number: Low income population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lalowihalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 1/2 mile, share: Share of tract population that are low income individuals beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lakidshalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, children age 0-17 at 1/2 mile, number: Kids population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lakidshalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, children age 0-17 at 1/2 mile, share: Share of tract population that are kids beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laseniorshalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, seniors age 65+ at 1/2 mile, number: Seniors population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laseniorshalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, seniors age 65+ at 1/2 mile, share: Share of tract population that are seniors beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lawhitehalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, White population at 1/2 mile, number: White population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lawhitehalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, White population at 1/2 mile, share: Share of tract population that are white beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lablackhalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Black or African American population at 1/2 mile, number: Black or African American population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lablackhalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Black or African American population at 1/2 mile, share: Share of tract population that are Black or African American beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laasianhalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Asian population at 1/2 mile, number: Asian population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laasianhalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Asian population at 1/2 mile, share: Share of tract population that are Asian beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lanhopihalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Native Hawaiian or Other Pacific Islander population at 1/2 mile, number: Native Hawaiian or Other Pacific Islander population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lanhopihalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Native Hawaiian or Other Pacific Islander population at 1/2 mile, share: Share of tract population that are Native Hawaiian or Other Pacific Islander beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laaianhalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, American Indian or Alaska Native population at 1/2 mile, number: American Indian or Alaska Native population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laaianhalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, American Indian or Alaska Native population at 1/2 mile, share: Share of tract population that are American Indian or Alaska Native beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laomultirhalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Other/Multiple race population at 1/2 mile, number: Other/Multiple race population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laomultirhalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Other/Multiple race population at 1/2 mile, share: Share of tract population that are Other/Multiple race beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahisphalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Hispanic or Latino population at 1/2 mile, number: Hispanic or Latino ethnicity population count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahisphalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Hispanic or Latino population at 1/2 mile, share: Share of tract population that are of Hispanic or Latino ethnicity beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahunvhalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Vehicle access, housing units without and low access at 1/2 mile, number: Housing units without vehicle count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahunvhalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Vehicle access, housing units without and low access at 1/2 mile, share: Share of tract housing units that are without vehicle and beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lasnaphalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, housing units receiving SNAP benefits at 1/2 mile, number: Housing units receiving SNAP benefits count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lasnaphalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, housing units receiving SNAP benefits at 1/2 mile, share: Share of tract housing units receiving SNAP benefits count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laveteranhalf`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, veterans of the U.S. Armed Forces at 1/2 mile, number: Veterans of the U.S. Armed Forces count beyond 1/2 mile from SNAP-authorized foodstore,calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laveteranhalfshare`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, veterans of the U.S. Armed Forces at 1/2 mile, share: Share of tract veterans of the U.S. Armed Forces count beyond 1/2 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lapop1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 1 mile, number: Population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lapop1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 1 mile, share: Share of tract population that are beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lalowi1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 1 mile, number: Low income population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lalowi1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 1 mile, share: Share of tract population that are low income individuals beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lakids1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, children age 0-17 at 1 mile, number: Kids population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lakids1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, children age 0-17 at 1 mile, share: Share of tract population that are kids beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laseniors1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, seniors age 65+ at 1 mile, number: Seniors population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laseniors1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, seniors age 65+ at 1 mile, share: Share of tract population that are seniors beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lawhite1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, White population at 1 mile, number: White population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lawhite1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, White population at 1 mile, share: Share of tract population that are white beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lablack1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Black or African American population at 1 mile, number: Black or African American population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lablack1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Black or African American population at 1 mile, share: Share of tract population that are Black or African American beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laasian1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Asian population at 1 mile, number: Asian population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laasian1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Asian population at 1 mile, share: Share of tract population that are Asian beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lanhopi1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Native Hawaiian and Other Pacific Islander population at 1 mile, number: Native Hawaiian or Other Pacific Islander population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lanhopi1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Native Hawaiian and Other Pacific Islander population at 1 mile, share: Share of tract population that are Native Hawaiian or Other Pacific Islander beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laaian1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, American Indian and Alaska Native population at 1 mile, number: American Indian or Alaska Native population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laaian1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, American Indian and Alaska Native population at 1 mile, share: Share of tract population that are American Indian or Alaska Native beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laomultir1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Other/Multiple race population at 1 mile, number: Other/Multiple race population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laomultir1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Other/Multiple race population at 1 mile, share: Share of tract population that are Other/Multiple race beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahisp1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Hispanic or Latino population at 1 mile, number: Hispanic or Latino ethnicity population count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahisp1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Hispanic or Latino population at 1 mile, share: Share of tract population that are of Hispanic or Latino ethnicity beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahunv1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Vehicle access, housing units without and low access at 1 mile, number: Housing units without vehicle count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahunv1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Vehicle access, housing units without and low access at 1 mile, share: Share of tract housing units that are without vehicle and beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lasnap1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, housing units receiving SNAP benefits at 1 mile, number: Housing units receiving SNAP benefits count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lasnap1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, housing units receiving SNAP benefits at 1 mile, share: Share of tract housing units receiving SNAP benefits count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laveteran1`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, veterans of the U.S. Armed Forces at 1 mile, number: Veterans of the U.S. Armed Forces count beyond 1 mile from SNAP-authorized foodstore,calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laveteran1share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, veterans of the U.S. Armed Forces at 1 mile, share: Share of tract veterans of the U.S. Armed Forces count beyond 1 mile from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lapop10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 10 miles, number: Population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lapop10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 10 miles, share: Share of tract population that are beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lalowi10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 10 miles, number: Low income population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lalowi10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 10 miles, share: Share of tract population that are low income individuals beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lakids10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, children age 0-17 at 10 miles, number: Kids population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lakids10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, children age 0-17 at 10 miles, share: Share of tract population that are kids beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laseniors10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, seniors age 65+ at 10 miles, number: Seniors population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laseniors10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, seniors age 65+ at 10 miles, share: Share of tract population that are seniors beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lawhite10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, White population at 10 miles, number: White population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lawhite10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, White population at 10 miles, share: Share of tract population that are white beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lablack10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Black or African American population at 10 miles, number: Black or African American population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lablack10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Black or African American population at 10 miles, share: Share of tract population that are Black or African American beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laasian10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Asian population at 10 miles, number: Asian population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laasian10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Asian population at 10 miles, share: Share of tract population that are Asian beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lanhopi10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Native Hawaiian and Other Pacific Islander population at 10 miles, number: Native Hawaiian or Other Pacific Islander population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lanhopi10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Native Hawaiian and Other Pacific Islander population at 10 miles, share: Share of tract population that are Native Hawaiian or Other Pacific Islander beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laaian10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, American Indian and Alaska Native population at 10 miles, number: American Indian or Alaska Native population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laaian10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, American Indian and Alaska Native population at 10 miles, share: Share of tract population that are American Indian or Alaska Native beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laomultir10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Other/Multiple race population at 10 miles, number: Other/Multiple race population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laomultir10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Other/Multiple race population at 10 miles, share: Share of tract population that are Other/Multiple race beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahisp10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Hispanic or Latino population at 10 miles, number: Hispanic or Latino ethnicity population count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahisp10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Hispanic or Latino population at 10 miles, share: Share of tract population that are of Hispanic or Latino ethnicity beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahunv10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Vehicle access, housing units without and low access at 10 miles, number: Housing units without vehicle count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahunv10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Vehicle access, housing units without and low access at 10 miles, share: Share of tract housing units that are without vehicle and beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lasnap10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, housing units receiving SNAP benefits at 10 miles, number: Housing units receiving SNAP benefits count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lasnap10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access,housing units receiving SNAP benefits at 10 miles, share: Share of tract housing units receiving SNAP benefits count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laveteran10`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, veterans of the U.S. Armed Forces at 10 miles, number: Veterans of the U.S. Armed Forces count beyond 10 miles from SNAP-authorized foodstore,calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laveteran10share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, veterans of the U.S. Armed Forces at 10 miles, share: Share of tract veterans of the U.S. Armed Forces count beyond 10 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lapop20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 20 miles, number: Population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lapop20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, population at 20 miles, share: Share of tract population that are beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lalowi20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 20 miles, number: Low income population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lalowi20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, low-income population at 20 miles, share: Share of tract population that are low income individuals beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lakids20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, children age 0-17 at 20 miles, number: Kids population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lakids20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, children age 0-17 at 20 miles, share: Share of tract population that are kids beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laseniors20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, seniors age 65+ at 20 miles, number: Seniors population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laseniors20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, seniors age 65+ at 20 miles, share: Share of tract population that are seniors beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lawhite20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, White population at 20 miles, number: White population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lawhite20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, White population at 20 miles, share: Share of tract population that are white beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lablack20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Black or African American population at 20 miles, number: Black or African American population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lablack20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Black or African American population at 20 miles, share: Share of tract population that are Black or African American beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laasian20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Asian population at 20 miles, number: Asian population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laasian20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Asian population at 20 miles, share: Share of tract population that are Asian beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lanhopi20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Native Hawaiian and Other Pacific Islander population at 20 miles, number: Native Hawaiian or Other Pacific Islander population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lanhopi20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Native Hawaiian and Other Pacific Islander population at 20 miles, share: Share of tract population that are Native Hawaiian or Other Pacific Islander beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laaian20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, American Indian and Alaska Native population at 20 miles, number: American Indian or Alaska Native population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laaian20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, American Indian and Alaska Native population at 20 miles, share: Share of tract population that are American Indian or Alaska Native beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laomultir20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Other/Multiple race population at 20 miles, number: Other/Multiple race population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laomultir20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Other/Multiple race population at 20 miles, share: Share of tract population that are Other/Multiple race beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahisp20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Hispanic or Latino population at 20 miles, number: Hispanic or Latino ethnicity population count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahisp20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, Hispanic or Latino population at 20 miles, share: Share of tract population that are of Hispanic or Latino ethnicity beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahunv20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Vehicle access, housing units without and low access at 20 miles, number: Housing units without vehicle count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lahunv20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Vehicle access, housing units without and low access at 20 miles, share: Share of tract housing units that are without vehicle and beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lasnap20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, housing units receiving SNAP benefits at 20 miles, number: Housing units receiving SNAP benefits count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_lasnap20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, housing units receiving SNAP benefits at 20 miles, share: Share of tract housing units receiving SNAP benefits count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laveteran20`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, veterans of the U.S. Armed Forces at 20 miles, number: Veterans of the U.S. Armed Forces count beyond 20 miles from SNAP-authorized foodstore,calculated using straight-line (Euclidean-based) distance.
`SD_SRAM_laveteran20share`	string		Straight-line Distance, SNAP-authorized Retailer Access Map, Low access, veterans of the U.S. Armed Forces at 20 miles, share: Share of tract veterans of the U.S. Armed Forces count beyond 20 miles from SNAP-authorized foodstore, calculated using straight-line (Euclidean-based) distance.
`atlas_edition`	string	yes	The Food Access Research Atlas edition this row was published in – ‘2025’ for SRAM, the version axis for this source (SPEC.md Versioning model). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.ers__ruca_tract`

USDA ERS Rural-Urban Commuting Area codes landed verbatim and whole, one row per census tract per edition. Public domain (U.S. Government work, 17 U.S.C. Sec 105). The 2010 and 2020 editions are different upstream layouts sharing this table via ruca_edition; each edition’s own columns are NULL on the other’s rows.

Sorted by: ruca_edition, fips_2010, TractFIPS20

Column	Type	Required	Doc
`ruca_edition`	string	yes	The RUCA edition this row was published in, ‘2010’ or ‘2020’ – the version axis for this source. Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.
`fips_2010`	string		5-digit county FIPS code (‘State-County FIPS Code’ column). 2010 edition only.
`state_2010`	string		USPS state abbreviation (‘Select State’ column). 2010 edition only.
`county_name_2010`	string		County (or equivalent) name (‘Select County’ column). 2010 edition only.
`tract_fips_2010`	string		11-digit tract FIPS code on 2010-vintage county codes (‘State-County-Tract FIPS Code’ column) – the geo_id source for the 2010 edition. 2010 edition only.
`primary_ruca_2010`	string		Primary RUCA code (‘Primary RUCA Code 2010’ column): 1-10 or 99 (not coded). See measure.definition RUCA:primary for the scheme. 2010 edition only.
`secondary_ruca_2010`	string		Secondary RUCA code (‘Secondary RUCA Code, 2010 (see errata)’ column) – the workbook’s own errata note says this reflects a 3 Jul 2019 correction to 10,909 of 74,002 tracts’ secondary codes; primary codes were unaffected. See measure.definition RUCA:secondary for the scheme. 2010 edition only.
`population_2010`	string		2010 Census tract population (‘Tract Population, 2010’ column). 2010 edition only.
`land_area_2010`	string		Land area, square miles (‘Land Area (square miles), 2010’ column). 2010 edition only.
`pop_density_2010`	string		Population per square mile (‘Population Density (per square mile), 2010’ column); NULL where land area is 0. 2010 edition only.
`TractFIPS23`	string		11-digit tract FIPS code on the county-equivalent codes ERS uses as of 2023 (Connecticut’s nine planning regions, 09110-09190, in place of its eight legacy counties); ‘N/A’ for a handful of zero-population Connecticut water tracts with no 2023 county assignment. NOT used as geo_id – see ers_ruca.py’s docstring. 2020 edition only.
`CountyFIPS23`	string		5-digit county-equivalent FIPS code paired with TractFIPS23, or ‘N/A’. 2020 edition only.
`CountyCode23`	string		3-digit county code (no state prefix) paired with TractFIPS23, or ‘N/A’. 2020 edition only.
`CountyName23`	string		County or county-equivalent name (e.g. a Connecticut planning region) paired with TractFIPS23, or ‘N/A’. 2020 edition only.
`TractFIPS20`	string		11-digit tract FIPS code on 2020-vintage county codes (Connecticut’s eight legacy counties, Alaska’s post-2019 areas) – the geo_id source for the 2020 edition (see ers_ruca.py’s docstring). Always populated, unlike TractFIPS23. 2020 edition only.
`TractCode20`	string		6-digit tract code (no state/county prefix) paired with TractFIPS20. 2020 edition only.
`TractName20`	string		Census tract name, e.g. ‘Census Tract 9781’. 2020 edition only.
`CountyFIPS20`	string		5-digit county FIPS code paired with TractFIPS20. 2020 edition only.
`CountyCode20`	string		3-digit county code (no state prefix) paired with TractFIPS20. 2020 edition only.
`CountyName20`	string		County name paired with TractFIPS20. 2020 edition only.
`StateFIPS20`	string		2-digit state FIPS code. 2020 edition only.
`StateName20`	string		State name. 2020 edition only.
`UrbanAreaCode20`	string		Census urban area code the tract’s core belongs to, or blank when the tract is not an urban core. 2020 edition only.
`UrbanAreaName20`	string		Census urban area name (may carry non-ASCII characters), or blank. 2020 edition only.
`UrbanCore`	string		‘1’ if the tract is part of an urban core, else ‘0’. 2020 edition only.
`UrbanCoreType`	string		Urban core classification driving PrimaryRUCA, e.g. ‘Rural’, ‘Micro core’; ‘Water’ on every code-99 (not coded) tract checked. 2020 edition only.
`PrimaryRUCA`	string		Primary RUCA code: 1-10 or 99 (not coded). See measure.definition RUCA:primary for the scheme. 2020 edition only.
`PrimaryRUCADescription`	string		ERS’s own short label for PrimaryRUCA, e.g. ‘Micropolitan high commuting’. 2020 edition only.
`PrimaryDestinationCode`	string		Urban area (or micro/small-town core tract) code the primary commuting flow is measured against, or blank. 2020 edition only.
`PrimaryDestinationName`	string		Name paired with PrimaryDestinationCode (may carry non-ASCII characters). 2020 edition only.
`SecondaryRUCA`	string		Secondary RUCA code: 1-10, 99, or a decimal sub-flag (e.g. ‘7.2’). See measure.definition RUCA:secondary for the scheme. 2020 edition only.
`SecondaryRUCADescription`	string		ERS’s own short label for SecondaryRUCA, e.g. ‘Small town core, secondary flow to micro UA’. 2020 edition only.
`SecondaryDestinationCode`	string		Destination code the secondary commuting flow is measured against, or blank. 2020 edition only.
`SecondaryDestinationName`	string		Name paired with SecondaryDestinationCode. 2020 edition only.
`Population`	string		2020 Census tract population. 2020 edition only.
`LandArea`	string		Land area, square miles. 2020 edition only.
`PopDensity`	string		Population per square mile. 2020 edition only.

`raw.ers__rucc`

USDA ERS Rural-Urban Continuum Codes landed verbatim and whole, long format: one row per (county, attribute) exactly as published. Public domain (U.S. Government work, 17 U.S.C. Sec 105).

Sorted by: rucc_edition, FIPS, Attribute

Column	Type	Required	Doc
`FIPS`	string	yes	5-digit county (or county-equivalent) FIPS code, as published — zero-padded string, e.g. ‘01001’.
`State`	string	yes	USPS state abbreviation.
`County_Name`	string	yes	County (or equivalent) name, as published.
`Attribute`	string	yes	Which fact this row carries: ‘Population_2020’, ‘RUCC_’ (e.g. ‘RUCC_2023’), or ‘Description’. Long format — one row per (FIPS, Attribute).
`Value`	string		The value for Attribute, unparsed. NULL only where the source cell itself is blank; a FIPS entirely missing an Attribute row (e.g. no RUCC_2023 for a zero-population entity) is absent from this table rather than present with a NULL Value.
`rucc_edition`	string	yes	The RUCC edition this row was published in, e.g. ‘2023’ — the version axis for this source. Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.fda__mqsa_facilities`

FDA MQSA certified mammography facility list, landed verbatim and whole, replaced weekly (SPEC.md § Sources — first tranche). Public domain; FDA’s site-wide website policy states ‘the contents of the FDA website … are not copyrighted. They are in the public domain and may be republished, reprinted and otherwise used freely by anyone without the need to obtain permission from FDA’ (https://www.fda.gov/about-fda/about-website/website-policies, checked 2026-09-18).

Sorted by: retrieved_on, State, Facility Name, Address 1

Column	Type	Required	Doc
`Facility Name`	string	yes	Facility’s own name. Normalised and hashed into facility.site.facility_id (no id column exists in this file – see fda_mqsa.py); also facility.site.name.
`Address 1`	string		Street address line 1; part of facility.site.address and facility_id.
`Address 2`	string		Street address line 2, often NULL; part of facility.site.address and facility_id.
`Address 3`	string		Street address line 3, often NULL; part of facility.site.address and facility_id.
`City`	string		Part of facility.site.address and facility_id; also facility.site.attributes_json’s ‘city’ key.
`State`	string	yes	USPS state/territory/military abbreviation; part of facility.site.address and facility_id; also facility.site.attributes_json’s ‘state’ key.
`Zip Code`	string	yes	5-digit or ZIP+4; only the first 5 digits feed facility_id (a ZIP+4 changing alone must not look like a different facility). Also facility.site.address and attributes_json’s ‘zip’ key.
`Phone`	string		As published by FDA; not used downstream (excluded from facility_id – see fda_mqsa.py).
`Fax`	string		As published by FDA; not used downstream.
`retrieved_on`	string	yes	Date this weekly-refreshed dump was fetched, ISO YYYY-MM-DD – the version axis for this source (it publishes no edition label). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.geography__county_recodes`

Curated CSV of Census ‘Substantial Changes to Counties’ name/code changes (county_recodes.csv, committed in the package — the upstream is prose, not a data file), landed verbatim and whole. Replaced wholesale each time it is re-curated, like raw.census__state_fips — there is no upstream edition to key an overwrite scope on. Licence: U.S. government work, public domain (17 U.S.C. § 105).

Sorted by: old_fips, new_fips

Column	Type	Required	Doc
`old_fips`	string	yes	5-digit county FIPS code before the change, as published, zero-padded, e.g. ‘46113’.
`old_name`	string	yes	County (or equivalent) name before the change, as published.
`new_fips`	string	yes	5-digit county FIPS code after the change, as published.
`new_name`	string	yes	County (or equivalent) name after the change, as published.
`effective_year`	string	yes	Calendar year the change took effect, unparsed.
`change_type`	string	yes	One of: recode, rename, recode_and_rename.
`source_url`	string	yes	The Census county-changes decade page this row was transcribed from.
`note`	string		The exact Census sentence this row was transcribed from, quoted.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.hrsa__ahrf`

HRSA Area Health Resources Files (AHRF), county level, landed LONG: one row per (county, field) cell rather than one enormously wide row per county (SPEC.md § Sources – first tranche). Landed WHOLE for every field not withheld on licence grounds – ‘whole’ as SPEC.md ADR-0002 uses it, at cell granularity rather than one wide table; public-domain federal-origin fields only. Licence: U.S. government work, public domain (17 U.S.C. Sec 105) for every field landed here. Fields sourced from the AMA Physician Masterfile, AHA hospital survey, or ADA Masterfile are copyrighted third-party content and are never landed.

Sorted by: ahrf_release, fips, column_name

Column	Type	Required	Doc
`ahrf_release`	string	yes	The AHRF release label, e.g. ‘2024-2025’ – the version column; raw is replaced wholesale per value of this column. NOT the year a value describes: one release carries many data years, encoded in column_name’s own numeric suffix (see hrsa_ahrf.py’s docstring).
`file`	string	yes	Which landed source file this cell came from, e.g. ‘AHRF2025.csv’.
`fips`	string	yes	5-digit county (or county-equivalent) FIPS code, as published – zero-padded string, e.g. ‘01001’.
`column_name`	string	yes	The AHRF field name this cell’s value came from, verbatim, e.g. ‘fedly_qualfd_hlth_ctr_24’. Only fields NOT sourced from the AMA Physician Masterfile, the AHA hospital survey, or the ADA Masterfile are landed here – those are copyrighted third-party content and are excluded before landing, never reproduced in any namespace.
`value`	string		The cell’s raw string value, unparsed. NULL only where the source CSV cell itself was blank – AHRF’s own missing-data marker for these fields; a real reported 0 is never read as missing.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed this row.

`raw.hrsa__health_center_sites`

HRSA Health Center Service Delivery and Look-Alike Sites, landed verbatim and whole (SPEC.md § Sources — first tranche). Public domain; HRSA’s own Data Usage Terms & Conditions for this dataset state ‘Usage limitations: None’ (https://data.hrsa.gov/data/download, checked 2026-09-18).

Sorted by: retrieved_on, BPHC Assigned Number

Column	Type	Required	Doc
`Health Center Type`	string	yes	‘Federally Qualified Health Center (FQHC)’ or ‘…FQHC) Look-Alike’.
`Health Center Number`	string		Grantee’s HRSA-assigned number, e.g. ‘H80CS00305’.
`BHCMIS Organization Identification Number`	string		As published by HRSA; not used downstream.
`BPHC Assigned Number`	string	yes	Per-site identifier, e.g. ‘BPS-H80-000078’ – verified unique across every row of the file (2026-09-18); this is facility.site.facility_id.
`Site Name`	string		Site’s own name; facility.site.name.
`Site Address`	string		Street address; part of facility.site.address.
`Site City`	string		Part of facility.site.address.
`Site State Abbreviation`	string		Part of facility.site.address.
`Site Postal Code`	string		Part of facility.site.address.
`Site Telephone Number`	string		As published by HRSA; not used downstream.
`Site Web Address`	string		As published by HRSA; not used downstream.
`Operating Hours per Week`	string		Unparsed; NULL for some Administrative sites. facility.site.attributes_json’s ‘operating_hours_reported’ flag is true iff this is non-NULL here.
`Health Center Location Setting Identification Number`	string		As published by HRSA; not used downstream.
`Health Center Service Delivery Site Location Setting Description`	string		As published by HRSA; not used downstream.
`Health Center Status Identification Number`	string		As published by HRSA; not used downstream.
`Site Status Description`	string		Always ‘Active’ in this file (it lists current sites only); facility.site.attributes_json’s ‘status’ key.
`FQHC Site Medicare Billing Number`	string		As published by HRSA; not used downstream.
`FQHC Site NPI Number`	string		As published by HRSA; not used downstream.
`Health Center Location Identification Number`	string		A lookup code (only 3 distinct values file-wide, 2026-09-18) – not a per-site id; see ‘BPHC Assigned Number’ for that.
`Health Center Location Type Description`	string		‘Permanent’ \| ‘Seasonal’ \| ‘Mobile Van’; facility.site.attributes_json’s ‘site_type’ key.
`Health Center Type Identification Number`	string		As published by HRSA; not used downstream.
`Health Center Type Description`	string		As published by HRSA; not used downstream.
`Health Center Operator Identification Number`	string		As published by HRSA; not used downstream.
`Health Center Operator Description`	string		As published by HRSA; not used downstream.
`Health Center Operating Schedule Identification Number`	string		As published by HRSA; not used downstream.
`Health Center Operational Schedule Description`	string		As published by HRSA; not used downstream.
`Health Center Operating Calendar Surrogate Key`	string		As published by HRSA; not used downstream.
`Health Center Operating Calendar`	string		As published by HRSA; not used downstream.
`Site Added to Scope this Date`	string		As published by HRSA; not used downstream.
`Health Center Name`	string		Grantee organization’s name; facility.site.attributes_json’s ‘grantee_name’ key.
`Health Center Organization Street Address`	string		As published by HRSA; not used downstream.
`Health Center Organization City`	string		As published by HRSA; not used downstream.
`Health Center Organization State`	string		As published by HRSA; not used downstream.
`Health Center Organization ZIP Code`	string		As published by HRSA; not used downstream.
`Grantee Organization Type Description`	string		As published by HRSA; not used downstream.
`Geocoding Artifact Address Primary X Coordinate`	string		Longitude, unparsed; facility.site.lon (TRY_CAST to double – 73 rows are blank, 2026-09-18).
`Geocoding Artifact Address Primary Y Coordinate`	string		Latitude, unparsed; facility.site.lat.
`U.S. - Mexico Border 100 Kilometer Indicator`	string		As published by HRSA; not used downstream.
`U.S. - Mexico Border County Indicator`	string		As published by HRSA; not used downstream.
`State and County Federal Information Processing Standard Code`	string	yes	5-digit county FIPS, e.g. ‘12031’; facility.site.geo_id is ‘county:’+this. The file carries current (2020-vintage) codes only – Connecticut’s nine planning regions 09110-09190 and Alaska’s current census areas (e.g. 02063 Chugach, 02066 Copper River), no legacy codes seen (2026-09-18).
`Complete County Name`	string		As published by HRSA; not used downstream.
`County Equivalent Name`	string		As published by HRSA; not used downstream.
`County Description`	string		As published by HRSA; not used downstream.
`HHS Region Code`	string		As published by HRSA; not used downstream.
`HHS Region Name`	string		As published by HRSA; not used downstream.
`State FIPS Code`	string		As published by HRSA; not used downstream.
`State Name`	string		As published by HRSA; not used downstream.
`State FIPS and Congressional District Number Code`	string		As published by HRSA; not used downstream.
`Congressional District Number`	string		As published by HRSA; not used downstream.
`Congressional District Name`	string		As published by HRSA; not used downstream.
`Congressional District Code`	string		As published by HRSA; not used downstream.
`U.S. Congressional Representative Name`	string		As published by HRSA; not used downstream.
`Name of U.S. Senator Number One`	string		As published by HRSA; not used downstream.
`Name of U.S. Senator Number Two`	string		As published by HRSA; not used downstream.
`Data Warehouse Record Create Date`	string		As published by HRSA; not used downstream.
`retrieved_on`	string	yes	Date this daily-refreshed dump was fetched, ISO YYYY-MM-DD – the version axis for this source (it publishes no edition label). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.hrsa__hpsa_primary_care`

HRSA primary-care Health Professional Shortage Area designations (BCD_HPSA_FCT_DET_PC.csv), landed verbatim and whole, every status including Withdrawn (SPEC.md § Sources — first tranche). Public domain; HRSA’s own Data Usage Terms & Conditions for this dataset state ‘Usage limitations: None’ (https://data.hrsa.gov/data/download, checked 2026-09-18). Dental and mental-health HPSA files are not landed by this module (issue #38 asks for primary care at minimum).

Sorted by: retrieved_on, HPSA ID

Column	Type	Required	Doc
`HPSA Name`	string		Shortage area’s own name – an organisation/place name, never an individual.
`HPSA ID`	string	yes	HRSA’s designation id.
`Designation Type`	string	yes	‘Geographic HPSA’ \| ‘High Needs Geographic HPSA’ (the only two counted into measure.observation) \| ‘HPSA Population’ \| ‘Federally Qualified Health Center’ \| ‘…Look A Like’ \| ‘Rural Health Clinic’ \| ‘Correctional Facility’ \| ‘Other Facility’ \| ‘Indian Health Service, Tribal Health, and Urban Indian Health Organizations’ – the rest are population-group or facility designations that don’t carry a usable geo_id (SPEC.md gap noted in issue #38); landed here but not derived.
`HPSA Discipline Class`	string	yes	‘Primary Care’ for every row in this file.
`HPSA Score`	string		HRSA’s shortage-severity score, unparsed; feeds measure.observation’s HPSA:pc_max_score.
`PC MCTA Score`	string		As published by HRSA; not used downstream.
`Primary State Abbreviation`	string		As published by HRSA; not used downstream.
`HPSA Status`	string	yes	‘Designated’ \| ‘Withdrawn’ \| ‘Proposed For Withdrawal’. Withdrawn / proposed-for-withdrawal is a real status, not suppression – carried as-is; only ‘Designated’ rows feed measure.observation.
`HPSA Designation Date`	string		As published by HRSA; not used downstream.
`HPSA Designation Last Update Date`	string		As published by HRSA; not used downstream.
`Metropolitan Indicator`	string		As published by HRSA; not used downstream.
`HPSA Geography Identification Number`	string		As published by HRSA; not used downstream.
`HPSA Degree of Shortage`	string		As published by HRSA; not used downstream.
`Withdrawn Date`	string		As published by HRSA; not used downstream.
`HPSA FTE`	string		As published by HRSA; not used downstream.
`HPSA Designation Population`	string		As published by HRSA; not used downstream.
`% of Population Below 100% Poverty`	string		As published by HRSA; not used downstream.
`HPSA Formal Ratio`	string		As published by HRSA; not used downstream.
`HPSA Population Type`	string		As published by HRSA; not used downstream.
`Rural Status`	string		As published by HRSA; not used downstream.
`Longitude`	string		As published by HRSA; not used downstream.
`Latitude`	string		As published by HRSA; not used downstream.
`BHCMIS Organization Identification Number`	string		As published by HRSA; not used downstream.
`Break in Designation`	string		As published by HRSA; not used downstream.
`Common County Name`	string		As published by HRSA; not used downstream.
`Common Postal Code`	string		As published by HRSA; not used downstream.
`Common Region Name`	string		As published by HRSA; not used downstream.
`Common State Abbreviation`	string		As published by HRSA; not used downstream.
`Common State County FIPS Code`	string		As published by HRSA; not used downstream.
`Common State FIPS Code`	string		As published by HRSA; not used downstream.
`Common State Name`	string		As published by HRSA; not used downstream.
`County Equivalent Name`	string		As published by HRSA; not used downstream.
`County or County Equivalent Federal Information Processing Standard Code`	string		As published by HRSA; not used downstream.
`Discipline Class Number`	string		As published by HRSA; not used downstream.
`HPSA Address`	string		As published by HRSA; not used downstream.
`HPSA City`	string		As published by HRSA; not used downstream.
`HPSA Component Name`	string		As published by HRSA; not used downstream.
`HPSA Component Source Identification Number`	string		As published by HRSA; not used downstream.
`HPSA Component State Abbreviation`	string		As published by HRSA; not used downstream.
`HPSA Component Type Code`	string		As published by HRSA; not used downstream.
`HPSA Component Type Description`	string		‘Single County’ \| ‘County Subdivision’ \| ‘Census Tract’ – the HPSA’s own sub-county component granularity; a multi-component HPSA has one row per component, all sharing the same county FIPS (deduplicated by HPSA ID + FIPS before counting, see hrsa_sites.py).
`HPSA Designation Population Type Description`	string		As published by HRSA; not used downstream.
`HPSA Estimated Served Population`	string		As published by HRSA; not used downstream.
`HPSA Estimated Underserved Population`	string		As published by HRSA; not used downstream.
`HPSA Metropolitan Indicator Code`	string		As published by HRSA; not used downstream.
`HPSA Population Type Code`	string		As published by HRSA; not used downstream.
`HPSA Postal Code`	string		As published by HRSA; not used downstream.
`HPSA Provider Ratio Goal`	string		As published by HRSA; not used downstream.
`HPSA Resident Civilian Population`	string		As published by HRSA; not used downstream.
`HPSA Shortage`	string		As published by HRSA; not used downstream.
`HPSA Status Code`	string		As published by HRSA; not used downstream.
`HPSA Type Code`	string		As published by HRSA; not used downstream.
`HPSA Withdrawn Date String`	string		As published by HRSA; not used downstream.
`Primary State FIPS Code`	string		As published by HRSA; not used downstream.
`Primary State Name`	string		As published by HRSA; not used downstream.
`Provider Type`	string		As published by HRSA; not used downstream.
`Rural Status Code`	string		As published by HRSA; not used downstream.
`State Abbreviation`	string		As published by HRSA; not used downstream.
`State and County Federal Information Processing Standard Code`	string	yes	5-digit county FIPS for a real designation, but ‘XXXXX’ / ‘XXX’ for some Withdrawn / Proposed For Withdrawal rows (masked, not a real code – verified 2026-09-18; none seen on a currently-Designated Geographic/High Needs row). measure.observation’s geo_id is ‘county:’+this, restricted to rows matching 5 digits.
`State FIPS Code`	string		As published by HRSA; not used downstream.
`State Name`	string		As published by HRSA; not used downstream.
`U.S. - Mexico Border 100 Kilometer Indicator`	string		As published by HRSA; not used downstream.
`U.S. - Mexico Border County Indicator`	string		As published by HRSA; not used downstream.
`Data Warehouse Record Create Date`	string		As published by HRSA; not used downstream.
`Data Warehouse Record Create Date Text`	string		As published by HRSA; not used downstream.
`retrieved_on`	string	yes	Date this daily-refreshed dump was fetched, ISO YYYY-MM-DD – the version axis for this source. Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.nci__catchment_areas`

NCI-designated cancer center catchment areas landed whole, geometry included (WKB), one row per shapefile record (69, incl. two summary rows). Source: National Cancer Institute, GIS Portal for Cancer Research; cite DelNero et al., CEBP 2022, doi:10.1158/1055-9965.EPI-21-1230. A U.S. Government work (17 U.S.C. § 105); licence cleared by the owner (#195).

Sorted by: source_version, ID

Column	Type	Required	Doc
`name`	string	yes	Catchment name as published (the center’s name; NOT unique – Mayo Clinic appears three times, once per site). The two summary rows ‘Total US Stat’ and ‘All Catchment Areas Stat’ are kept here and have no geometry. Source: National Cancer Institute, GIS Portal for Cancer Research (https://gis.cancer.gov/ncicatchment/). Cite DelNero PF, et al., Cancer Epidemiol Biomarkers Prev 2022;31(5):965-71, doi:10.1158/1055-9965.EPI-21-1230.
`ID`	string	yes	NCI’s catchment id, the dBASE integer as text. Unique per polygon (not per center, not contiguous); the key.
`type`	string		Designation: ‘Comprehensive Cancer Center’ or ‘Cancer Center’. NULL on the summary rows.
`address`	string		Center street address as published, embedded line breaks kept.
`state`	string		State name as published (e.g. ‘Washington D.C.’).
`GeoDesc`	string		NCI’s geographic description: Full-State \| Sub-State \| Inter-State \| Multi-State \| Full-Inter-State.
`url`	string		Center web address as published.
`draworder`	string		Portal map drawing order, as text; display only.
`geometry_wkb`	binary		The catchment polygon as OGC well-known binary, in the shapefile’s own CRS (see geometry_crs). NULL on the two summary rows. Republished from NCI_Catchment_Areas_*.zip; boundaries are center-submitted definitions plus Census TIGER, so some are partial counties.
`geometry_crs`	string	yes	CRS of geometry_wkb as DuckDB spatial reads it from the shapefile’s .prj, e.g. ‘EPSG:4326’.
`source_version`	string	yes	The zip’s HTTP Last-Modified date (ISO), the version axis for this source. Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.places__county`

CDC PLACES county-data release, landed verbatim and whole: one row per (county, measure, stratification type) model-based small-area estimate (SPEC.md § Sources — first tranche). Public domain.

Sorted by: places_release, LocationID, MeasureId, DataValueTypeID

Column	Type	Required	Doc
`Year`	string	yes	BRFSS survey year this row’s estimate is based on, e.g. ‘2022’.
`StateAbbr`	string		Two-letter state postal abbreviation, or ‘US’ for the national aggregate row.
`StateDesc`	string		State name, or ‘United States’ for the national row.
`LocationName`	string		County name; empty for the national row.
`DataSource`	string		Survey the estimate is modeled from, e.g. ‘BRFSS’.
`Category`	string		Measure category, e.g. ‘Health Outcomes’, ‘Prevention’.
`Measure`	string		Full measure description including its universe, e.g. ‘Current cigarette smoking among adults’.
`Data_Value_Unit`	string		Unit of Data_Value, e.g. ‘%’.
`Data_Value_Type`	string		‘Crude prevalence’ or ‘Age-adjusted prevalence’.
`Data_Value`	string		The published estimate, unparsed; empty (NULL) when suppressed — see Data_Value_Footnote.
`Data_Value_Footnote_Symbol`	string		Footnote marker on Data_Value, or NULL.
`Data_Value_Footnote`	string		Footnote text explaining a missing Data_Value, or NULL.
`Low_Confidence_Limit`	string		95% CI lower bound, unparsed.
`High_Confidence_Limit`	string		95% CI upper bound, unparsed.
`TotalPopulation`	string		Total population of the location, per the source’s own population estimate. NOT this measure’s denominator — PLACES publishes no numerator/denominator pair; kept for reference only.
`TotalPop18plus`	string		Adult (18+) population of the location, per the source’s own population estimate. Not used as a denominator, for the same reason as TotalPopulation.
`LocationID`	string	yes	County FIPS code (5 digits, leading zero kept), or ‘59’ for the national aggregate row (paired with StateAbbr=‘US’).
`CategoryID`	string		Short code for Category.
`MeasureId`	string	yes	Short code for Measure, e.g. ‘CSMOKING’.
`DataValueTypeID`	string		Short code for Data_Value_Type, e.g. ‘CrdPrv’, ‘AgeAdjPrv’.
`Short_Question_Text`	string		Short label for Measure, e.g. ‘Current Smoking’.
`Geolocation`	string		County centroid as a WKT POINT string, or NULL for the national row.
`places_release`	string	yes	The PLACES county-data release year this row came from, e.g. ‘2025’ (a key of places.RELEASES). Raw is replaced wholesale per value of this column.

`raw.places__tract`

CDC PLACES tract-data release, landed verbatim and whole: one row per (tract, measure) model-based small-area estimate, crude prevalence only (SPEC.md § Sources — first tranche; #30). Public domain.

Sorted by: places_release, LocationID, MeasureId, DataValueTypeID

Column	Type	Required	Doc
`Year`	string	yes	BRFSS survey year this row’s estimate is based on, e.g. ‘2022’.
`StateAbbr`	string		Two-letter state postal abbreviation.
`StateDesc`	string		State name.
`CountyName`	string		County name the tract belongs to. Not present in the county-data contract (raw.places__county), which IS the county.
`CountyFIPS`	string	yes	5-digit county FIPS code (leading zero kept) the tract belongs to.
`LocationName`	string		The 11-digit tract FIPS, verbatim – an upstream quirk: unlike the county file, where LocationName is a human name, here it duplicates LocationID rather than naming anything.
`DataSource`	string		Survey the estimate is modeled from, e.g. ‘BRFSS’.
`Category`	string		Measure category, e.g. ‘Health Outcomes’, ‘Disability’.
`Measure`	string		Full measure description including its universe, e.g. ‘Current cigarette smoking among adults’.
`Data_Value_Unit`	string		Unit of Data_Value, e.g. ‘%’.
`Data_Value_Type`	string		Always ‘Crude prevalence’ in the tract data – PLACES publishes no age-adjusted variant at tract grain (verified via the Socrata SODA API against every landed release).
`Data_Value`	string		The published estimate, unparsed; empty (NULL) when suppressed – see Data_Value_Footnote. Every row is ‘reported’ in the releases actually landed here (places.py module docstring).
`Data_Value_Footnote_Symbol`	string		Footnote marker on Data_Value, or NULL.
`Data_Value_Footnote`	string		Footnote text explaining a missing Data_Value, or NULL.
`Low_Confidence_Limit`	string		95% CI lower bound, unparsed.
`High_Confidence_Limit`	string		95% CI upper bound, unparsed.
`TotalPopulation`	string		Total population of the tract, per the source’s own population estimate. NOT this measure’s denominator, same as the county table.
`TotalPop18plus`	string		Adult (18+) population of the tract, per the source’s own population estimate. Not used as a denominator, same as the county table.
`Geolocation`	string		Tract centroid as a WKT POINT string.
`LocationID`	string	yes	11-digit tract FIPS code (leading zero kept).
`CategoryID`	string		Short code for Category.
`MeasureId`	string	yes	Short code for Measure, e.g. ‘CSMOKING’ – the same code space as the county table; derived observations reuse the county crude measure_id rather than minting a tract-specific one.
`DataValueTypeID`	string		Always ‘CrdPrv’ in tract data.
`Short_Question_Text`	string		Short label for Measure, e.g. ‘Current Smoking’.
`places_release`	string	yes	The PLACES tract-data release year this row came from, e.g. ‘2025’ (a key of places.TRACT_RELEASES). Raw is replaced wholesale per value of this column.

`raw.scp__incidence`

State Cancer Profiles incidence, landed verbatim and whole, one row per (geography, cancer site, sex, age, race, stage) query cell, per vintage (SPEC.md § Sources – first tranche, the flagship, #27). This is a REPUBLISHED SCRAPE, not the original archive: statecancerprofiles.cancer.gov (NCI/CDC) has no API, bulk download or archive, so seandavi/state-cancer-profile-scraper scrapes it and republishes each captured vintage as a versioned Zenodo deposit, read here over anonymous HTTPS (#65). The underlying content is a U.S. Government work, public domain under 17 U.S.C. Sec 105; not endorsed by NCI/CDC.

Sorted by: scp_vintage, fips, cancer, sex

Column	Type	Required	Doc
`reported_locale`	string		County/state name exactly as SCP renders it, including any footnote markers glued on (e.g. ‘Allen County, Kansas(2)’); see locale/state for the plain name.
`fips`	string		5-digit FIPS code as published: a county code, a state code padded ‘000’, or the national sentinel ‘00000’.
`2023_rural_urban_continuum_codesrural_urban_note`	string		SCP’s own two header cells concatenated with no separator by the upstream export (a verbatim upstream defect, not a scrape artifact) – rural/urban classification per the 2023 USDA RUCC (2013 codes for Connecticut). NULL in V1/V2, which predate this column.
`age_adjusted_rate_per_100_000`	string		The published incidence rate, age-adjusted to the 2000 US standard population. NULL whenever the cell is suppressed or withheld.
`lower_ci_rate`	string		95% CI lower bound, or the literal sentinel ’*’ when the rate is suppressed – landed as text so the sentinel survives verbatim; TRY_CAST in transform turns it into a clean NULL.
`upper_ci_rate`	string		95% CI upper bound, or ’*’ when suppressed (see lower_ci_rate).
`ci_rank`	string		SCP’s CI*Rank statistic; only populated for ‘By State’ rows from the 2026-05-28+ scrape. Landed for reference, not derived.
`lower_ci_rank`	string		Lower bound of ci_rank’s interval; see ci_rank.
`upper_ci_rank`	string		Upper bound of ci_rank’s interval; see ci_rank.
`average_annual_count`	string		Average annual case count for the period, or NULL when suppressed. A small rounded value (e.g. ‘3’) is not itself evidence of suppression – SCP rounds counts of 16+ that are still below reporting precision; only suppression_reason / a NULL rate means suppressed.
`recent_trend`	string		SCP’s trend call (‘stable’/‘rising’/‘falling’), or a text marker: ’*’ (trend not computable/suppressed) or ‘[P1 note]’ (state-law withholding). Landed verbatim; both markers become trend=NULL in measure.observation.
`recent_5_year_trend_in_rate`	string		Average Annual Percent Change (AAPC) point estimate, or the ’*‘/’[P1 note]’ markers (see recent_trend). Landed for reference, not derived.
`lower_ci_trend_in_rate`	string		AAPC’s 95% CI lower bound; see recent_5_year_trend_in_rate.
`upper_ci_trend_in_rate`	string		AAPC’s 95% CI upper bound; see recent_5_year_trend_in_rate.
`year`	string		SCP’s own period label – always the literal constant ‘Latest 5-year average’ in every row of every vintage (verified); carries no real year. See scp.py’s module docstring for where the real period comes from.
`sex`	string		‘Both Sexes’ \| ‘Male’ \| ‘Female’, as published.
`stage`	string		‘All Stages’ \| ‘Late Stage (Regional & Distant)’, as published.
`race`	string		Source-native race/ethnicity category, as published (6 values; see the scraper’s select_options.json).
`cancer`	string		SCP’s cancer-site category label, as published (23 values, including combined categories like ‘Colon & Rectum’ – see select_options.json and scp.py’s SEER bridge).
`areatype`	string		SCP’s query-mode flag (‘By County’/‘By State’); NOT reliable for a row’s own geographic level – constant ‘By County’ even on the national aggregate row in V1. See locale_type.
`age`	string		Source-native age group, as published (7 values; see select_options.json).
`state_fips`	string		2-digit state FIPS code, or ‘00’ for the national row.
`measurement`	string		Topic marker, constant ‘incidence’ for this table.
`locale_type`	string		SCP’s own geography-type tag (‘county’/‘state’/‘national’/‘other’); NOT reliable for a row’s own geographic level – known to misclassify real counties (Louisiana parishes, Alaska boroughs, DC, Puerto Rico) as ‘other’. Geo level is derived from fips’s own shape instead (scp.py’s module docstring).
`_extracted_at`	string		ISO timestamp the scraper recorded for this row’s capture.
`url`	string		The exact statecancerprofiles.cancer.gov query URL the scraper captured this row from.
`suppression_reason`	string		‘suppressed_small_count’ \| ‘withheld_state_law’, or NULL when reported. Absent from V1/V2 (NULL on every row there) – those vintages carry no suppression marker at all (scp.py’s module docstring); V3’s own two values are the complete enum found in the real files – an unmapped value raises SystemExit in transform rather than a guess.
`percent_of_cases_with_late_stage`	string		A separate published statistic (not this measure’s rate); landed for reference, not derived.
`locale`	string		Plain county/state name, footnote markers stripped (compare reported_locale).
`state`	string		Full state name, or NULL for a county-level row (the state is implied by fips).
`scp_vintage`	string	yes	Which vintage this row belongs to: ‘V1’ \| ‘V2’ \| ‘V3’ (scp.py’s module docstring). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	Cancer Basemap release that landed this row.

`raw.scp__mortality`

State Cancer Profiles mortality, landed verbatim and whole, one row per (geography, cancer site, sex, age, race[, stage]) query cell, per vintage (SPEC.md § Sources – first tranche, the flagship, #27). This is a REPUBLISHED SCRAPE, not the original archive: statecancerprofiles.cancer.gov (NCI/CDC) has no API, bulk download or archive, so seandavi/state-cancer-profile-scraper scrapes it and republishes each captured vintage as a versioned Zenodo deposit, read here over anonymous HTTPS (#65). The underlying content is a U.S. Government work, public domain under 17 U.S.C. Sec 105; not endorsed by NCI/CDC.

Sorted by: scp_vintage, fips, cancer, sex

Column	Type	Required	Doc
`reported_locale`	string		County/state name exactly as SCP renders it, including any footnote markers glued on (e.g. ‘Allen County, Kansas(2)’); see locale/state for the plain name.
`fips`	string		5-digit FIPS code as published: a county code, a state code padded ‘000’, or the national sentinel ‘00000’.
`2023_rural_urban_continuum_codesrural_urban_note`	string		SCP’s own two header cells concatenated with no separator by the upstream export (a verbatim upstream defect, not a scrape artifact) – rural/urban classification per the 2023 USDA RUCC (2013 codes for Connecticut). NULL in V1/V2, which predate this column.
`age_adjusted_rate_per_100_000`	string		The published death rate, age-adjusted to the 2000 US standard population. NULL whenever the cell is suppressed or withheld.
`lower_ci_rate`	string		95% CI lower bound, or the literal sentinel ’*’ when the rate is suppressed – landed as text so the sentinel survives verbatim; TRY_CAST in transform turns it into a clean NULL.
`upper_ci_rate`	string		95% CI upper bound, or ’*’ when suppressed (see lower_ci_rate).
`ci_rank`	string		SCP’s CI*Rank statistic; only populated for ‘By State’ rows from the 2026-05-28+ scrape. Landed for reference, not derived.
`lower_ci_rank`	string		Lower bound of ci_rank’s interval; see ci_rank.
`upper_ci_rank`	string		Upper bound of ci_rank’s interval; see ci_rank.
`average_annual_count`	string		Average annual death count for the period, or NULL when suppressed. A small rounded value (e.g. ‘3’) is not itself evidence of suppression – SCP rounds counts of 16+ that are still below reporting precision; only suppression_reason / a NULL rate means suppressed.
`recent_trend`	string		SCP’s trend call (‘stable’/‘rising’/‘falling’), or a text marker: ’*’ (trend not computable/suppressed) or ‘[P1 note]’ (state-law withholding). Landed verbatim; both markers become trend=NULL in measure.observation.
`recent_5_year_trend_in_rate`	string		Average Annual Percent Change (AAPC) point estimate, or the ’*‘/’[P1 note]’ markers (see recent_trend). Landed for reference, not derived.
`lower_ci_trend_in_rate`	string		AAPC’s 95% CI lower bound; see recent_5_year_trend_in_rate.
`upper_ci_trend_in_rate`	string		AAPC’s 95% CI upper bound; see recent_5_year_trend_in_rate.
`year`	string		SCP’s own period label – always the literal constant ‘Latest 5-year average’ in every row of every vintage (verified); carries no real year. See scp.py’s module docstring for where the real period comes from.
`sex`	string		‘Both Sexes’ \| ‘Male’ \| ‘Female’, as published.
`stage`	string		‘All Stages’ \| ‘Late Stage (Regional & Distant)’, as published. Absent from V3 (NULL on every V3 row) – SCP dropped this dimension from mortality starting with the 2026-08-24 scrape.
`race`	string		Source-native race/ethnicity category, as published (6 values; see the scraper’s select_options.json).
`cancer`	string		SCP’s cancer-site category label, as published (23 values, including combined categories like ‘Colon & Rectum’ – see select_options.json and scp.py’s SEER bridge).
`areatype`	string		SCP’s query-mode flag (‘By County’/‘By State’); NOT reliable for a row’s own geographic level – constant ‘By County’ even on the national aggregate row in V1. See locale_type.
`age`	string		Source-native age group, as published (7 values; see select_options.json).
`state_fips`	string		2-digit state FIPS code, or ‘00’ for the national row.
`measurement`	string		Topic marker, constant ‘mortality’ for this table.
`locale_type`	string		SCP’s own geography-type tag (‘county’/‘state’/‘national’/‘other’); NOT reliable for a row’s own geographic level – known to misclassify real counties (Louisiana parishes, Alaska boroughs, DC, Puerto Rico) as ‘other’. Geo level is derived from fips’s own shape instead (scp.py’s module docstring).
`_extracted_at`	string		ISO timestamp the scraper recorded for this row’s capture.
`url`	string		The exact statecancerprofiles.cancer.gov query URL the scraper captured this row from.
`suppression_reason`	string		‘suppressed_small_count’ \| ‘withheld_state_law’, or NULL when reported. Absent from V1/V2 (NULL on every row there) – those vintages carry no suppression marker at all (scp.py’s module docstring); V3’s own two values are the complete enum found in the real files – an unmapped value raises SystemExit in transform rather than a guess.
`locale`	string		Plain county/state name, footnote markers stripped (compare reported_locale).
`state`	string		Full state name, or NULL for a county-level row (the state is implied by fips).
`scp_vintage`	string	yes	Which vintage this row belongs to: ‘V1’ \| ‘V2’ \| ‘V3’ (scp.py’s module docstring). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	Cancer Basemap release that landed this row.

`raw.scp__risk`

State Cancer Profiles screening & risk factors (BRFSS-derived), landed verbatim and whole, V3 only – not published in V1/V2 (SPEC.md § Sources, #27). Land-only in this PR: not yet derived into measure.observation (scp.py’s module docstring ponytail note – its geography and race vocabulary need their own investigation before deriving it safely). This is a REPUBLISHED SCRAPE, not the original archive: statecancerprofiles.cancer.gov (NCI/CDC) has no API, bulk download or archive, so seandavi/state-cancer-profile-scraper scrapes it and republishes each captured vintage as a versioned Zenodo deposit, read here over anonymous HTTPS (#65). The underlying content is a U.S. Government work, public domain under 17 U.S.C. Sec 105; not endorsed by NCI/CDC.

Sorted by: scp_vintage, fips, topic, sex

Column	Type	Required	Doc
`reported_locale`	string		County/state name exactly as SCP renders it, including any footnote markers glued on; see locale/state for the plain name.
`fips`	string		5-digit FIPS code: a real county code for the District of Columbia/Puerto Rico rows only (BRFSS risk factors are not tabulated for ordinary US counties), a state code padded ‘000’, or the national sentinel ‘00000’.
`percent`	string		The published BRFSS prevalence percent. NULL when suppressed.
`lower_ci_percent`	string		95% CI lower bound, or NULL when suppressed.
`upper_ci_percent`	string		95% CI upper bound, or NULL when suppressed.
`respondents`	string		BRFSS survey respondent count underlying this estimate.
`topic`	string		Short topic-group code, e.g. ‘smoke’, ‘colorec’, ‘women’, ‘men’, ‘alcohol’, ‘dietex’, ‘vaccine’.
`topic_label`	string		Human-readable topic group, e.g. ‘Smoking’, ‘Colorectal Screening’.
`risk`	string		Short code for the specific risk/screening measure, e.g. ‘v505’.
`risk_label`	string		Human-readable label for the measure, e.g. ‘Binge drinking (4+ drinks on one occasion for women, 5+ … ), ages 21+’.
`race`	string		Source-native race/ethnicity category, as published – a DIFFERENT vocabulary than incidence/mortality’s race column (includes a verbatim upstream misspelling, ‘Asian /Pacifice Islander (Non-Hispanic)’); never harmonised.
`sex`	string		‘Both Sexes’ \| ‘Male’ \| ‘Female’, as published.
`datatype`	string		Estimation method tag; always ‘Direct Estimates’ in the landed file.
`statefips_query`	string		The state FIPS value SCP’s own query form used to produce this row (not necessarily this row’s own geography).
`state_fips`	string		2-digit state FIPS code, or ‘00’ for the national row.
`locale_type`	string		SCP’s own geography-type tag; real county-level rows exist only for DC/Puerto Rico (BRFSS has no ordinary county estimates) – see scp.py’s module docstring ponytail note on why this topic isn’t derived yet.
`_extracted_at`	string		ISO timestamp the scraper recorded for this row’s capture.
`url`	string		The exact statecancerprofiles.cancer.gov query URL the scraper captured this row from.
`suppression_reason`	string		‘suppressed_small_count’, or NULL when reported (the complete enum found in the real V3 risk file; an unmapped value would raise SystemExit if this topic were derived).
`model_based_percent3`	string		A separate model-based estimate variant published alongside the direct estimate; landed for reference, not derived.
`scp_vintage`	string	yes	Which vintage this row belongs to; always ‘V3’ – risk is not published in V1/V2 (scp.py’s module docstring). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	Cancer Basemap release that landed this row.

`raw.sdwis__geographic_areas`

EPA SDWIS Federal: every county/city/zip/tribal area each public water system reports serving, landed verbatim and whole, replaced wholesale per SUBMISSIONYEARQUARTER (SPEC.md § Sources — second tranche). A system serving several counties has one row per county. Public domain (17 U.S.C. § 105).

Sorted by: SUBMISSIONYEARQUARTER, PWSID, GEO_ID

Column	Type	Required	Doc
`SUBMISSIONYEARQUARTER`	string	yes	This source’s version axis, e.g. ‘2026Q2’. Raw is replaced wholesale per value of this column.
`PWSID`	string	yes	Public water system id.
`GEO_ID`	string		EPA’s own system-generated id for this (PWSID, area) record – unrelated to Cancer Basemap’s own geo_id convention used elsewhere in this catalog.
`AREA_TYPE_CODE`	string		TR tribal, CN county, ZC zip code, CT city, IR Indian reservation, or NULL/unknown. Only CN rows are used to derive county measures.
`TRIBAL_CODE`	string		EPA code for the Indian reservation or Alaska Native village.
`STATE_SERVED`	string		State the facility is serving, per EPA’s own documentation – empty on every CN (county) row observed in the real 2026Q2 download; epa_sdwis.py derives the state from PWSID’s own two-letter prefix instead (see its module docstring).
`ANSI_ENTITY_CODE`	string		ANSI/FIPS county entity code, 3-digit zero-padded. Paired with the state implied by PWSID’s prefix, via raw.sdwis__ref_ansi_areas, to build a county FIPS code. NULL on non-county rows; on some CN rows it is populated but does not match any real county for that state (bad upstream data) – excluded and reported, never guessed.
`ZIP_CODE_SERVED`	string		ZIP code served, on ZC rows.
`CITY_SERVED`	string		City name served, on CT rows.
`COUNTY_SERVED`	string		County name as reported; sometimes NULL even when ANSI_ENTITY_CODE is populated. Not used for the FIPS derivation, kept for reference.
`LAST_REPORTED_DATE`	string		Last reported date.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.sdwis__pub_water_systems`

EPA SDWIS Federal public water systems, landed verbatim and whole (minus nine individual columns – ORG_NAME, ADDRESS_LINE1/2 and six admin-contact fields – excluded – see epa_sdwis.py). One row per PWSID, replaced wholesale per SUBMISSIONYEARQUARTER (SPEC.md § Sources — second tranche). Public domain (17 U.S.C. § 105).

Sorted by: SUBMISSIONYEARQUARTER, PWSID

Column	Type	Required	Doc
`SUBMISSIONYEARQUARTER`	string	yes	Fiscal year and quarter of this quarterly SDWIS snapshot, e.g. ‘2026Q2’ – this source’s version axis. Raw is replaced wholesale per value of this column.
`PWSID`	string	yes	Public water system id: a two-letter state, territory, or numeric EPA-region code, followed by seven digits, e.g. ‘CT1680051’.
`PWS_NAME`	string		Water system name.
`PRIMACY_AGENCY_CODE`	string		Two-character state/territory code, or a numeric EPA Region code, of the agency with primary enforcement responsibility.
`EPA_REGION`	string		EPA Region number.
`SEASON_BEGIN_DATE`	string		Opening month/day of a seasonal system’s service period.
`SEASON_END_DATE`	string		Closing month/day of a seasonal system’s service period.
`PWS_ACTIVITY_CODE`	string		Current activity status: A active, I inactive, N never operated, M merged/consolidated, P potential future system. A current-snapshot field, not a per-year history – see module docstring.
`PWS_DEACTIVATION_DATE`	string		Date the system was reported closed/deactivated.
`PWS_TYPE_CODE`	string		CWS community, TNCWS transient non-community, NTNCWS non-transient non-community, or NP.
`DBPR_SCHEDULE_CAT_CODE`	string		Stage 2 Disinfectant Byproducts Rule monitoring category.
`CDS_ID`	string		Combined distribution system id.
`GW_SW_CODE`	string		Groundwater or surface water source.
`LT2_SCHEDULE_CAT_CODE`	string		Long Term 2 Enhanced Surface Water Treatment Rule category.
`OWNER_TYPE_CODE`	string		Ownership: F federal, L local, M public/private, N native American, P private, S state.
`POPULATION_SERVED_COUNT`	string		Estimated average daily population served, as of this snapshot – not a per-year historical figure (module docstring).
`POP_CAT_2_CODE`	string		Population-size category (2 tiers).
`POP_CAT_3_CODE`	string		Population-size category (3 tiers).
`POP_CAT_4_CODE`	string		Population-size category (4 tiers).
`POP_CAT_5_CODE`	string		Population-size category (5 tiers).
`POP_CAT_11_CODE`	string		Population-size category (11 tiers).
`PRIMACY_TYPE`	string		State, tribal, territorial, or EPA-direct primacy regulation.
`PRIMARY_SOURCE_CODE`	string		Primary water source, e.g. GW, SW, GU, GWP, SWP.
`IS_GRANT_ELIGIBLE_IND`	string		Grant eligibility indicator.
`IS_WHOLESALER_IND`	string		Wholesaler status indicator.
`IS_SCHOOL_OR_DAYCARE_IND`	string		School-or-daycare service-area indicator.
`SERVICE_CONNECTIONS_COUNT`	string		Number of service connections.
`SUBMISSION_STATUS_CODE`	string		Reported/unreported/rejected submission status.
`CITY_NAME`	string		City.
`ZIP_CODE`	string		USPS ZIP code.
`COUNTRY_CODE`	string		Two-character country code.
`FIRST_REPORTED_DATE`	string		First reported date for the system.
`LAST_REPORTED_DATE`	string		Last reported date for the system.
`STATE_CODE`	string		USPS state abbreviation of the system’s address – a mailing address, not necessarily the state of the geography it serves (see raw.sdwis__geographic_areas); can be NULL or non-US for a handful of systems.
`SOURCE_WATER_PROTECTION_CODE`	string		Source water protection implementation status.
`SOURCE_PROTECTION_BEGIN_DATE`	string		Date source water protection was substantially implemented.
`OUTSTANDING_PERFORMER`	string		Outstanding-performer criteria compliance.
`OUTSTANDING_PERFORM_BEGIN_DATE`	string		Date outstanding-performer criteria was met.
`REDUCED_RTCR_MONITORING`	string		Reduced Revised Total Coliform Rule monitoring frequency.
`REDUCED_MONITORING_BEGIN_DATE`	string		Start date of reduced monitoring.
`REDUCED_MONITORING_END_DATE`	string		End date of reduced monitoring.
`SEASONAL_STARTUP_SYSTEM`	string		Seasonal pressurization/startup status.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.sdwis__ref_ansi_areas`

EPA’s own ANSI/FIPS county reference table, bundled in the same SDWA bulk download – the authority epa_sdwis.py uses to turn a (PWSID prefix, ANSI_ENTITY_CODE) pair into a real county FIPS code, and to catch the ones that do not correspond to any real county (SPEC.md’s ‘report the unmatched rate honestly’ rule). Not itself versioned per quarter; replaced wholesale each release, the same pattern as raw.census__state_fips. Public domain (17 U.S.C. § 105).

Sorted by: ANSI_STATE_CODE, ANSI_ENTITY_CODE

Column	Type	Required	Doc
`ANSI_STATE_CODE`	string	yes	2-digit ANSI/FIPS state code, zero-padded, e.g. ‘09’ for Connecticut.
`ANSI_ENTITY_CODE`	string	yes	3-digit ANSI/FIPS county entity code, zero-padded, e.g. ‘001’.
`ANSI_NAME`	string		County (or equivalent) name.
`STATE_CODE`	string	yes	USPS state postal abbreviation, e.g. ‘CT’. Joined against raw.sdwis__geographic_areas’ PWSID prefix in epa_sdwis.py, since that table’s own STATE_SERVED column is empty on county rows.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.sdwis__violations_enforcement`

EPA SDWIS Federal violation+enforcement records, landed verbatim and whole, replaced wholesale per SUBMISSIONYEARQUARTER (SPEC.md § Sources — second tranche). Grain is (violation, enforcement action) – see VIOLATION_ID’s doc for why a violation count must dedupe. Millions of rows; landed in batches (epa_sdwis.py, ported from bioc-on-ice’s ncbi.py::_land). Public domain (17 U.S.C. § 105).

Sorted by: SUBMISSIONYEARQUARTER, PWSID, VIOLATION_ID

Column	Type	Required	Doc
`SUBMISSIONYEARQUARTER`	string	yes	This source’s version axis, e.g. ‘2026Q2’. Raw is replaced wholesale per value of this column.
`PWSID`	string	yes	Public water system id.
`VIOLATION_ID`	string		System-generated violation id; NULL on enforcement-only rows with no associated violation. (PWSID, VIOLATION_ID) identifies one violation but is NOT this table’s row key: a violation with several enforcement actions repeats across several rows sharing the same (PWSID, VIOLATION_ID) and a different ENFORCEMENT_ID – verified against the real 2026Q2 file, whose 15,432,737 rows compress to 5,514,271 distinct (PWSID, VIOLATION_ID) pairs. Deriving a count of violations must count DISTINCT (PWSID, VIOLATION_ID), never rows.
`FACILITY_ID`	string		Facility id within the water system.
`COMPL_PER_BEGIN_DATE`	string		Compliance period begin date.
`COMPL_PER_END_DATE`	string		Compliance period end date.
`NON_COMPL_PER_BEGIN_DATE`	string		Noncompliance period begin date – the violation-year axis epa_sdwis.py derives measure.observation’s period_start/period_end from. Verified constant within a (PWSID, VIOLATION_ID) group.
`NON_COMPL_PER_END_DATE`	string		Noncompliance period end date.
`PWS_DEACTIVATION_DATE`	string		System deactivation date, if any.
`VIOLATION_CODE`	string		Violation type code.
`VIOLATION_CATEGORY_CODE`	string		Category: TT, MRDL, MCL, MR, MON, RPT, etc.
`IS_HEALTH_BASED_IND`	string		‘Y’ for a health-based violation, ‘N’ or NULL otherwise. epa_sdwis.py’s derived measure counts ‘Y’ only. Verified constant within a (PWSID, VIOLATION_ID) group.
`CONTAMINANT_CODE`	string		Contaminant code.
`VIOL_MEASURE`	string		Analytical result value, unparsed.
`UNIT_OF_MEASURE`	string		Unit of VIOL_MEASURE.
`FEDERAL_MCL`	string		Federal maximum contaminant level exceeded.
`STATE_MCL`	string		State maximum contaminant level exceeded.
`IS_MAJOR_VIOL_IND`	string		Major/minor designation for MR violations.
`SEVERITY_IND_CNT`	string		Severity count for certain DBPR/IESWTR violations.
`CALCULATED_RTC_DATE`	string		Date the system returned to compliance.
`VIOLATION_STATUS`	string		Resolved, Archived, Addressed, or Unaddressed.
`PUBLIC_NOTIFICATION_TIER`	string		Public notification tier.
`CALCULATED_PUB_NOTIF_TIER`	string		Calculated public notification tier.
`VIOL_ORIGINATOR_CODE`	string		F federal, H state, R reporting agency, S state.
`SAMPLE_RESULT_ID`	string		Reporting jurisdiction’s sample-result id.
`CORRECTIVE_ACTION_ID`	string		Corrective action id.
`RULE_CODE`	string		National Drinking Water rule code.
`RULE_GROUP_CODE`	string		Rule group code.
`RULE_FAMILY_CODE`	string		Rule family code.
`VIOL_FIRST_REPORTED_DATE`	string		Date the violation was first reported.
`VIOL_LAST_REPORTED_DATE`	string		Date the violation was last reported.
`ENFORCEMENT_ID`	string		Id of one enforcement action; several can exist per (PWSID, VIOLATION_ID) – see VIOLATION_ID’s doc.
`ENFORCEMENT_DATE`	string		Enforcement action date.
`ENFORCEMENT_ACTION_TYPE_CODE`	string		Enforcement action type.
`ENF_ACTION_CATEGORY`	string		Formal, Informal, or Resolving.
`ENF_ORIGINATOR_CODE`	string		F federal, H state, R reporting agency, S state.
`ENF_FIRST_REPORTED_DATE`	string		Date the enforcement action was first reported.
`ENF_LAST_REPORTED_DATE`	string		Date the enforcement action was last reported.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.seer__cod_recode`

SEER Cause of Death Recode 1969+, ‘Neoplasm Causes of Death’ table only (the source file’s other two tables – non-neoplasm causes, and administrative codes – are out of scope for a cancer-site bridge), landed verbatim and whole (SPEC.md § measure.cancer_site). Public domain (NCI/U.S. Government work).

Sorted by: cod_recode_edition, row_order

Column	Type	Required	Doc
`cod_group`	string	yes	Cause-of-death group label, exactly as published – including the source’s own leading-space indentation.
`icd8`	string		ICD-8 range, unparsed. Usually blank – this table’s own header carries the column but most rows only state ICD-9/ICD-10.
`icd9`	string		ICD-9 (1979-1998) range, unparsed.
`icd10`	string		ICD-10 (1999+) range, unparsed.
`recode`	string		The numeric recode code, as published. Blank for a group heading; the literal sentinel ‘–’ for ‘All Malignant Cancers’, which has no code of its own (SCP’s FAQ: ‘All Cancers refers to all invasive cancers combined’).
`row_order`	int	yes	0-based position within the ‘Neoplasm Causes of Death’ table in the source file.
`cod_recode_edition`	string	yes	Which SEER Cause of Death Recode edition this row came from, e.g. ‘1969_d03012018’ (COD Recode 1969+, current as of 03/01/2018 – the edition State Cancer Profiles’ own FAQ names for mortality). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.seer__site_recode`

SEER Site Recode ICD-O-3/WHO 2008, landed verbatim and whole from the source’s own semicolon-delimited text file (SPEC.md § measure.cancer_site). Public domain (NCI/U.S. Government work).

Sorted by: site_recode_edition, row_order

Column	Type	Required	Doc
`site_group`	string	yes	Site/group label, exactly as published – including the source’s own leading-space indentation (4 spaces per nesting level), its only hierarchy marker.
`icdo3_site`	string		ICD-O-3 topography range for this row, unparsed. Blank for a group heading rather than a site (e.g. ‘Colon and Rectum’).
`icdo3_histology`	string		ICD-O-3 histology qualifier for this row, unparsed – an exclusion range (e.g. ‘excluding 9050-9055, 9140, 9590-9993’) for most codes, an inclusion range for a few (e.g. Melanoma’s ‘8720-8790’).
`recode`	string		The numeric site-recode code, as published (a trailing space on some rows is a real upstream artifact, kept verbatim). Blank for a group heading. A code can be defined by more than one row (e.g. 31040 has two: see module docstring); all land here.
`row_order`	int	yes	0-based position in the source file, preserved so multi-row code definitions concatenate in publication order.
`site_recode_edition`	string	yes	Which SEER site-recode edition this row came from, e.g. ‘icdo3_dwhoheme’ (Site Recode ICD-O-3/WHO 2008 – the edition State Cancer Profiles’ own FAQ names for incidence). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.superfund__npl_frs`

EPA Facility Registry Service’s own NPL subset (FRS_INTERESTS_SEMS_NPL), landed verbatim and whole – the source of facility.site’s county FIPS for EPA_SUPERFUND, joined to raw.superfund__npl_status on the shared EPA site id (epa_superfund.py module docstring). Public domain – 17 U.S.C. § 105.

Sorted by: retrieved_on, PGM_SYS_ID

Column	Type	Required	Doc
`REGISTRY_ID`	string	yes	EPA Facility Registry Service’s own cross-program facility id. facility.site.attributes_json’s ‘registry_id’ key.
`PRIMARY_NAME`	string		FRS’s own facility name.
`LOCATION_ADDRESS`	string		Street address; part of facility.site.address when this row matches a status-layer site.
`CITY_NAME`	string		Part of facility.site.address.
`COUNTY_NAME`	string		County name, as published.
`FIPS_CODE`	string		County FIPS code, landed exactly as published – NOT consistently zero-padded (e.g. ‘9003’ vs ‘01013’, verified 2026-09-18) and not always a real FIPS code at all (9 live rows carry a state postal abbreviation glued to a county code, e.g. ‘NJ017’, or garbage like ‘S’, verified 2026-09-19 – see epa_superfund.py module docstring). facility.site.geo_id is ‘county:’+lpad(this, 5, ‘0’) only after validating this matches [0-9]{1,5}; otherwise geo_id is NULL, not guessed. 2010-vintage geography (Connecticut rows carry its eight legacy counties, never the nine 2022 planning regions – same marker epa_sdwis.py’s ANSI reference uses for its own GEO_VINTAGE=2010).
`STATE_CODE`	string		USPS state/territory abbreviation; part of facility.site.address.
`POSTAL_CODE`	string		ZIP code; part of facility.site.address.
`LATITUDE83`	double		WGS84/NAD83 latitude – landed for reference; facility.site.lat comes from raw.superfund__npl_status.Latitude instead (populated on every site, not only FRS-matched ones; see module docstring).
`LONGITUDE83`	double		WGS84/NAD83 longitude; see LATITUDE83’s doc.
`HUC8_CODE`	string		8-digit hydrologic unit code, or NULL.
`ACCURACY_VALUE`	int		Geocoding accuracy value, or NULL.
`COLLECT_MTH_DESC`	string		Coordinate collection method, or NULL.
`REF_POINT_DESC`	string		Reference point description, or NULL.
`CREATE_DATE`	string		FRS record creation timestamp (epoch milliseconds, unparsed text).
`UPDATE_DATE`	string		FRS record last-update timestamp (epoch milliseconds, unparsed text).
`LAST_REPORTED_DATE`	string		Last-reported timestamp (epoch milliseconds, unparsed text), or NULL.
`FAC_URL`	string		Link to the facility’s FRS detail page.
`PGM_SYS_ID`	string	yes	EPA’s per-site id in this program system – the same id as raw.superfund__npl_status.Site_EPA_ID; the join key.
`PGM_SYS_ACRNM`	string		Program system acronym, constant ‘SEMS’ for this layer.
`INTEREST_TYPE`	string		Constant ‘SUPERFUND NPL’ for this layer.
`PROGRAM_URL`	string		Link to the Superfund program page.
`PGM_REPORT_URL`	string		Program report link, or ‘no data yet’.
`PUBLIC_IND`	string		‘Y’ if publicly visible, as published.
`ACTIVE_STATUS`	string		‘CURRENTLY ON THE FINAL NPL’ \| ‘PROPOSED FOR NPL’ \| ‘DELETED FROM THE FINAL NPL’ – FRS’s own status text, not derived from.
`FEDERAL_AGENCY_NAME`	string		Responsible federal agency for a federal facility, or NULL.
`HUC_12`	string		12-digit hydrologic unit code, or NULL.
`FEDERAL_LAND_IND`	string		Federal-land indicator, or NULL.
`FED_FACILITY_CODE`	string		Federal-facility code, or NULL.
`EPA_REGION_CODE`	string		2-digit EPA region code.
`KEY_FIELD`	string		FRS’s own composite key, e.g. ‘SEMSCTD009717604’.
`retrieved_on`	string	yes	ISO date this snapshot was retrieved; see raw.superfund__npl_status.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.superfund__npl_status`

EPA Superfund National Priorities List sites with status (proposed / final / deleted), landed verbatim and whole from the ‘Superfund National Priorities List (NPL) Sites with Status Information’ ArcGIS Feature Service (EPA’s own ‘Where You Live’ page dataset). Public domain; the service’s own licenseInfo states ‘Access Constraints: None’ (checked 2026-09-18). Joined against raw.superfund__npl_frs for county FIPS – see epa_superfund.py module docstring.

Sorted by: retrieved_on, Site_EPA_ID

Column	Type	Required	Doc
`Site_Name`	string		Site’s own name; facility.site.name.
`Site_Score`	double		Hazard Ranking System score; facility.site.attributes_json’s ‘site_score’ key.
`Site_EPA_ID`	string	yes	EPA’s own per-site id (e.g. ‘CTD009717604’) – verified unique across the whole live file (2026-09-18); joined against raw.superfund__npl_frs.PGM_SYS_ID and this is facility.site.facility_id’s ‘EPA_SUPERFUND:’+this.
`SEMS_ID`	int		SEMS internal numeric site id.
`SITS_ID`	int		Superfund Information Tracking System id.
`Region_ID`	int		EPA region number (1-10); facility.site.attributes_json’s ‘region_id’ key.
`State`	string		Full state/territory name, as published.
`City`	string		City, as published.
`County`	string		County name(s) as free text, not a FIPS code – some sites span more than one (e.g. ‘Limestone, Madison, Morgan’); see raw.superfund__npl_frs.FIPS_CODE for the single county FIPS this module derives geo_id from. facility.site.attributes_json’s ‘county_name’ key.
`Status`	string		‘NPL Site’ \| ‘Proposed NPL Site’ \| ‘Deleted NPL Site’. facility.site.attributes_json’s ‘status’ key.
`Longitude`	double		WGS84 longitude; facility.site.lon.
`Latitude`	double		WGS84 latitude; facility.site.lat.
`Proposed_Date`	string		Date proposed to the NPL, unparsed (M/D/YYYY as published). facility.site.attributes_json’s ‘proposed_date’ key – see module docstring on why this lands in attributes_json, not source_release (issue #19).
`Listing_Date`	string		Date finalized on the NPL, unparsed. attributes_json’s ‘listing_date’ key.
`Construction_Completion_Date`	string		Date remedial construction was completed, unparsed, or NULL. attributes_json’s ‘construction_completion_date’ key.
`Construction_Completion_Number`	int		EPA’s sequential Construction Completion List number, or NULL.
`NOID_Date`	string		Notice of Intent to Delete date, unparsed, or NULL. attributes_json’s ‘noid_date’ key.
`Deletion_Date`	string		Date deleted from the NPL, unparsed, or NULL. attributes_json’s ‘deletion_date’ key.
`Site_Listing_Narrative`	string		HTML link to the site’s listing narrative PDF, as published.
`Site_Progress_Profile`	string		HTML link to the site’s EPA cleanup-progress page, as published.
`Notice_of_Data_Availability`	string		HTML link to a Notice of Data Availability, or NULL.
`Proposed_FR_Notice`	string		HTML link to the proposal’s Federal Register notice, or NULL.
`Deletion_FR_Notice`	string		HTML link to the deletion’s Federal Register notice, or NULL.
`Final_FR_Notice`	string		HTML link to the final-listing Federal Register notice, or NULL.
`NOID_FR_Notice`	string		HTML link to the NOID’s Federal Register notice, or NULL.
`Restoration_FR_Notice_Jumper_Page`	string		HTML link to a restoration Federal Register notice, or NULL.
`Site_has_had_a_Partial_Deletion`	string		‘Yes’ (as an HTML link) or ‘No’, as published. attributes_json’s ‘partial_deletion’ key.
`retrieved_on`	string	yes	ISO date this snapshot was retrieved – SEMS publishes no edition label (module docstring); raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.svi__county`

CDC/ATSDR Social Vulnerability Index county file landed verbatim and whole, one row per county per edition (SPEC.md § Sources – first tranche). Union of the two real layouts this module lands (2014-family, 2020-family; module docstring) – a column absent from an edition’s own layout is NULL for that edition. Public domain (17 U.S.C. § 105; https://www.cdc.gov/other/agencymaterials.html).

Sorted by: svi_edition, FIPS

Column	Type	Required	Doc
`ST`	string		2-digit state FIPS code.
`STATE`	string		State name, as published (case varies by edition: uppercase through 2018, title case from 2020).
`ST_ABBR`	string		2-letter USPS state abbreviation.
`STCNTY`	string		5-digit state+county FIPS code. Equal to FIPS at county level; at tract level, the containing county’s code.
`COUNTY`	string		County (or county-equivalent) name, as published.
`FIPS`	string	yes	Geographic identifier: 5-digit county FIPS in raw.svi__county, 11-digit tract FIPS in raw.svi__tract.
`LOCATION`	string		Human-readable location name, e.g. ‘Autauga County, Alabama’ (county) or ‘Census Tract 4001.01; Capitol Planning Region; Connecticut’ (tract).
`AREA_SQMI`	string		Land area of the unit, square miles, as published.
`E_TOTPOP`	string		ACS/Census estimate (count): total population.
`M_TOTPOP`	string		Margin of error (90% confidence) for the paired E_ estimate: total population.
`E_HU`	string		ACS/Census estimate (count): total housing units.
`M_HU`	string		Margin of error (90% confidence) for the paired E_ estimate: total housing units.
`E_HH`	string		ACS/Census estimate (count): total households.
`M_HH`	string		Margin of error (90% confidence) for the paired E_ estimate: total households.
`E_POV150`	string		ACS/Census estimate (count): persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018).
`M_POV150`	string		Margin of error (90% confidence) for the paired E_ estimate: persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018).
`E_UNEMP`	string		ACS/Census estimate (count): civilian (age 16+) population unemployed.
`M_UNEMP`	string		Margin of error (90% confidence) for the paired E_ estimate: civilian (age 16+) population unemployed.
`E_HBURD`	string		ACS/Census estimate (count): occupied housing units spending 30% or more of household income on housing costs (2020 edition onward).
`M_HBURD`	string		Margin of error (90% confidence) for the paired E_ estimate: occupied housing units spending 30% or more of household income on housing costs (2020 edition onward).
`E_NOHSDP`	string		ACS/Census estimate (count): persons age 25+ with no high school diploma.
`M_NOHSDP`	string		Margin of error (90% confidence) for the paired E_ estimate: persons age 25+ with no high school diploma.
`E_UNINSUR`	string		ACS/Census estimate (count): civilian noninstitutionalized population with no health insurance.
`M_UNINSUR`	string		Margin of error (90% confidence) for the paired E_ estimate: civilian noninstitutionalized population with no health insurance.
`E_AGE65`	string		ACS/Census estimate (count): persons aged 65 and older.
`M_AGE65`	string		Margin of error (90% confidence) for the paired E_ estimate: persons aged 65 and older.
`E_AGE17`	string		ACS/Census estimate (count): persons aged 17 and under.
`M_AGE17`	string		Margin of error (90% confidence) for the paired E_ estimate: persons aged 17 and under.
`E_DISABL`	string		ACS/Census estimate (count): civilian noninstitutionalized population with a disability.
`M_DISABL`	string		Margin of error (90% confidence) for the paired E_ estimate: civilian noninstitutionalized population with a disability.
`E_SNGPNT`	string		ACS/Census estimate (count): single-parent households.
`M_SNGPNT`	string		Margin of error (90% confidence) for the paired E_ estimate: single-parent households.
`E_LIMENG`	string		ACS/Census estimate (count): persons age 5+ who speak English “less than well”.
`M_LIMENG`	string		Margin of error (90% confidence) for the paired E_ estimate: persons age 5+ who speak English “less than well”.
`E_MINRTY`	string		ACS/Census estimate (count): minority population (all persons except white, non-Hispanic).
`M_MINRTY`	string		Margin of error (90% confidence) for the paired E_ estimate: minority population (all persons except white, non-Hispanic).
`E_MUNIT`	string		ACS/Census estimate (count): housing units in structures with 10 or more units.
`M_MUNIT`	string		Margin of error (90% confidence) for the paired E_ estimate: housing units in structures with 10 or more units.
`E_MOBILE`	string		ACS/Census estimate (count): mobile homes.
`M_MOBILE`	string		Margin of error (90% confidence) for the paired E_ estimate: mobile homes.
`E_CROWD`	string		ACS/Census estimate (count): occupied housing units with more people than rooms.
`M_CROWD`	string		Margin of error (90% confidence) for the paired E_ estimate: occupied housing units with more people than rooms.
`E_NOVEH`	string		ACS/Census estimate (count): households with no vehicle available.
`M_NOVEH`	string		Margin of error (90% confidence) for the paired E_ estimate: households with no vehicle available.
`E_GROUPQ`	string		ACS/Census estimate (count): persons in group quarters.
`M_GROUPQ`	string		Margin of error (90% confidence) for the paired E_ estimate: persons in group quarters.
`EP_POV150`	string		ACS/Census percent estimate: persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018), as a percentage of the relevant universe.
`MP_POV150`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018).
`EP_UNEMP`	string		ACS/Census percent estimate: civilian (age 16+) population unemployed, as a percentage of the relevant universe.
`MP_UNEMP`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: civilian (age 16+) population unemployed.
`EP_HBURD`	string		ACS/Census percent estimate: occupied housing units spending 30% or more of household income on housing costs (2020 edition onward), as a percentage of the relevant universe.
`MP_HBURD`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: occupied housing units spending 30% or more of household income on housing costs (2020 edition onward).
`EP_NOHSDP`	string		ACS/Census percent estimate: persons age 25+ with no high school diploma, as a percentage of the relevant universe.
`MP_NOHSDP`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons age 25+ with no high school diploma.
`EP_UNINSUR`	string		ACS/Census percent estimate: civilian noninstitutionalized population with no health insurance, as a percentage of the relevant universe.
`MP_UNINSUR`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: civilian noninstitutionalized population with no health insurance.
`EP_AGE65`	string		ACS/Census percent estimate: persons aged 65 and older, as a percentage of the relevant universe.
`MP_AGE65`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons aged 65 and older.
`EP_AGE17`	string		ACS/Census percent estimate: persons aged 17 and under, as a percentage of the relevant universe.
`MP_AGE17`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons aged 17 and under.
`EP_DISABL`	string		ACS/Census percent estimate: civilian noninstitutionalized population with a disability, as a percentage of the relevant universe.
`MP_DISABL`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: civilian noninstitutionalized population with a disability.
`EP_SNGPNT`	string		ACS/Census percent estimate: single-parent households, as a percentage of the relevant universe.
`MP_SNGPNT`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: single-parent households.
`EP_LIMENG`	string		ACS/Census percent estimate: persons age 5+ who speak English “less than well”, as a percentage of the relevant universe.
`MP_LIMENG`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons age 5+ who speak English “less than well”.
`EP_MINRTY`	string		ACS/Census percent estimate: minority population (all persons except white, non-Hispanic), as a percentage of the relevant universe.
`MP_MINRTY`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: minority population (all persons except white, non-Hispanic).
`EP_MUNIT`	string		ACS/Census percent estimate: housing units in structures with 10 or more units, as a percentage of the relevant universe.
`MP_MUNIT`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: housing units in structures with 10 or more units.
`EP_MOBILE`	string		ACS/Census percent estimate: mobile homes, as a percentage of the relevant universe.
`MP_MOBILE`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: mobile homes.
`EP_CROWD`	string		ACS/Census percent estimate: occupied housing units with more people than rooms, as a percentage of the relevant universe.
`MP_CROWD`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: occupied housing units with more people than rooms.
`EP_NOVEH`	string		ACS/Census percent estimate: households with no vehicle available, as a percentage of the relevant universe.
`MP_NOVEH`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: households with no vehicle available.
`EP_GROUPQ`	string		ACS/Census percent estimate: persons in group quarters, as a percentage of the relevant universe.
`MP_GROUPQ`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons in group quarters.
`EPL_POV150`	string		Percentile rank (0-1) of persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018), among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_UNEMP`	string		Percentile rank (0-1) of civilian (age 16+) population unemployed, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_HBURD`	string		Percentile rank (0-1) of occupied housing units spending 30% or more of household income on housing costs (2020 edition onward), among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_NOHSDP`	string		Percentile rank (0-1) of persons age 25+ with no high school diploma, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_UNINSUR`	string		Percentile rank (0-1) of civilian noninstitutionalized population with no health insurance, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`SPL_THEME1`	string		Sum of theme 1’s EPL_ percentile-rank components. Theme 1 is Socioeconomic Status (poverty, unemployment, income, education) in the 2014/2016/2018 editions, or Socioeconomic Status (poverty, unemployment, housing cost burden, education, uninsured) in 2020/2022.
`RPL_THEME1`	string		Percentile ranking (0-1) for theme 1, among all units landed in this edition. Theme 1 is Socioeconomic Status (poverty, unemployment, income, education) in the 2014/2016/2018 editions, or Socioeconomic Status (poverty, unemployment, housing cost burden, education, uninsured) in 2020/2022; derived into measure.observation as ‘SVI:RPL_THEME1:’.
`EPL_AGE65`	string		Percentile rank (0-1) of persons aged 65 and older, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_AGE17`	string		Percentile rank (0-1) of persons aged 17 and under, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_DISABL`	string		Percentile rank (0-1) of civilian noninstitutionalized population with a disability, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_SNGPNT`	string		Percentile rank (0-1) of single-parent households, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_LIMENG`	string		Percentile rank (0-1) of persons age 5+ who speak English “less than well”, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`SPL_THEME2`	string		Sum of theme 2’s EPL_ percentile-rank components. Theme 2 is Household Composition & Disability (age 65+, age 17-, disability, single-parent households) in the 2014/2016/2018 editions, or Household Characteristics (age 65+, age 17-, disability, single-parent households, limited English) in 2020/2022.
`RPL_THEME2`	string		Percentile ranking (0-1) for theme 2, among all units landed in this edition. Theme 2 is Household Composition & Disability (age 65+, age 17-, disability, single-parent households) in the 2014/2016/2018 editions, or Household Characteristics (age 65+, age 17-, disability, single-parent households, limited English) in 2020/2022; derived into measure.observation as ‘SVI:RPL_THEME2:’.
`EPL_MINRTY`	string		Percentile rank (0-1) of minority population (all persons except white, non-Hispanic), among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`SPL_THEME3`	string		Sum of theme 3’s EPL_ percentile-rank components. Theme 3 is Minority Status & Language (minority population, limited English) in the 2014/2016/2018 editions, or Racial & Ethnic Minority Status (minority population) in 2020/2022.
`RPL_THEME3`	string		Percentile ranking (0-1) for theme 3, among all units landed in this edition. Theme 3 is Minority Status & Language (minority population, limited English) in the 2014/2016/2018 editions, or Racial & Ethnic Minority Status (minority population) in 2020/2022; derived into measure.observation as ‘SVI:RPL_THEME3:’.
`EPL_MUNIT`	string		Percentile rank (0-1) of housing units in structures with 10 or more units, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_MOBILE`	string		Percentile rank (0-1) of mobile homes, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_CROWD`	string		Percentile rank (0-1) of occupied housing units with more people than rooms, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_NOVEH`	string		Percentile rank (0-1) of households with no vehicle available, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_GROUPQ`	string		Percentile rank (0-1) of persons in group quarters, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`SPL_THEME4`	string		Sum of theme 4’s EPL_ percentile-rank components. Theme 4 is Housing Type & Transportation (multi-unit housing, mobile homes, crowding, no vehicle, group quarters) in the 2014/2016/2018 editions, or Housing Type & Transportation (multi-unit housing, mobile homes, crowding, no vehicle, group quarters) in 2020/2022.
`RPL_THEME4`	string		Percentile ranking (0-1) for theme 4, among all units landed in this edition. Theme 4 is Housing Type & Transportation (multi-unit housing, mobile homes, crowding, no vehicle, group quarters) in the 2014/2016/2018 editions, or Housing Type & Transportation (multi-unit housing, mobile homes, crowding, no vehicle, group quarters) in 2020/2022; derived into measure.observation as ‘SVI:RPL_THEME4:’.
`SPL_THEMES`	string		Sum of SPL_THEME1-4 (theme sub-scores).
`RPL_THEMES`	string		Overall SVI percentile ranking (0-1) across all four themes, among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEMES:’ (family ‘2014’ for the 2014/2016/2018 editions, ‘2020’ for 2020/2022 – theme composition differs between them; see measure.definition.doc).
`F_POV150`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018))
`F_UNEMP`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (civilian (age 16+) population unemployed)
`F_HBURD`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (occupied housing units spending 30% or more of household income on housing costs (2020 edition onward))
`F_NOHSDP`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons age 25+ with no high school diploma)
`F_UNINSUR`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (civilian noninstitutionalized population with no health insurance)
`F_THEME1`	string		Flag: 1 if theme 1’s RPL_THEME1 is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed.
`F_AGE65`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons aged 65 and older)
`F_AGE17`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons aged 17 and under)
`F_DISABL`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (civilian noninstitutionalized population with a disability)
`F_SNGPNT`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (single-parent households)
`F_LIMENG`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons age 5+ who speak English “less than well”)
`F_THEME2`	string		Flag: 1 if theme 2’s RPL_THEME2 is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed.
`F_MINRTY`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (minority population (all persons except white, non-Hispanic))
`F_THEME3`	string		Flag: 1 if theme 3’s RPL_THEME3 is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed.
`F_MUNIT`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (housing units in structures with 10 or more units)
`F_MOBILE`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (mobile homes)
`F_CROWD`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (occupied housing units with more people than rooms)
`F_NOVEH`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (households with no vehicle available)
`F_GROUPQ`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons in group quarters)
`F_THEME4`	string		Flag: 1 if theme 4’s RPL_THEME4 is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed.
`F_TOTAL`	string		Flag: 1 if RPL_THEMES is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed.
`E_DAYPOP`	string		ACS/Census estimate (count): daytime population estimate.
`E_NOINT`	string		ACS/Census estimate (count): households with no internet access (2020 edition onward).
`M_NOINT`	string		Margin of error (90% confidence) for the paired E_ estimate: households with no internet access (2020 edition onward).
`E_AFAM`	string		ACS/Census estimate (count): Black or African American alone population (2020 edition onward).
`M_AFAM`	string		Margin of error (90% confidence) for the paired E_ estimate: Black or African American alone population (2020 edition onward).
`E_HISP`	string		ACS/Census estimate (count): Hispanic or Latino population, any race (2020 edition onward).
`M_HISP`	string		Margin of error (90% confidence) for the paired E_ estimate: Hispanic or Latino population, any race (2020 edition onward).
`E_ASIAN`	string		ACS/Census estimate (count): Asian alone population (2020 edition onward).
`M_ASIAN`	string		Margin of error (90% confidence) for the paired E_ estimate: Asian alone population (2020 edition onward).
`E_AIAN`	string		ACS/Census estimate (count): American Indian and Alaska Native alone population (2020 edition onward).
`M_AIAN`	string		Margin of error (90% confidence) for the paired E_ estimate: American Indian and Alaska Native alone population (2020 edition onward).
`E_NHPI`	string		ACS/Census estimate (count): Native Hawaiian and Other Pacific Islander alone population (2020 edition onward).
`M_NHPI`	string		Margin of error (90% confidence) for the paired E_ estimate: Native Hawaiian and Other Pacific Islander alone population (2020 edition onward).
`E_TWOMORE`	string		ACS/Census estimate (count): population of two or more races (2020 edition onward).
`M_TWOMORE`	string		Margin of error (90% confidence) for the paired E_ estimate: population of two or more races (2020 edition onward).
`E_OTHERRACE`	string		ACS/Census estimate (count): population of some other race alone (2020 edition onward).
`M_OTHERRACE`	string		Margin of error (90% confidence) for the paired E_ estimate: population of some other race alone (2020 edition onward).
`EP_NOINT`	string		ACS/Census percent estimate: households with no internet access (2020 edition onward), as a percentage of the relevant universe.
`MP_NOINT`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: households with no internet access (2020 edition onward).
`EP_AFAM`	string		ACS/Census percent estimate: Black or African American alone population (2020 edition onward), as a percentage of the relevant universe.
`MP_AFAM`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: Black or African American alone population (2020 edition onward).
`EP_HISP`	string		ACS/Census percent estimate: Hispanic or Latino population, any race (2020 edition onward), as a percentage of the relevant universe.
`MP_HISP`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: Hispanic or Latino population, any race (2020 edition onward).
`EP_ASIAN`	string		ACS/Census percent estimate: Asian alone population (2020 edition onward), as a percentage of the relevant universe.
`MP_ASIAN`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: Asian alone population (2020 edition onward).
`EP_AIAN`	string		ACS/Census percent estimate: American Indian and Alaska Native alone population (2020 edition onward), as a percentage of the relevant universe.
`MP_AIAN`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: American Indian and Alaska Native alone population (2020 edition onward).
`EP_NHPI`	string		ACS/Census percent estimate: Native Hawaiian and Other Pacific Islander alone population (2020 edition onward), as a percentage of the relevant universe.
`MP_NHPI`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: Native Hawaiian and Other Pacific Islander alone population (2020 edition onward).
`EP_TWOMORE`	string		ACS/Census percent estimate: population of two or more races (2020 edition onward), as a percentage of the relevant universe.
`MP_TWOMORE`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: population of two or more races (2020 edition onward).
`EP_OTHERRACE`	string		ACS/Census percent estimate: population of some other race alone (2020 edition onward), as a percentage of the relevant universe.
`MP_OTHERRACE`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: population of some other race alone (2020 edition onward).
`AFFGEOID`	string		Census fully qualified GEOID for the unit, e.g. ‘0500000US01001’. Present in the 2014 layout only.
`E_POV`	string		ACS/Census estimate (count): persons below the poverty threshold (100% of the federal poverty level; 2014-2018 editions only, replaced by POV150 from 2020).
`M_POV`	string		Margin of error (90% confidence) for the paired E_ estimate: persons below the poverty threshold (100% of the federal poverty level; 2014-2018 editions only, replaced by POV150 from 2020).
`E_PCI`	string		ACS/Census estimate (count): per capita income, dollars (2014-2018 editions only; dropped from the SVI methodology starting with the 2020 edition).
`M_PCI`	string		Margin of error (90% confidence) for the paired E_ estimate: per capita income, dollars (2014-2018 editions only; dropped from the SVI methodology starting with the 2020 edition).
`EP_POV`	string		ACS/Census percent estimate: persons below the poverty threshold (100% of the federal poverty level; 2014-2018 editions only, replaced by POV150 from 2020), as a percentage of the relevant universe.
`MP_POV`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons below the poverty threshold (100% of the federal poverty level; 2014-2018 editions only, replaced by POV150 from 2020).
`EP_PCI`	string		Per capita income, dollars, duplicated verbatim from E_PCI – CDC’s own naming quirk: PCI has no separate percent form, but the source still prefixes it EP_ (confirmed identical to E_PCI in the real file).
`MP_PCI`	string		Margin of error (90% confidence) for E_PCI/EP_PCI (dollars, not a percent).
`EPL_POV`	string		Percentile rank (0-1) of persons below the poverty threshold (100% of the federal poverty level; 2014-2018 editions only, replaced by POV150 from 2020), among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_PCI`	string		Percentile rank (0-1) of per capita income, dollars (2014-2018 editions only; dropped from the SVI methodology starting with the 2020 edition), among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`F_POV`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons below the poverty threshold (100% of the federal poverty level; 2014-2018 editions only, replaced by POV150 from 2020))
`F_PCI`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (per capita income, dollars (2014-2018 editions only; dropped from the SVI methodology starting with the 2020 edition))
`svi_edition`	string	yes	The SVI edition this row was published in, e.g. ‘2022’ – the version axis for this source (module docstring). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.svi__county_2000`

CDC/ATSDR Social Vulnerability Index 2000 edition, county file, landed verbatim and whole under its own real column layout – NOT unioned into raw.svi_county (module docstring: no ACS E/M_ columns at all, decennial-Census-based; the real file’s line 1 is a stale header CDC never removed, so this table’s schema matches the file’s real line-2 header, and land_raw skips line 1 on read). Public domain (17 U.S.C. Sec 105; https://www.cdc.gov/other/agencymaterials.html).

Sorted by: svi_edition, STCNTY

Column	Type	Required	Doc
`ST`	string		2-digit state FIPS code.
`COU`	string		3-digit county FIPS code (within-state).
`STCNTY`	string	yes	5-digit state+county FIPS code – the county-level geographic identifier in the county file (which has no separate FIPS column); the containing county’s code in the tract file.
`STATE`	string		State name, as published (e.g. ‘Alabama’).
`ST_ABBR`	string		2-letter USPS state abbreviation.
`COUNTY`	string		County (or county-equivalent) name, as published.
`P_POV`	string		Proportion of individuals below the poverty level (SVI 2000 Data Dictionary, theme 1: Socioeconomic).
`P_UNEMP`	string		Proportion of civilian population (age 16+) unemployed (theme 1).
`P_PCI`	string		Per capita income in 1999 dollars – despite the ‘P_’ prefix shared with the proportion variables, this is a dollar amount, not a percentage (theme 1; same naming quirk as the 2010/2014+ layouts’ EP_PCI).
`P_NOHSDP`	string		Proportion of persons age 25+ with no high school diploma (theme 1).
`P_AGE65`	string		Proportion of persons aged 65 and older (theme 2: Household Composition/Disability).
`P_AGE17`	string		Proportion of persons aged 17 and younger (theme 2).
`P_DISABL`	string		Proportion of persons age 5+ with a disability (theme 2).
`P_SNGPNT`	string		Proportion of single-parent households with children under 18 (theme 2).
`P_MINRTY`	string		Proportion minority (all persons except white, non-Hispanic) (theme 3: Minority Status/Language).
`P_LIMENG`	string		Proportion of persons age 5+ who speak English “less than well” (theme 3).
`P_MUNIT`	string		Proportion of housing in structures with 10 or more units (theme 4: Housing Type/Transportation).
`P_MOBILE`	string		Proportion of mobile homes (theme 4).
`P_CROWD`	string		Proportion of households with more people than rooms (theme 4).
`P_NOVEH`	string		Proportion of households with no vehicle available (theme 4).
`P_GROUPQ`	string		Proportion of persons in institutional and non-institutional group quarters (theme 4).
`PL_POV`	string		Percentile ranking (0-1) of the poverty proportion, among all units landed in this edition; one of the four components summed into RPL_THEME1.
`PL_UNEMP`	string		Percentile ranking (0-1) of the unemployment proportion; one of the four components summed into RPL_THEME1.
`PL_PCI`	string		Percentile ranking (0-1) of per capita income (ranked low-to-high, since unlike the other variables a higher income is lower vulnerability); one of the four components summed into RPL_THEME1.
`PL_NOHSDP`	string		Percentile ranking (0-1) of the no-high-school-diploma proportion; one of the four components summed into RPL_THEME1.
`RPL_THEME1`	string		Overall percentile ranking (0-1) for theme 1 (Socioeconomic: poverty, unemployment, per capita income, no high school diploma), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME1:2000’.
`PL_AGE65`	string		Percentile ranking (0-1) of the age-65+ proportion; one of the four components summed into RPL_THEME2.
`PL_AGE17`	string		Percentile ranking (0-1) of the age-17-and-under proportion; one of the four components summed into RPL_THEME2.
`PL_DISABL`	string		Percentile ranking (0-1) of the disability proportion; one of the four components summed into RPL_THEME2.
`PL_SNGPNT`	string		Percentile ranking (0-1) of the single-parent-household proportion; one of the four components summed into RPL_THEME2.
`RPL_THEME2`	string		Overall percentile ranking (0-1) for theme 2 (Household Composition/Disability: age 65+, age 17 and under, disability, single-parent households), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME2:2000’.
`PL_MINRTY`	string		Percentile ranking (0-1) of the minority proportion; one of the two components summed into RPL_THEME3.
`PL_LIMENG`	string		Percentile ranking (0-1) of the limited-English proportion; one of the two components summed into RPL_THEME3.
`RPL_THEME3`	string		Overall percentile ranking (0-1) for theme 3 (Minority Status/Language: minority population, limited English), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME3:2000’.
`PL_MUNIT`	string		Percentile ranking (0-1) of the multi-unit-housing proportion; one of the five components summed into RPL_THEME4.
`PL_MOBILE`	string		Percentile ranking (0-1) of the mobile-home proportion; one of the five components summed into RPL_THEME4.
`PL_CROWD`	string		Percentile ranking (0-1) of the crowding proportion; one of the five components summed into RPL_THEME4.
`PL_NOVEH`	string		Percentile ranking (0-1) of the no-vehicle proportion; one of the five components summed into RPL_THEME4.
`PL_GROUPQ`	string		Percentile ranking (0-1) of the group-quarters proportion; one of the five components summed into RPL_THEME4.
`RPL_THEME4`	string		Overall percentile ranking (0-1) for theme 4 (Housing Type/Transportation: multi-unit housing, mobile homes, crowding, no vehicle, group quarters), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME4:2000’.
`RPL_THEMES`	string		Overall SVI percentile ranking (0-1) across all four themes, among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEMES:2000’. Unlike the 2010/2014+ layouts, 2000 publishes no separate SPL_THEME sum-of-percentiles column, only the PL_ per-variable percentiles and this RPL_ theme/overall ranking (verified against the real header).
`F_POV`	string		Flag: 1 if the poverty proportion is in the 90th percentile (high-vulnerability), 0 otherwise.
`F_UNEMP`	string		Flag: 1 if the unemployment proportion is in the 90th percentile, 0 otherwise.
`F_PCI`	string		Flag: 1 if per capita income is in the 90th percentile (of vulnerability, i.e. low income), 0 otherwise.
`F_NOHSDP`	string		Flag: 1 if the no-high-school-diploma proportion is in the 90th percentile, 0 otherwise.
`F_THEME1`	string		Sum of the theme 1 flags (F_POV + F_UNEMP + F_PCI + F_NOHSDP).
`F_AGE65`	string		Flag: 1 if the age-65+ proportion is in the 90th percentile, 0 otherwise.
`F_AGE17`	string		Flag: 1 if the age-17-and-under proportion is in the 90th percentile, 0 otherwise.
`F_DISABL`	string		Flag: 1 if the disability proportion is in the 90th percentile, 0 otherwise.
`F_SNGPNT`	string		Flag: 1 if the single-parent-household proportion is in the 90th percentile, 0 otherwise.
`F_THEME2`	string		Sum of the theme 2 flags (F_AGE65 + F_AGE17 + F_DISABL + F_SNGPNT).
`F_MINRTY`	string		Flag: 1 if the minority proportion is in the 90th percentile, 0 otherwise.
`F_LIMENG`	string		Flag: 1 if the limited-English proportion is in the 90th percentile, 0 otherwise.
`F_THEME3`	string		Sum of the theme 3 flags (F_MINRTY + F_LIMENG).
`F_MUNIT`	string		Flag: 1 if the multi-unit-housing proportion is in the 90th percentile, 0 otherwise.
`F_MOBILE`	string		Flag: 1 if the mobile-home proportion is in the 90th percentile, 0 otherwise.
`F_CROWD`	string		Flag: 1 if the crowding proportion is in the 90th percentile, 0 otherwise.
`F_NOVEH`	string		Flag: 1 if the no-vehicle proportion is in the 90th percentile, 0 otherwise.
`F_GROUPQ`	string		Flag: 1 if the group-quarters proportion is in the 90th percentile, 0 otherwise.
`F_THEME4`	string		Sum of the theme 4 flags (F_MUNIT + F_MOBILE + F_CROWD + F_NOVEH + F_GROUPQ).
`F_TOTAL`	string		Sum of all four theme flag sums (F_THEME1 + F_THEME2 + F_THEME3 + F_THEME4).
`TOTPOP`	string		Total 2000 population.
`HU`	string		Total 2000 housing units.
`POV`	string		Number of individuals below the poverty level.
`UNEMP`	string		Number of civilian (age 16+) population unemployed.
`NOHSDP`	string		Number of persons age 25+ with no high school diploma.
`AGE65`	string		Number of persons aged 65 and older.
`AGE17`	string		Number of persons aged 17 and younger.
`DISABL`	string		Number of persons age 5+ with a disability.
`SNGPNT`	string		Number of single-parent households with children under 18.
`MINRTY`	string		Number of minority persons (all persons except white, non-Hispanic).
`LIMENG`	string		Number of persons age 5+ who speak English “less than well”.
`MUNIT`	string		Number of housing units in structures with 10 or more units.
`MOBILE`	string		Number of mobile homes.
`CROWD`	string		Number of households with more people than rooms.
`NOVEH`	string		Number of households with no vehicle available.
`GROUPQ`	string		Number of persons in institutional and non-institutional group quarters.
`svi_edition`	string	yes	The SVI edition this row was published in (‘2000’ or ‘2010’ for this table) – the version axis for this source (module docstring). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.svi__county_2010`

CDC/ATSDR Social Vulnerability Index 2010 edition, county file, landed verbatim and whole under its own real column layout – NOT unioned into raw.svi__county (module docstring: this edition’s own STATE column holds the 2-digit state FIPS code, while every 2014+ layout’s STATE column holds the state name – a same-name, different-meaning collision unsafe to union). Public domain (17 U.S.C. Sec 105; https://www.cdc.gov/other/agencymaterials.html).

Sorted by: svi_edition, FIPS

Column	Type	Required	Doc
`ST`	string		2-letter USPS state abbreviation (county file only; note this is the opposite of STATE in this same layout – see STATE).
`STATE`	string		2-digit state FIPS code in the county file (opposite meaning from the 2014+ layouts, where STATE is the state name – module docstring: this is exactly the collision that keeps 2010 out of the shared raw.svi__county union table).
`FIPS`	string	yes	Geographic identifier: 5-digit county FIPS in raw.svi__county_2010, 11-digit tract FIPS in raw.svi__tract_2010.
`LOCATION`	string		Human-readable location name, e.g. ‘Autauga County, Alabama’ (county) or ‘Census Tract 201, Autauga County, Alabama’ (tract).
`TOTPOP`	string		Total population, 2010 Census SF1 (100% count).
`E_TOTPOP`	string		Population estimate, 2006-2010 ACS (5-year).
`M_TOTPOP`	string		Margin of error (90% confidence) for the paired E_TOTPOP estimate, 2006-2010 ACS.
`HU`	string		Total housing units, 2010 Census SF1.
`E_HU`	string		Housing units estimate, 2006-2010 ACS.
`M_HU`	string		Margin of error (90% confidence) for the paired E_HU estimate.
`HH`	string		Number of households, 2010 Census SF1.
`E_POV`	string		Persons below the poverty level estimate, 2006-2010 ACS.
`M_POV`	string		Margin of error (90% confidence) for the paired E_POV estimate.
`E_UNEMP`	string		Civilian (age 16+) unemployed estimate, 2006-2010 ACS.
`M_UNEMP`	string		Margin of error (90% confidence) for the paired E_UNEMP estimate.
`E_PCI`	string		Per capita income estimate, dollars, 2006-2010 ACS.
`M_PCI`	string		Margin of error (90% confidence) for the paired E_PCI estimate.
`E_NOHSDIP`	string		Persons age 25+ with no high school diploma estimate, 2006-2010 ACS.
`M_NOHSDIP`	string		Margin of error (90% confidence) for the paired E_NOHSDIP estimate.
`AGE65`	string		Persons aged 65 and older, 2010 Census SF1 (100% count, no sampling error – SVI 2010 documentation).
`AGE17`	string		Persons aged 17 and younger, 2010 Census SF1 (100% count).
`SNGPRNT`	string		Single-parent households with children under 18, 2010 Census SF1 (100% count). SVI 2010 has no separate disability variable at all – the Census Bureau collected no tract-level disability data for either the 2010 Census or the 2006-2010 ACS (SVI 2010 documentation).
`MINORITY`	string		Minority population (all persons except white, non-Hispanic), 2010 Census SF1 (100% count).
`E_LIMENG`	string		Persons age 5+ who speak English “less than well” estimate, 2006-2010 ACS.
`M_LIMENG`	string		Margin of error (90% confidence) for the paired E_LIMENG estimate.
`E_MUNIT`	string		Housing in structures with 10 or more units estimate, 2006-2010 ACS.
`M_MUNIT`	string		Margin of error (90% confidence) for the paired E_MUNIT estimate.
`E_MOBILE`	string		Mobile homes estimate, 2006-2010 ACS.
`M_MOBILE`	string		Margin of error (90% confidence) for the paired E_MOBILE estimate.
`E_CROWD`	string		Households with more people than rooms estimate, 2006-2010 ACS.
`M_CROWD`	string		Margin of error (90% confidence) for the paired E_CROWD estimate.
`E_NOVEH`	string		Households with no vehicle available estimate, 2006-2010 ACS.
`M_NOVEH`	string		Margin of error (90% confidence) for the paired E_NOVEH estimate.
`GROUPQ`	string		Persons in institutionalized and non-institutionalized group quarters, 2010 Census SF1 (100% count).
`E_P_POV`	string		Proportion of persons below poverty estimate (E_POV / persons for whom poverty status is determined estimate); multiply by 100 for a percentage.
`M_P_POV`	string		Margin of error (90% confidence) for the paired E_P_POV estimate.
`E_P_UNEMP`	string		Proportion of civilian (age 16+) unemployed estimate (E_UNEMP / civilians estimate); multiply by 100 for a percentage.
`M_P_UNEMP`	string		Margin of error (90% confidence) for the paired E_P_UNEMP estimate.
`E_P_PCI`	string		Per capita income estimate, dollars – duplicated verbatim from E_PCI (SVI 2010 documentation: ‘Same as E_PCI’; not actually a proportion despite the naming, same quirk as the 2014+ layouts’ EP_PCI).
`M_P_PCI`	string		Margin of error (90% confidence) for E_PCI/E_P_PCI, duplicated verbatim from M_PCI (dollars, not a percent).
`E_P_NOHSDIP`	string		Proportion of persons with no high school diploma (age 25+) estimate; multiply by 100 for a percentage.
`M_P_NOHSDIP`	string		Margin of error (90% confidence) for the paired E_P_NOHSDIP estimate.
`P_AGE65`	string		Proportion of persons aged 65 and older (AGE65 / TOTPOP, 2010 Census SF1, no sampling error); multiply by 100 for a percentage.
`P_AGE17`	string		Proportion of persons aged 17 and younger (AGE17 / TOTPOP, 2010 Census SF1); multiply by 100 for a percentage.
`P_SNGPRNT`	string		Proportion of single-parent households with children under 18 (SNGPRNT / HH, 2010 Census SF1); multiply by 100 for a percentage.
`P_MINORITY`	string		Proportion minority, all persons except white non-Hispanic (MINORITY / TOTPOP, 2010 Census SF1); multiply by 100 for a percentage.
`E_P_LIMENG`	string		Proportion of persons age 5+ who speak English “less than well” estimate (E_LIMENG / persons aged 5+ estimate); multiply by 100 for a percentage.
`M_P_LIMENG`	string		Margin of error (90% confidence) for the paired E_P_LIMENG estimate.
`E_P_MUNIT`	string		Proportion of housing in structures with 10+ units estimate (E_MUNIT / E_HU); multiply by 100 for a percentage.
`M_P_MUNIT`	string		Margin of error (90% confidence) for the paired E_P_MUNIT estimate.
`E_P_MOBILE`	string		Proportion of mobile homes estimate (E_MOBILE / E_HU); multiply by 100 for a percentage.
`M_P_MOBILE`	string		Margin of error (90% confidence) for the paired E_P_MOBILE estimate.
`E_P_CROWD`	string		Proportion of households with more people than rooms estimate (E_CROWD / occupied housing units estimate); multiply by 100 for a percentage.
`M_P_CROWD`	string		Margin of error (90% confidence) for the paired E_P_CROWD estimate.
`E_P_NOVEH`	string		Proportion of households with no vehicle available estimate (E_NOVEH / occupied housing units estimate); multiply by 100 for a percentage.
`M_P_NOVEH`	string		Margin of error (90% confidence) for the paired E_P_NOVEH estimate.
`P_GROUPQ`	string		Proportion of persons in institutionalized and non-institutionalized group quarters (GROUPQ / TOTPOP, 2010 Census SF1); multiply by 100 for a percentage.
`E_PL_POV`	string		Percentile of the poverty proportion estimate, no consideration of MOE; one of the four components summed into S_PL_THEME1.
`E_PL_UNEMP`	string		Percentile of the unemployment proportion estimate, no consideration of MOE; one of the four components summed into S_PL_THEME1.
`E_PL_PCI`	string		Percentile of per capita income estimate, no consideration of MOE; one of the four components summed into S_PL_THEME1.
`E_PL_NOHSDIP`	string		Percentile of the no-high-school-diploma proportion estimate, no consideration of MOE; one of the four components summed into S_PL_THEME1.
`S_PL_THEME1`	string		Sum of the E_PLxxx series for theme 1 (E_PL_POV + E_PL_UNEMP + E_PL_PCI + E_PL_NOHSDIP).
`R_PL_THEME1`	string		Percentile ranking (0-1) for theme 1 (Socioeconomic), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME1:2010’.
`PL_AGE65`	string		Percentile of the age-65+ proportion, based on 100% counts (no sampling error); one of the three components summed into S_PL_THEME2.
`PL_AGE17`	string		Percentile of the age-17-and-under proportion, based on 100% counts; one of the three components summed into S_PL_THEME2.
`PL_SNGPRNT`	string		Percentile of the single-parent-household proportion, based on 100% counts; one of the three components summed into S_PL_THEME2.
`S_PL_THEME2`	string		Sum of the PLxxx series for theme 2 (PL_AGE65 + PL_AGE17 + PL_SNGPRNT – no disability component in this edition).
`R_PL_THEME2`	string		Percentile ranking (0-1) for theme 2 (Household Composition – no disability variable in this edition, unlike SVI 2000 and 2014+), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME2:2010’.
`PL_MINORITY`	string		Percentile of the minority proportion, based on 100% counts (no sampling error); one of the two components summed into S_PL_THEME3.
`E_PL_LIMENG`	string		Percentile of the limited-English proportion estimate, no consideration of MOE; one of the two components summed into S_PL_THEME3.
`S_PL_THEME3`	string		Sum of the PLxxx series for theme 3 (PL_MINORITY + E_PL_LIMENG).
`R_PL_THEME3`	string		Percentile ranking (0-1) for theme 3 (Minority Status/Language), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME3:2010’.
`E_PL_MUNIT`	string		Percentile of the multi-unit-housing proportion estimate, no consideration of MOE; one of the five components summed into S_PL_THEME4.
`E_PL_MOBILE`	string		Percentile of the mobile-home proportion estimate, no consideration of MOE; one of the five components summed into S_PL_THEME4.
`E_PL_CROWD`	string		Percentile of the crowding proportion estimate, no consideration of MOE; one of the five components summed into S_PL_THEME4.
`E_PL_NOVEH`	string		Percentile of the no-vehicle proportion estimate, no consideration of MOE; one of the five components summed into S_PL_THEME4.
`PL_GROUPQ`	string		Percentile of the group-quarters proportion, based on 100% counts (no sampling error); one of the five components summed into S_PL_THEME4.
`S_PL_THEME4`	string		Sum of the PLxxx series for theme 4 (E_PL_MUNIT + E_PL_MOBILE + E_PL_CROWD + E_PL_NOVEH + PL_GROUPQ).
`R_PL_THEME4`	string		Percentile ranking (0-1) for theme 4 (Housing Type/Transportation), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME4:2010’.
`S_PL_THEMES`	string		Sum of the four themes’ S_PL_THEME sums.
`R_PL_THEMES`	string		Overall SVI percentile ranking (0-1) across all four themes, among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEMES:2010’.
`F_PL_POV`	string		Flag: 1 if the poverty percentile is in the 90th percentile (high-vulnerability), 0 otherwise.
`F_PL_UNEMP`	string		Flag: 1 if the unemployment percentile is in the 90th percentile, 0 otherwise.
`F_PL_PCI`	string		Flag: 1 if the per-capita-income percentile is in the 90th percentile, 0 otherwise.
`F_PL_NOHSDIP`	string		Flag: 1 if the no-high-school-diploma percentile is in the 90th percentile, 0 otherwise.
`F_PL_THEME1`	string		Sum of the theme 1 flags (F_PL_POV + F_PL_UNEMP + F_PL_PCI + F_PL_NOHSDIP).
`F_PL_AGE65`	string		Flag: 1 if the age-65+ percentile is in the 90th percentile, 0 otherwise.
`F_PL_AGE17`	string		Flag: 1 if the age-17-and-under percentile is in the 90th percentile, 0 otherwise.
`F_PLSNGPRNT`	string		Flag: 1 if the single-parent-household percentile is in the 90th percentile, 0 otherwise. Landed verbatim under its real, misspelled county-file name – the tract file spells the equivalent column F_PL_SNGPRNT (verified against both real files); this is why county and tract are declared as separate tables rather than unioned.
`F_PL_THEME2`	string		Sum of the theme 2 flags.
`F_PL_MINORITY`	string		Flag: 1 if the minority percentile is in the 90th percentile, 0 otherwise.
`F_PL_LIMENG`	string		Flag: 1 if the limited-English percentile is in the 90th percentile, 0 otherwise.
`F_PL_THEME3`	string		Sum of the theme 3 flags.
`F_PL_MUNIT`	string		Flag: 1 if the multi-unit-housing percentile is in the 90th percentile, 0 otherwise.
`F_PL_MOBILE`	string		Flag: 1 if the mobile-home percentile is in the 90th percentile, 0 otherwise.
`F_PL_CROWD`	string		Flag: 1 if the crowding percentile is in the 90th percentile, 0 otherwise.
`F_PL_NOVEH`	string		Flag: 1 if the no-vehicle percentile is in the 90th percentile, 0 otherwise.
`F_PL_GROUPQ`	string		Flag: 1 if the group-quarters percentile is in the 90th percentile, 0 otherwise.
`F_PL_THEME4`	string		Sum of the theme 4 flags.
`F_PL_TOTAL`	string		Sum of all four theme flag sums.
`Shape`	string		ArcGIS geometry byproduct (county file only), landed verbatim; not the canonical geometry representation (SPEC.md geometry non-goal).
`Shape.STArea()`	string		ArcGIS geometry byproduct (county file only), landed verbatim.
`Shape.STLength()`	string		ArcGIS geometry byproduct (county file only), landed verbatim.
`svi_edition`	string	yes	The SVI edition this row was published in (‘2000’ or ‘2010’ for this table) – the version axis for this source (module docstring). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.svi__tract`

CDC/ATSDR Social Vulnerability Index tract file landed verbatim and whole, one row per census tract per edition. Only the 2022 edition is landed (module docstring); same ‘2020’ layout as raw.svi__county’s 2020/2022 rows, verified byte-identical. Public domain (17 U.S.C. § 105; https://www.cdc.gov/other/agencymaterials.html).

Sorted by: svi_edition, FIPS

Column	Type	Required	Doc
`ST`	string		2-digit state FIPS code.
`STATE`	string		State name, as published (case varies by edition: uppercase through 2018, title case from 2020).
`ST_ABBR`	string		2-letter USPS state abbreviation.
`STCNTY`	string		5-digit state+county FIPS code. Equal to FIPS at county level; at tract level, the containing county’s code.
`COUNTY`	string		County (or county-equivalent) name, as published.
`FIPS`	string	yes	Geographic identifier: 5-digit county FIPS in raw.svi__county, 11-digit tract FIPS in raw.svi__tract.
`LOCATION`	string		Human-readable location name, e.g. ‘Autauga County, Alabama’ (county) or ‘Census Tract 4001.01; Capitol Planning Region; Connecticut’ (tract).
`AREA_SQMI`	string		Land area of the unit, square miles, as published.
`E_TOTPOP`	string		ACS/Census estimate (count): total population.
`M_TOTPOP`	string		Margin of error (90% confidence) for the paired E_ estimate: total population.
`E_HU`	string		ACS/Census estimate (count): total housing units.
`M_HU`	string		Margin of error (90% confidence) for the paired E_ estimate: total housing units.
`E_HH`	string		ACS/Census estimate (count): total households.
`M_HH`	string		Margin of error (90% confidence) for the paired E_ estimate: total households.
`E_POV150`	string		ACS/Census estimate (count): persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018).
`M_POV150`	string		Margin of error (90% confidence) for the paired E_ estimate: persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018).
`E_UNEMP`	string		ACS/Census estimate (count): civilian (age 16+) population unemployed.
`M_UNEMP`	string		Margin of error (90% confidence) for the paired E_ estimate: civilian (age 16+) population unemployed.
`E_HBURD`	string		ACS/Census estimate (count): occupied housing units spending 30% or more of household income on housing costs (2020 edition onward).
`M_HBURD`	string		Margin of error (90% confidence) for the paired E_ estimate: occupied housing units spending 30% or more of household income on housing costs (2020 edition onward).
`E_NOHSDP`	string		ACS/Census estimate (count): persons age 25+ with no high school diploma.
`M_NOHSDP`	string		Margin of error (90% confidence) for the paired E_ estimate: persons age 25+ with no high school diploma.
`E_UNINSUR`	string		ACS/Census estimate (count): civilian noninstitutionalized population with no health insurance.
`M_UNINSUR`	string		Margin of error (90% confidence) for the paired E_ estimate: civilian noninstitutionalized population with no health insurance.
`E_AGE65`	string		ACS/Census estimate (count): persons aged 65 and older.
`M_AGE65`	string		Margin of error (90% confidence) for the paired E_ estimate: persons aged 65 and older.
`E_AGE17`	string		ACS/Census estimate (count): persons aged 17 and under.
`M_AGE17`	string		Margin of error (90% confidence) for the paired E_ estimate: persons aged 17 and under.
`E_DISABL`	string		ACS/Census estimate (count): civilian noninstitutionalized population with a disability.
`M_DISABL`	string		Margin of error (90% confidence) for the paired E_ estimate: civilian noninstitutionalized population with a disability.
`E_SNGPNT`	string		ACS/Census estimate (count): single-parent households.
`M_SNGPNT`	string		Margin of error (90% confidence) for the paired E_ estimate: single-parent households.
`E_LIMENG`	string		ACS/Census estimate (count): persons age 5+ who speak English “less than well”.
`M_LIMENG`	string		Margin of error (90% confidence) for the paired E_ estimate: persons age 5+ who speak English “less than well”.
`E_MINRTY`	string		ACS/Census estimate (count): minority population (all persons except white, non-Hispanic).
`M_MINRTY`	string		Margin of error (90% confidence) for the paired E_ estimate: minority population (all persons except white, non-Hispanic).
`E_MUNIT`	string		ACS/Census estimate (count): housing units in structures with 10 or more units.
`M_MUNIT`	string		Margin of error (90% confidence) for the paired E_ estimate: housing units in structures with 10 or more units.
`E_MOBILE`	string		ACS/Census estimate (count): mobile homes.
`M_MOBILE`	string		Margin of error (90% confidence) for the paired E_ estimate: mobile homes.
`E_CROWD`	string		ACS/Census estimate (count): occupied housing units with more people than rooms.
`M_CROWD`	string		Margin of error (90% confidence) for the paired E_ estimate: occupied housing units with more people than rooms.
`E_NOVEH`	string		ACS/Census estimate (count): households with no vehicle available.
`M_NOVEH`	string		Margin of error (90% confidence) for the paired E_ estimate: households with no vehicle available.
`E_GROUPQ`	string		ACS/Census estimate (count): persons in group quarters.
`M_GROUPQ`	string		Margin of error (90% confidence) for the paired E_ estimate: persons in group quarters.
`EP_POV150`	string		ACS/Census percent estimate: persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018), as a percentage of the relevant universe.
`MP_POV150`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018).
`EP_UNEMP`	string		ACS/Census percent estimate: civilian (age 16+) population unemployed, as a percentage of the relevant universe.
`MP_UNEMP`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: civilian (age 16+) population unemployed.
`EP_HBURD`	string		ACS/Census percent estimate: occupied housing units spending 30% or more of household income on housing costs (2020 edition onward), as a percentage of the relevant universe.
`MP_HBURD`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: occupied housing units spending 30% or more of household income on housing costs (2020 edition onward).
`EP_NOHSDP`	string		ACS/Census percent estimate: persons age 25+ with no high school diploma, as a percentage of the relevant universe.
`MP_NOHSDP`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons age 25+ with no high school diploma.
`EP_UNINSUR`	string		ACS/Census percent estimate: civilian noninstitutionalized population with no health insurance, as a percentage of the relevant universe.
`MP_UNINSUR`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: civilian noninstitutionalized population with no health insurance.
`EP_AGE65`	string		ACS/Census percent estimate: persons aged 65 and older, as a percentage of the relevant universe.
`MP_AGE65`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons aged 65 and older.
`EP_AGE17`	string		ACS/Census percent estimate: persons aged 17 and under, as a percentage of the relevant universe.
`MP_AGE17`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons aged 17 and under.
`EP_DISABL`	string		ACS/Census percent estimate: civilian noninstitutionalized population with a disability, as a percentage of the relevant universe.
`MP_DISABL`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: civilian noninstitutionalized population with a disability.
`EP_SNGPNT`	string		ACS/Census percent estimate: single-parent households, as a percentage of the relevant universe.
`MP_SNGPNT`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: single-parent households.
`EP_LIMENG`	string		ACS/Census percent estimate: persons age 5+ who speak English “less than well”, as a percentage of the relevant universe.
`MP_LIMENG`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons age 5+ who speak English “less than well”.
`EP_MINRTY`	string		ACS/Census percent estimate: minority population (all persons except white, non-Hispanic), as a percentage of the relevant universe.
`MP_MINRTY`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: minority population (all persons except white, non-Hispanic).
`EP_MUNIT`	string		ACS/Census percent estimate: housing units in structures with 10 or more units, as a percentage of the relevant universe.
`MP_MUNIT`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: housing units in structures with 10 or more units.
`EP_MOBILE`	string		ACS/Census percent estimate: mobile homes, as a percentage of the relevant universe.
`MP_MOBILE`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: mobile homes.
`EP_CROWD`	string		ACS/Census percent estimate: occupied housing units with more people than rooms, as a percentage of the relevant universe.
`MP_CROWD`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: occupied housing units with more people than rooms.
`EP_NOVEH`	string		ACS/Census percent estimate: households with no vehicle available, as a percentage of the relevant universe.
`MP_NOVEH`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: households with no vehicle available.
`EP_GROUPQ`	string		ACS/Census percent estimate: persons in group quarters, as a percentage of the relevant universe.
`MP_GROUPQ`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: persons in group quarters.
`EPL_POV150`	string		Percentile rank (0-1) of persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018), among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_UNEMP`	string		Percentile rank (0-1) of civilian (age 16+) population unemployed, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_HBURD`	string		Percentile rank (0-1) of occupied housing units spending 30% or more of household income on housing costs (2020 edition onward), among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_NOHSDP`	string		Percentile rank (0-1) of persons age 25+ with no high school diploma, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_UNINSUR`	string		Percentile rank (0-1) of civilian noninstitutionalized population with no health insurance, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`SPL_THEME1`	string		Sum of theme 1’s EPL_ percentile-rank components. Theme 1 is Socioeconomic Status (poverty, unemployment, income, education) in the 2014/2016/2018 editions, or Socioeconomic Status (poverty, unemployment, housing cost burden, education, uninsured) in 2020/2022.
`RPL_THEME1`	string		Percentile ranking (0-1) for theme 1, among all units landed in this edition. Theme 1 is Socioeconomic Status (poverty, unemployment, income, education) in the 2014/2016/2018 editions, or Socioeconomic Status (poverty, unemployment, housing cost burden, education, uninsured) in 2020/2022; derived into measure.observation as ‘SVI:RPL_THEME1:’.
`EPL_AGE65`	string		Percentile rank (0-1) of persons aged 65 and older, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_AGE17`	string		Percentile rank (0-1) of persons aged 17 and under, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_DISABL`	string		Percentile rank (0-1) of civilian noninstitutionalized population with a disability, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_SNGPNT`	string		Percentile rank (0-1) of single-parent households, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_LIMENG`	string		Percentile rank (0-1) of persons age 5+ who speak English “less than well”, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`SPL_THEME2`	string		Sum of theme 2’s EPL_ percentile-rank components. Theme 2 is Household Composition & Disability (age 65+, age 17-, disability, single-parent households) in the 2014/2016/2018 editions, or Household Characteristics (age 65+, age 17-, disability, single-parent households, limited English) in 2020/2022.
`RPL_THEME2`	string		Percentile ranking (0-1) for theme 2, among all units landed in this edition. Theme 2 is Household Composition & Disability (age 65+, age 17-, disability, single-parent households) in the 2014/2016/2018 editions, or Household Characteristics (age 65+, age 17-, disability, single-parent households, limited English) in 2020/2022; derived into measure.observation as ‘SVI:RPL_THEME2:’.
`EPL_MINRTY`	string		Percentile rank (0-1) of minority population (all persons except white, non-Hispanic), among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`SPL_THEME3`	string		Sum of theme 3’s EPL_ percentile-rank components. Theme 3 is Minority Status & Language (minority population, limited English) in the 2014/2016/2018 editions, or Racial & Ethnic Minority Status (minority population) in 2020/2022.
`RPL_THEME3`	string		Percentile ranking (0-1) for theme 3, among all units landed in this edition. Theme 3 is Minority Status & Language (minority population, limited English) in the 2014/2016/2018 editions, or Racial & Ethnic Minority Status (minority population) in 2020/2022; derived into measure.observation as ‘SVI:RPL_THEME3:’.
`EPL_MUNIT`	string		Percentile rank (0-1) of housing units in structures with 10 or more units, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_MOBILE`	string		Percentile rank (0-1) of mobile homes, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_CROWD`	string		Percentile rank (0-1) of occupied housing units with more people than rooms, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_NOVEH`	string		Percentile rank (0-1) of households with no vehicle available, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`EPL_GROUPQ`	string		Percentile rank (0-1) of persons in group quarters, among all units landed in this edition; one of the components summed into this variable’s SPL_THEME.
`SPL_THEME4`	string		Sum of theme 4’s EPL_ percentile-rank components. Theme 4 is Housing Type & Transportation (multi-unit housing, mobile homes, crowding, no vehicle, group quarters) in the 2014/2016/2018 editions, or Housing Type & Transportation (multi-unit housing, mobile homes, crowding, no vehicle, group quarters) in 2020/2022.
`RPL_THEME4`	string		Percentile ranking (0-1) for theme 4, among all units landed in this edition. Theme 4 is Housing Type & Transportation (multi-unit housing, mobile homes, crowding, no vehicle, group quarters) in the 2014/2016/2018 editions, or Housing Type & Transportation (multi-unit housing, mobile homes, crowding, no vehicle, group quarters) in 2020/2022; derived into measure.observation as ‘SVI:RPL_THEME4:’.
`SPL_THEMES`	string		Sum of SPL_THEME1-4 (theme sub-scores).
`RPL_THEMES`	string		Overall SVI percentile ranking (0-1) across all four themes, among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEMES:’ (family ‘2014’ for the 2014/2016/2018 editions, ‘2020’ for 2020/2022 – theme composition differs between them; see measure.definition.doc).
`F_POV150`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons below 150% of the federal poverty level (2020 edition onward; replaces the 100%-threshold POV variable used through 2018))
`F_UNEMP`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (civilian (age 16+) population unemployed)
`F_HBURD`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (occupied housing units spending 30% or more of household income on housing costs (2020 edition onward))
`F_NOHSDP`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons age 25+ with no high school diploma)
`F_UNINSUR`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (civilian noninstitutionalized population with no health insurance)
`F_THEME1`	string		Flag: 1 if theme 1’s RPL_THEME1 is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed.
`F_AGE65`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons aged 65 and older)
`F_AGE17`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons aged 17 and under)
`F_DISABL`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (civilian noninstitutionalized population with a disability)
`F_SNGPNT`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (single-parent households)
`F_LIMENG`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons age 5+ who speak English “less than well”)
`F_THEME2`	string		Flag: 1 if theme 2’s RPL_THEME2 is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed.
`F_MINRTY`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (minority population (all persons except white, non-Hispanic))
`F_THEME3`	string		Flag: 1 if theme 3’s RPL_THEME3 is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed.
`F_MUNIT`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (housing units in structures with 10 or more units)
`F_MOBILE`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (mobile homes)
`F_CROWD`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (occupied housing units with more people than rooms)
`F_NOVEH`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (households with no vehicle available)
`F_GROUPQ`	string		Flag: 1 if this variable’s percentile rank is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed. (persons in group quarters)
`F_THEME4`	string		Flag: 1 if theme 4’s RPL_THEME4 is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed.
`F_TOTAL`	string		Flag: 1 if RPL_THEMES is in the edition’s flagged (high-vulnerability) range, 0 otherwise; -999 where not computed.
`E_DAYPOP`	string		ACS/Census estimate (count): daytime population estimate.
`E_NOINT`	string		ACS/Census estimate (count): households with no internet access (2020 edition onward).
`M_NOINT`	string		Margin of error (90% confidence) for the paired E_ estimate: households with no internet access (2020 edition onward).
`E_AFAM`	string		ACS/Census estimate (count): Black or African American alone population (2020 edition onward).
`M_AFAM`	string		Margin of error (90% confidence) for the paired E_ estimate: Black or African American alone population (2020 edition onward).
`E_HISP`	string		ACS/Census estimate (count): Hispanic or Latino population, any race (2020 edition onward).
`M_HISP`	string		Margin of error (90% confidence) for the paired E_ estimate: Hispanic or Latino population, any race (2020 edition onward).
`E_ASIAN`	string		ACS/Census estimate (count): Asian alone population (2020 edition onward).
`M_ASIAN`	string		Margin of error (90% confidence) for the paired E_ estimate: Asian alone population (2020 edition onward).
`E_AIAN`	string		ACS/Census estimate (count): American Indian and Alaska Native alone population (2020 edition onward).
`M_AIAN`	string		Margin of error (90% confidence) for the paired E_ estimate: American Indian and Alaska Native alone population (2020 edition onward).
`E_NHPI`	string		ACS/Census estimate (count): Native Hawaiian and Other Pacific Islander alone population (2020 edition onward).
`M_NHPI`	string		Margin of error (90% confidence) for the paired E_ estimate: Native Hawaiian and Other Pacific Islander alone population (2020 edition onward).
`E_TWOMORE`	string		ACS/Census estimate (count): population of two or more races (2020 edition onward).
`M_TWOMORE`	string		Margin of error (90% confidence) for the paired E_ estimate: population of two or more races (2020 edition onward).
`E_OTHERRACE`	string		ACS/Census estimate (count): population of some other race alone (2020 edition onward).
`M_OTHERRACE`	string		Margin of error (90% confidence) for the paired E_ estimate: population of some other race alone (2020 edition onward).
`EP_NOINT`	string		ACS/Census percent estimate: households with no internet access (2020 edition onward), as a percentage of the relevant universe.
`MP_NOINT`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: households with no internet access (2020 edition onward).
`EP_AFAM`	string		ACS/Census percent estimate: Black or African American alone population (2020 edition onward), as a percentage of the relevant universe.
`MP_AFAM`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: Black or African American alone population (2020 edition onward).
`EP_HISP`	string		ACS/Census percent estimate: Hispanic or Latino population, any race (2020 edition onward), as a percentage of the relevant universe.
`MP_HISP`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: Hispanic or Latino population, any race (2020 edition onward).
`EP_ASIAN`	string		ACS/Census percent estimate: Asian alone population (2020 edition onward), as a percentage of the relevant universe.
`MP_ASIAN`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: Asian alone population (2020 edition onward).
`EP_AIAN`	string		ACS/Census percent estimate: American Indian and Alaska Native alone population (2020 edition onward), as a percentage of the relevant universe.
`MP_AIAN`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: American Indian and Alaska Native alone population (2020 edition onward).
`EP_NHPI`	string		ACS/Census percent estimate: Native Hawaiian and Other Pacific Islander alone population (2020 edition onward), as a percentage of the relevant universe.
`MP_NHPI`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: Native Hawaiian and Other Pacific Islander alone population (2020 edition onward).
`EP_TWOMORE`	string		ACS/Census percent estimate: population of two or more races (2020 edition onward), as a percentage of the relevant universe.
`MP_TWOMORE`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: population of two or more races (2020 edition onward).
`EP_OTHERRACE`	string		ACS/Census percent estimate: population of some other race alone (2020 edition onward), as a percentage of the relevant universe.
`MP_OTHERRACE`	string		Margin of error (90% confidence) for the paired EP_ percent estimate: population of some other race alone (2020 edition onward).
`svi_edition`	string	yes	The SVI edition this row was published in, e.g. ‘2022’ – the version axis for this source (module docstring). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.svi__tract_2000`

CDC/ATSDR Social Vulnerability Index 2000 edition, tract file, landed verbatim and whole under its own real column layout – see raw.svi__county_2000 for why this is a dedicated table rather than a union. Public domain (17 U.S.C. Sec 105; https://www.cdc.gov/other/agencymaterials.html).

Sorted by: svi_edition, FIPS

Column	Type	Required	Doc
`ST`	string		2-digit state FIPS code.
`COU`	string		3-digit county FIPS code (within-state).
`STCNTY`	string		5-digit state+county FIPS code – the county-level geographic identifier in the county file (which has no separate FIPS column); the containing county’s code in the tract file.
`TRACT`	string		Local tract number (tract file only), e.g. ‘020100’.
`FIPS`	string	yes	11-digit tract FIPS code (tract file only).
`STATE`	string		State name, as published (e.g. ‘Alabama’).
`ST_ABBR`	string		2-letter USPS state abbreviation.
`COUNTY`	string		County (or county-equivalent) name, as published.
`P_POV`	string		Proportion of individuals below the poverty level (SVI 2000 Data Dictionary, theme 1: Socioeconomic).
`P_UNEMP`	string		Proportion of civilian population (age 16+) unemployed (theme 1).
`P_PCI`	string		Per capita income in 1999 dollars – despite the ‘P_’ prefix shared with the proportion variables, this is a dollar amount, not a percentage (theme 1; same naming quirk as the 2010/2014+ layouts’ EP_PCI).
`P_NOHSDP`	string		Proportion of persons age 25+ with no high school diploma (theme 1).
`P_AGE65`	string		Proportion of persons aged 65 and older (theme 2: Household Composition/Disability).
`P_AGE17`	string		Proportion of persons aged 17 and younger (theme 2).
`P_DISABL`	string		Proportion of persons age 5+ with a disability (theme 2).
`P_SNGPNT`	string		Proportion of single-parent households with children under 18 (theme 2).
`P_MINRTY`	string		Proportion minority (all persons except white, non-Hispanic) (theme 3: Minority Status/Language).
`P_LIMENG`	string		Proportion of persons age 5+ who speak English “less than well” (theme 3).
`P_MUNIT`	string		Proportion of housing in structures with 10 or more units (theme 4: Housing Type/Transportation).
`P_MOBILE`	string		Proportion of mobile homes (theme 4).
`P_CROWD`	string		Proportion of households with more people than rooms (theme 4).
`P_NOVEH`	string		Proportion of households with no vehicle available (theme 4).
`P_GROUPQ`	string		Proportion of persons in institutional and non-institutional group quarters (theme 4).
`PL_POV`	string		Percentile ranking (0-1) of the poverty proportion, among all units landed in this edition; one of the four components summed into RPL_THEME1.
`PL_UNEMP`	string		Percentile ranking (0-1) of the unemployment proportion; one of the four components summed into RPL_THEME1.
`PL_PCI`	string		Percentile ranking (0-1) of per capita income (ranked low-to-high, since unlike the other variables a higher income is lower vulnerability); one of the four components summed into RPL_THEME1.
`PL_NOHSDP`	string		Percentile ranking (0-1) of the no-high-school-diploma proportion; one of the four components summed into RPL_THEME1.
`RPL_THEME1`	string		Overall percentile ranking (0-1) for theme 1 (Socioeconomic: poverty, unemployment, per capita income, no high school diploma), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME1:2000’.
`PL_AGE65`	string		Percentile ranking (0-1) of the age-65+ proportion; one of the four components summed into RPL_THEME2.
`PL_AGE17`	string		Percentile ranking (0-1) of the age-17-and-under proportion; one of the four components summed into RPL_THEME2.
`PL_DISABL`	string		Percentile ranking (0-1) of the disability proportion; one of the four components summed into RPL_THEME2.
`PL_SNGPNT`	string		Percentile ranking (0-1) of the single-parent-household proportion; one of the four components summed into RPL_THEME2.
`RPL_THEME2`	string		Overall percentile ranking (0-1) for theme 2 (Household Composition/Disability: age 65+, age 17 and under, disability, single-parent households), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME2:2000’.
`PL_MINRTY`	string		Percentile ranking (0-1) of the minority proportion; one of the two components summed into RPL_THEME3.
`PL_LIMENG`	string		Percentile ranking (0-1) of the limited-English proportion; one of the two components summed into RPL_THEME3.
`RPL_THEME3`	string		Overall percentile ranking (0-1) for theme 3 (Minority Status/Language: minority population, limited English), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME3:2000’.
`PL_MUNIT`	string		Percentile ranking (0-1) of the multi-unit-housing proportion; one of the five components summed into RPL_THEME4.
`PL_MOBILE`	string		Percentile ranking (0-1) of the mobile-home proportion; one of the five components summed into RPL_THEME4.
`PL_CROWD`	string		Percentile ranking (0-1) of the crowding proportion; one of the five components summed into RPL_THEME4.
`PL_NOVEH`	string		Percentile ranking (0-1) of the no-vehicle proportion; one of the five components summed into RPL_THEME4.
`PL_GROUPQ`	string		Percentile ranking (0-1) of the group-quarters proportion; one of the five components summed into RPL_THEME4.
`RPL_THEME4`	string		Overall percentile ranking (0-1) for theme 4 (Housing Type/Transportation: multi-unit housing, mobile homes, crowding, no vehicle, group quarters), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME4:2000’.
`RPL_THEMES`	string		Overall SVI percentile ranking (0-1) across all four themes, among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEMES:2000’. Unlike the 2010/2014+ layouts, 2000 publishes no separate SPL_THEME sum-of-percentiles column, only the PL_ per-variable percentiles and this RPL_ theme/overall ranking (verified against the real header).
`F_POV`	string		Flag: 1 if the poverty proportion is in the 90th percentile (high-vulnerability), 0 otherwise.
`F_UNEMP`	string		Flag: 1 if the unemployment proportion is in the 90th percentile, 0 otherwise.
`F_PCI`	string		Flag: 1 if per capita income is in the 90th percentile (of vulnerability, i.e. low income), 0 otherwise.
`F_NOHSDP`	string		Flag: 1 if the no-high-school-diploma proportion is in the 90th percentile, 0 otherwise.
`F_THEME1`	string		Sum of the theme 1 flags (F_POV + F_UNEMP + F_PCI + F_NOHSDP).
`F_AGE65`	string		Flag: 1 if the age-65+ proportion is in the 90th percentile, 0 otherwise.
`F_AGE17`	string		Flag: 1 if the age-17-and-under proportion is in the 90th percentile, 0 otherwise.
`F_DISABL`	string		Flag: 1 if the disability proportion is in the 90th percentile, 0 otherwise.
`F_SNGPNT`	string		Flag: 1 if the single-parent-household proportion is in the 90th percentile, 0 otherwise.
`F_THEME2`	string		Sum of the theme 2 flags (F_AGE65 + F_AGE17 + F_DISABL + F_SNGPNT).
`F_MINRTY`	string		Flag: 1 if the minority proportion is in the 90th percentile, 0 otherwise.
`F_LIMENG`	string		Flag: 1 if the limited-English proportion is in the 90th percentile, 0 otherwise.
`F_THEME3`	string		Sum of the theme 3 flags (F_MINRTY + F_LIMENG).
`F_MUNIT`	string		Flag: 1 if the multi-unit-housing proportion is in the 90th percentile, 0 otherwise.
`F_MOBILE`	string		Flag: 1 if the mobile-home proportion is in the 90th percentile, 0 otherwise.
`F_CROWD`	string		Flag: 1 if the crowding proportion is in the 90th percentile, 0 otherwise.
`F_NOVEH`	string		Flag: 1 if the no-vehicle proportion is in the 90th percentile, 0 otherwise.
`F_GROUPQ`	string		Flag: 1 if the group-quarters proportion is in the 90th percentile, 0 otherwise.
`F_THEME4`	string		Sum of the theme 4 flags (F_MUNIT + F_MOBILE + F_CROWD + F_NOVEH + F_GROUPQ).
`F_TOTAL`	string		Sum of all four theme flag sums (F_THEME1 + F_THEME2 + F_THEME3 + F_THEME4).
`TOTPOP`	string		Total 2000 population.
`HU`	string		Total 2000 housing units.
`POV`	string		Number of individuals below the poverty level.
`UNEMP`	string		Number of civilian (age 16+) population unemployed.
`NOHSDP`	string		Number of persons age 25+ with no high school diploma.
`AGE65`	string		Number of persons aged 65 and older.
`AGE17`	string		Number of persons aged 17 and younger.
`DISABL`	string		Number of persons age 5+ with a disability.
`SNGPNT`	string		Number of single-parent households with children under 18.
`MINRTY`	string		Number of minority persons (all persons except white, non-Hispanic).
`LIMENG`	string		Number of persons age 5+ who speak English “less than well”.
`MUNIT`	string		Number of housing units in structures with 10 or more units.
`MOBILE`	string		Number of mobile homes.
`CROWD`	string		Number of households with more people than rooms.
`NOVEH`	string		Number of households with no vehicle available.
`GROUPQ`	string		Number of persons in institutional and non-institutional group quarters.
`svi_edition`	string	yes	The SVI edition this row was published in (‘2000’ or ‘2010’ for this table) – the version axis for this source (module docstring). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.svi__tract_2010`

CDC/ATSDR Social Vulnerability Index 2010 edition, tract file, landed verbatim and whole under its own real column layout – see raw.svi__county_2010 for why this is a dedicated table rather than a union. Public domain (17 U.S.C. Sec 105; https://www.cdc.gov/other/agencymaterials.html).

Sorted by: svi_edition, FIPS

Column	Type	Required	Doc
`GEO_ID`	string		Census fully qualified GEOID for the tract (tract file only), e.g. ‘1400000US01001020100’.
`STATE_FIPS`	string		2-digit state FIPS code (tract file only).
`CNTY_FIPS`	string		3-digit county FIPS code, within-state (tract file only).
`TRACT`	string		Local tract number (tract file only), e.g. ‘020100’.
`CENSUSAREA`	string		Land area of the tract, square miles, as published (tract file only).
`STCOFIPS`	string		5-digit state+county FIPS code of the containing county (tract file only; equivalent to STCNTY in the 2014+ layouts).
`FIPS`	string	yes	Geographic identifier: 5-digit county FIPS in raw.svi__county_2010, 11-digit tract FIPS in raw.svi__tract_2010.
`STATE_ABBR`	string		2-letter USPS state abbreviation (tract file only).
`STATE_NAME`	string		State name, as published (tract file only).
`COUNTY`	string		County (or county-equivalent) name, as published (tract file only).
`LOCATION`	string		Human-readable location name, e.g. ‘Autauga County, Alabama’ (county) or ‘Census Tract 201, Autauga County, Alabama’ (tract).
`TOTPOP`	string		Total population, 2010 Census SF1 (100% count).
`E_TOTPOP`	string		Population estimate, 2006-2010 ACS (5-year).
`M_TOTPOP`	string		Margin of error (90% confidence) for the paired E_TOTPOP estimate, 2006-2010 ACS.
`HU`	string		Total housing units, 2010 Census SF1.
`E_HU`	string		Housing units estimate, 2006-2010 ACS.
`M_HU`	string		Margin of error (90% confidence) for the paired E_HU estimate.
`HH`	string		Number of households, 2010 Census SF1.
`E_POV`	string		Persons below the poverty level estimate, 2006-2010 ACS.
`M_POV`	string		Margin of error (90% confidence) for the paired E_POV estimate.
`E_UNEMP`	string		Civilian (age 16+) unemployed estimate, 2006-2010 ACS.
`M_UNEMP`	string		Margin of error (90% confidence) for the paired E_UNEMP estimate.
`E_PCI`	string		Per capita income estimate, dollars, 2006-2010 ACS.
`M_PCI`	string		Margin of error (90% confidence) for the paired E_PCI estimate.
`E_NOHSDIP`	string		Persons age 25+ with no high school diploma estimate, 2006-2010 ACS.
`M_NOHSDIP`	string		Margin of error (90% confidence) for the paired E_NOHSDIP estimate.
`AGE65`	string		Persons aged 65 and older, 2010 Census SF1 (100% count, no sampling error – SVI 2010 documentation).
`AGE17`	string		Persons aged 17 and younger, 2010 Census SF1 (100% count).
`SNGPRNT`	string		Single-parent households with children under 18, 2010 Census SF1 (100% count). SVI 2010 has no separate disability variable at all – the Census Bureau collected no tract-level disability data for either the 2010 Census or the 2006-2010 ACS (SVI 2010 documentation).
`MINORITY`	string		Minority population (all persons except white, non-Hispanic), 2010 Census SF1 (100% count).
`E_LIMENG`	string		Persons age 5+ who speak English “less than well” estimate, 2006-2010 ACS.
`M_LIMENG`	string		Margin of error (90% confidence) for the paired E_LIMENG estimate.
`E_MUNIT`	string		Housing in structures with 10 or more units estimate, 2006-2010 ACS.
`M_MUNIT`	string		Margin of error (90% confidence) for the paired E_MUNIT estimate.
`E_MOBILE`	string		Mobile homes estimate, 2006-2010 ACS.
`M_MOBILE`	string		Margin of error (90% confidence) for the paired E_MOBILE estimate.
`E_CROWD`	string		Households with more people than rooms estimate, 2006-2010 ACS.
`M_CROWD`	string		Margin of error (90% confidence) for the paired E_CROWD estimate.
`E_NOVEH`	string		Households with no vehicle available estimate, 2006-2010 ACS.
`M_NOVEH`	string		Margin of error (90% confidence) for the paired E_NOVEH estimate.
`GROUPQ`	string		Persons in institutionalized and non-institutionalized group quarters, 2010 Census SF1 (100% count).
`E_P_POV`	string		Proportion of persons below poverty estimate (E_POV / persons for whom poverty status is determined estimate); multiply by 100 for a percentage.
`M_P_POV`	string		Margin of error (90% confidence) for the paired E_P_POV estimate.
`E_P_UNEMP`	string		Proportion of civilian (age 16+) unemployed estimate (E_UNEMP / civilians estimate); multiply by 100 for a percentage.
`M_P_UNEMP`	string		Margin of error (90% confidence) for the paired E_P_UNEMP estimate.
`E_P_PCI`	string		Per capita income estimate, dollars – duplicated verbatim from E_PCI (SVI 2010 documentation: ‘Same as E_PCI’; not actually a proportion despite the naming, same quirk as the 2014+ layouts’ EP_PCI).
`M_P_PCI`	string		Margin of error (90% confidence) for E_PCI/E_P_PCI, duplicated verbatim from M_PCI (dollars, not a percent).
`E_P_NOHSDIP`	string		Proportion of persons with no high school diploma (age 25+) estimate; multiply by 100 for a percentage.
`M_P_NOHSDIP`	string		Margin of error (90% confidence) for the paired E_P_NOHSDIP estimate.
`P_AGE65`	string		Proportion of persons aged 65 and older (AGE65 / TOTPOP, 2010 Census SF1, no sampling error); multiply by 100 for a percentage.
`P_AGE17`	string		Proportion of persons aged 17 and younger (AGE17 / TOTPOP, 2010 Census SF1); multiply by 100 for a percentage.
`P_SNGPRNT`	string		Proportion of single-parent households with children under 18 (SNGPRNT / HH, 2010 Census SF1); multiply by 100 for a percentage.
`P_MINORITY`	string		Proportion minority, all persons except white non-Hispanic (MINORITY / TOTPOP, 2010 Census SF1); multiply by 100 for a percentage.
`E_P_LIMENG`	string		Proportion of persons age 5+ who speak English “less than well” estimate (E_LIMENG / persons aged 5+ estimate); multiply by 100 for a percentage.
`M_P_LIMENG`	string		Margin of error (90% confidence) for the paired E_P_LIMENG estimate.
`E_P_MUNIT`	string		Proportion of housing in structures with 10+ units estimate (E_MUNIT / E_HU); multiply by 100 for a percentage.
`M_P_MUNIT`	string		Margin of error (90% confidence) for the paired E_P_MUNIT estimate.
`E_P_MOBILE`	string		Proportion of mobile homes estimate (E_MOBILE / E_HU); multiply by 100 for a percentage.
`M_P_MOBILE`	string		Margin of error (90% confidence) for the paired E_P_MOBILE estimate.
`E_P_CROWD`	string		Proportion of households with more people than rooms estimate (E_CROWD / occupied housing units estimate); multiply by 100 for a percentage.
`M_P_CROWD`	string		Margin of error (90% confidence) for the paired E_P_CROWD estimate.
`E_P_NOVEH`	string		Proportion of households with no vehicle available estimate (E_NOVEH / occupied housing units estimate); multiply by 100 for a percentage.
`M_P_NOVEH`	string		Margin of error (90% confidence) for the paired E_P_NOVEH estimate.
`P_GROUPQ`	string		Proportion of persons in institutionalized and non-institutionalized group quarters (GROUPQ / TOTPOP, 2010 Census SF1); multiply by 100 for a percentage.
`E_PL_POV`	string		Percentile of the poverty proportion estimate, no consideration of MOE; one of the four components summed into S_PL_THEME1.
`E_PL_UNEMP`	string		Percentile of the unemployment proportion estimate, no consideration of MOE; one of the four components summed into S_PL_THEME1.
`E_PL_PCI`	string		Percentile of per capita income estimate, no consideration of MOE; one of the four components summed into S_PL_THEME1.
`E_PL_NOHSDIP`	string		Percentile of the no-high-school-diploma proportion estimate, no consideration of MOE; one of the four components summed into S_PL_THEME1.
`S_PL_THEME1`	string		Sum of the E_PLxxx series for theme 1 (E_PL_POV + E_PL_UNEMP + E_PL_PCI + E_PL_NOHSDIP).
`R_PL_THEME1`	string		Percentile ranking (0-1) for theme 1 (Socioeconomic), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME1:2010’.
`PL_AGE65`	string		Percentile of the age-65+ proportion, based on 100% counts (no sampling error); one of the three components summed into S_PL_THEME2.
`PL_AGE17`	string		Percentile of the age-17-and-under proportion, based on 100% counts; one of the three components summed into S_PL_THEME2.
`PL_SNGPRNT`	string		Percentile of the single-parent-household proportion, based on 100% counts; one of the three components summed into S_PL_THEME2.
`S_PL_THEME2`	string		Sum of the PLxxx series for theme 2 (PL_AGE65 + PL_AGE17 + PL_SNGPRNT – no disability component in this edition).
`R_PL_THEME2`	string		Percentile ranking (0-1) for theme 2 (Household Composition – no disability variable in this edition, unlike SVI 2000 and 2014+), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME2:2010’.
`PL_MINORITY`	string		Percentile of the minority proportion, based on 100% counts (no sampling error); one of the two components summed into S_PL_THEME3.
`E_PL_LIMENG`	string		Percentile of the limited-English proportion estimate, no consideration of MOE; one of the two components summed into S_PL_THEME3.
`S_PL_THEME3`	string		Sum of the PLxxx series for theme 3 (PL_MINORITY + E_PL_LIMENG).
`R_PL_THEME3`	string		Percentile ranking (0-1) for theme 3 (Minority Status/Language), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME3:2010’.
`E_PL_MUNIT`	string		Percentile of the multi-unit-housing proportion estimate, no consideration of MOE; one of the five components summed into S_PL_THEME4.
`E_PL_MOBILE`	string		Percentile of the mobile-home proportion estimate, no consideration of MOE; one of the five components summed into S_PL_THEME4.
`E_PL_CROWD`	string		Percentile of the crowding proportion estimate, no consideration of MOE; one of the five components summed into S_PL_THEME4.
`E_PL_NOVEH`	string		Percentile of the no-vehicle proportion estimate, no consideration of MOE; one of the five components summed into S_PL_THEME4.
`PL_GROUPQ`	string		Percentile of the group-quarters proportion, based on 100% counts (no sampling error); one of the five components summed into S_PL_THEME4.
`S_PL_THEME4`	string		Sum of the PLxxx series for theme 4 (E_PL_MUNIT + E_PL_MOBILE + E_PL_CROWD + E_PL_NOVEH + PL_GROUPQ).
`R_PL_THEME4`	string		Percentile ranking (0-1) for theme 4 (Housing Type/Transportation), among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEME4:2010’.
`S_PL_THEMES`	string		Sum of the four themes’ S_PL_THEME sums.
`R_PL_THEMES`	string		Overall SVI percentile ranking (0-1) across all four themes, among all units landed in this edition; derived into measure.observation as ‘SVI:RPL_THEMES:2010’.
`F_PL_POV`	string		Flag: 1 if the poverty percentile is in the 90th percentile (high-vulnerability), 0 otherwise.
`F_PL_UNEMP`	string		Flag: 1 if the unemployment percentile is in the 90th percentile, 0 otherwise.
`F_PL_PCI`	string		Flag: 1 if the per-capita-income percentile is in the 90th percentile, 0 otherwise.
`F_PL_NOHSDIP`	string		Flag: 1 if the no-high-school-diploma percentile is in the 90th percentile, 0 otherwise.
`F_PL_THEME1`	string		Sum of the theme 1 flags (F_PL_POV + F_PL_UNEMP + F_PL_PCI + F_PL_NOHSDIP).
`F_PL_AGE65`	string		Flag: 1 if the age-65+ percentile is in the 90th percentile, 0 otherwise.
`F_PL_AGE17`	string		Flag: 1 if the age-17-and-under percentile is in the 90th percentile, 0 otherwise.
`F_PL_SNGPRNT`	string		Flag: 1 if the single-parent-household percentile is in the 90th percentile, 0 otherwise (tract file’s spelling; see raw.svi__county_2010.F_PLSNGPRNT for the county file’s differently misspelled equivalent).
`F_PL_THEME2`	string		Sum of the theme 2 flags.
`F_PL_MINORITY`	string		Flag: 1 if the minority percentile is in the 90th percentile, 0 otherwise.
`F_PL_LIMENG`	string		Flag: 1 if the limited-English percentile is in the 90th percentile, 0 otherwise.
`F_PL_THEME3`	string		Sum of the theme 3 flags.
`F_PL_MUNIT`	string		Flag: 1 if the multi-unit-housing percentile is in the 90th percentile, 0 otherwise.
`F_PL_MOBILE`	string		Flag: 1 if the mobile-home percentile is in the 90th percentile, 0 otherwise.
`F_PL_CROWD`	string		Flag: 1 if the crowding percentile is in the 90th percentile, 0 otherwise.
`F_PL_NOVEH`	string		Flag: 1 if the no-vehicle percentile is in the 90th percentile, 0 otherwise.
`F_PL_GROUPQ`	string		Flag: 1 if the group-quarters percentile is in the 90th percentile, 0 otherwise.
`F_PL_THEME4`	string		Sum of the theme 4 flags.
`F_PL_TOTAL`	string		Sum of all four theme flag sums.
`Shape`	string		ArcGIS geometry byproduct (county file only), landed verbatim; not the canonical geometry representation (SPEC.md geometry non-goal).
`Shape.STArea()`	string		ArcGIS geometry byproduct (county file only), landed verbatim.
`Shape.STLength()`	string		ArcGIS geometry byproduct (county file only), landed verbatim.
`svi_edition`	string	yes	The SVI edition this row was published in (‘2000’ or ‘2010’ for this table) – the version axis for this source (module docstring). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`raw.teenvaxview__coverage`

CDC TeenVaxView / NIS-Teen vaccination coverage among adolescents 13-17 years, landed verbatim and whole, every vaccine and survey year (SPEC.md § Sources; #105). U.S. Government work; public domain per CDC’s site-wide content-usage policy (teenvaxview.py’s module docstring).

Sorted by: teenvax_vintage, vaccine, geography, dose, year_season

Column	Type	Required	Doc
`vaccine`	string	yes	Which vaccine/sample this row covers, e.g. ‘HPV’, ‘≥1 Dose MenACWY’, ‘Tetanus’ – as published.
`dose`	string		Dose family plus sex, comma-joined, e.g. ‘≥1 Dose, Males and Females’ (teenvaxview.py splits this on the last ‘,’ – see its module docstring). Blank for a handful of `vaccine` values that pack the dose into `vaccine` instead.
`geography_type`	string	yes	‘States/Local Areas’ or ‘HHS Regions/National’, as published.
`geography`	string	yes	State/territory name, local area name (e.g. ‘TX-Bexar County’), ‘Region N’, or ‘United States’, as published.
`year_season`	string	yes	Survey year, e.g. ‘2022’, or a pooled window, e.g. ‘2018-2022’ – teenvaxview.py splits this on ‘-’ for period_start/period_end.
`dimension_type`	string	yes	‘Overall’ \| ‘Age’ \| ‘Race and Ethnicity’ \| ‘Insurance Coverage’ \| ‘Poverty’ \| ‘Urbanicity’, as published.
`dimension`	string	yes	The category within dimension_type, e.g. ‘13-17 Years’, ‘Uninsured’, as published.
`coverage_estimate`	string	yes	The published percent, or the literal sentinel ‘NA’ when withheld (module docstring: no separate footnote column).
`ci_95`	string		95% CI as published, e.g. ‘60.3 to 68.3’; NULL when coverage_estimate is ‘NA’.
`sample_size`	string		Unweighted NIS-Teen survey respondent count underlying the estimate (not a numerator/denominator pair for it – module docstring’s ponytail note); NULL when suppressed.
`teenvax_vintage`	string	yes	Retrieval-date vintage this row was landed under, e.g. ‘2026-09-19’ (SPEC.md’s vintage rule). Raw is replaced wholesale per value of this column.
`landed_in`	string	yes	The Cancer Basemap release whose ingest landed these rows.

`geography` — Units, vintages, crosswalks, aliases — the spine every fact joins through.

`geography.alias`

FIPS renames and re-codings that are NOT boundary changes (SPEC.md § geography.alias, #26): a join on an old code resolves through here to the current one instead of dropping (SPEC.md Acceptance B). Real boundary changes (splits, merges, Connecticut’s planning regions) belong to geography.crosswalk (#25) instead, since a 1:1 alias would misrepresent them.

Business key: old_geo_id, new_geo_id
Sorted by: old_geo_id, new_geo_id

Column	Type	Required	Doc
`old_geo_id`	string	yes	geography.unit-style id (‘county:’) before the change. Part of the business key together with new_geo_id. Carries no vintage — unlike geography.unit, an alias is a pure code mapping a join resolves regardless of which vintage the observation came from.
`new_geo_id`	string	yes	geography.unit-style id (‘county:’) after the change. Part of the business key together with old_geo_id.
`effective_year`	int	yes	Calendar year the change took effect, e.g. 2015.
`change_type`	string	yes	One of: recode (code changed, name did not), rename (name changed, code did not — not useful for resolving a join, since old_geo_id would equal new_geo_id, so none are seeded), recode_and_rename (both changed, e.g. Shannon -> Oglala Lakota County).
`old_name`	string	yes	Name before the change.
`new_name`	string	yes	Name after the change.
`source`	string	yes	Asserting provider, e.g. ‘CENSUS_COUNTY_CHANGES’. Part of every writer’s merge scope, so a second source of aliases (NHGIS, say) could stack here without retiring this one’s rows.
`source_url`	string	yes	The page this row’s change was documented on.
`note`	string		Citation: the exact source sentence this row was transcribed from.

`geography.unit`

Geography — the spine every fact joins through (SPEC.md § Geography). Every level and vintage Census has ever drawn, one row per unit per vintage, with full Type-2 history via valid_from/valid_to.

Business key: geo_id, vintage
Sorted by: vintage, level, geo_id

Column	Type	Required	Doc
`geo_id`	string	yes	Canonical id: ‘:’, e.g. ‘county:08031’. Part of the business key together with vintage.
`level`	string	yes	One of: nation, state, county, tract, block_group, zcta, place, cd (congressional district), sldu (state legislative district, upper chamber), sldl (state legislative district, lower chamber), custom.
`fips`	string		The bare code, without the level prefix.
`vintage`	int	yes	Boundary vintage year, e.g. 2020. Part of the business key: a FIPS code without a vintage is an assembly name without a patch level — boundaries move (Connecticut’s 2022 move from counties to planning regions, tract redraws each decennial census).
`name`	string		Human-readable name.
`parent_geo_id`	string		Containing unit’s geo_id, in the same vintage.
`aland_m2`	double		Land area, square meters.
`awater_m2`	double		Water area, square meters.
`centroid_lat`	double		Centroid latitude, WGS84.
`centroid_lon`	double		Centroid longitude, WGS84.
`geometry_uri`	string		Pointer to the boundary geometry (GeoParquet / PMTiles on R2), not the geometry itself — geometry is referenced, never the primary artifact (SPEC.md Non-goals). NULL where no geometry is pointed to yet.

`measure` — Every published number, in one stacked long table, plus its definitions.

`measure.cancer_site`

SEER site recode <-> ICD-O-3 topography/histology <-> ICD-10 (mortality) <-> NCIt/MONDO (SPEC.md § measure.cancer_site) – the bridge to biocOnIce’s ontology namespace. Full Type-2 history via valid_from/valid_to.

Business key: cancer_site_code, source_release
Sorted by: cancer_site_code, source_release

Column	Type	Required	Doc
`cancer_site_code`	string	yes	The SEER site-recode numeric code (raw.seer__site_recode.recode), e.g. ‘26000’ for Breast. Business key together with source_release.
`label`	string	yes	Site/group name, as SEER publishes it.
`parent_code`	string		Another row’s cancer_site_code, for SEER’s own nested groupings (e.g. Cecum under ‘Colon excluding Rectum’ under ‘Colon and Rectum’). Always NULL for this edition: SEER’s table assigns no numeric code to any group heading, at any depth, so there is no coded ancestor to record – see module docstring.
`icdo3_topography`	string		ICD-O-3 topography range(s), verbatim from raw.seer__site_recode (joined with ‘;’ when a code’s definition spans more than one published row).
`icdo3_histology_exclusions`	string		ICD-O-3 histology qualifier(s), verbatim from raw.seer__site_recode (an exclusion range for most codes, an inclusion range for a few – see that table’s own column doc).
`icd10_mortality`	string		ICD-10 mortality range, verbatim from raw.seer__cod_recode, filled only where that table’s label matches this row’s label exactly (module docstring: 56 of 81 codes align this way). NULL where COD groups this site more coarsely than incidence does, or the labels genuinely differ, rather than guessed.
`ncit_id`	string		NCI Thesaurus id (e.g. ‘NCIT:C9335’), from the curated bridge (src/cancerbasemap/data/cancer_site_ontology.csv) for the State Cancer Profiles sites it covers. NULL elsewhere – never guessed (module docstring lists the sites left unmapped and why).
`mondo_id`	string		MONDO Disease Ontology id (e.g. ‘MONDO:0007254’), from the same curated bridge. NULL elsewhere.
`mapping_basis`	string		‘curated’ when ncit_id or mondo_id is filled (this project’s own researched mapping – no official SEER-recode-to-ontology crosswalk exists, checked 2026-09-18); NULL when neither is filled. No row here is ‘published’ – that value is reserved should SEER, NCIt or MONDO ever publish such a mapping themselves.
`source`	string	yes	Always ‘SEER’ – the recode’s own publisher.
`source_release`	string	yes	The site-recode edition this row’s cancer_site_code is defined under, e.g. ‘icdo3_dwhoheme’. Business key together with cancer_site_code – a later SEER edition never retires this one’s rows.
`mapping_relation`	string		How ncit_id/mondo_id relate to this cancer_site_code’s disease: ‘exact’ \| ‘broader’ \| ‘narrower’ \| ‘overlap’ – the same vocabulary as measure.stratum_map’s relation column (SPEC.md). NULL only where neither ncit_id nor mondo_id is filled (mapping_basis is also NULL there). A subsite code combined by SCP into a larger category (e.g. 21041 Cecum, part of ‘Colon and Rectum’) is ‘broader’ – the ontology term denotes the combined disease, not the subsite alone; a code whose ontology term matches it 1:1 (e.g. 26000 Breast, or 27020 Corpus Uteri, the exact anatomic site ‘Malignant Uterine Corpus Neoplasm’ names) is ‘exact’; a code that is neither a clean subset nor superset of the ontology term (e.g. 27030 Uterus, NOS – unclassified by subsite, so only some of its cases are uterine corpus cases) is ‘overlap’. Added by #90 for the cross-lake join to biocOnIce’s ontology namespace (#60, #61) to be able to choose exact matches only.

`measure.cancer_site_group`

Prevention-lens groupings over measure.cancer_site – screenable, vaccine-preventable, tobacco-/HPV-/obesity-/alcohol-/UV-associated (SPEC.md § measure.cancer_site_group, #126). Every row cites the defining publication. Full Type-2 history via valid_from/valid_to.

Business key: group_id, cancer_site_code
Sorted by: group_id, cancer_site_code

Column	Type	Required	Doc
`group_id`	string	yes	Snake_case grouping id: ‘tobacco_associated’ \| ‘hpv_associated’ \| ‘obesity_associated’ \| ‘alcohol_associated’ \| ‘alcohol_associated_limited_evidence’ \| ‘uspstf_screenable’ \| ‘vaccine_preventable’ \| ‘uv_associated’. Part of the business key together with cancer_site_code – a site can belong to more than one group.
`group_label`	string	yes	Human-readable label, e.g. ‘Tobacco-associated cancer’.
`cancer_site_code`	string	yes	FK measure.cancer_site.cancer_site_code. Business key together with group_id.
`mapping_relation`	string	yes	‘exact’ \| ‘broader’ – see raw.canceronice__cancer_site_group.
`basis`	string	yes	The citation establishing this membership – see raw.canceronice__cancer_site_group.
`source_url`	string	yes	URL `basis` quotes.
`note`	string		Caveats – see raw.canceronice__cancer_site_group.
`source`	string	yes	Always ‘CANCERONICE’ – this project’s own curated grouping (synthesizing external citations recorded per row in basis/source_url), the same convention SPEC.md uses for derived indices. Part of the merge scope, so a second curator/source of groupings could stack here without retiring this one’s rows.

`measure.definition`

One row per published measure definition (SPEC.md § Measures). A lookup table, not versioned in place — replaced wholesale per source via merge.write.

Business key: measure_id
Sorted by: measure_id

Column	Type	Required	Doc
`measure_id`	string	yes	Business key.
`source`	string	yes	The asserting provider that defines this measure, e.g. ‘SCP’, ‘PLACES’, ‘ACS’.
`label`	string		Human-readable measure name.
`units`	string		Unit of the published value.
`universe`	string		Population the rate is computed over.
`rate_basis`	string		One of: per_100000, per_1000000, percent, count, index, sum (a plain summed quantity in `units`, not a rate – e.g. TRI’s pounds-released totals, #100).
`age_adjustment`	string		Standard population used for age adjustment (e.g. ‘2000 US standard’), or NULL when the measure is not age-adjusted.
`method`	string		One of: direct, model_based, survey_direct, derived.
`cancer_site_code`	string		FK into measure.cancer_site when this measure is cancer-specific; NULL otherwise.
`doc`	string		Prose description of the measure.

`measure.observation`

Every published number, one stacked long table across sources (SPEC.md § Measures). Merge scope is (source, source_release) — a new SCP vintage never retires a PLACES row. Full Type-2 history via valid_from/valid_to.

Business key: source, source_release, measure_id, geo_id, geo_vintage, period_start, period_end, stratum_id
Partitioned by: source
Sorted by: source_release, measure_id, geo_id, period_start, stratum_id

Column	Type	Required	Doc
`source`	string	yes	Asserting provider: ‘SCP’ \| ‘PLACES’ \| ‘ACS’ \| ‘SVI’ \| … . Part of the business key and of every writer’s merge scope, so providers stack in one table and none can retire another’s rows.
`source_release`	string	yes	The upstream edition that published this value — a vintage or release label (SPEC.md § Versioning model), distinct from the period the value describes and from valid_from/valid_to.
`measure_id`	string	yes	FK measure.definition.
`geo_id`	string	yes	FK geography.unit.
`geo_vintage`	int	yes	FK geography.unit’s vintage, together with geo_id.
`period_start`	string	yes	Start of the time period this estimate describes, e.g. ‘2018’ for a five-year pooled 2018-2022 rate. The time the estimate is ABOUT, distinct from source_release (when it was published) and valid_from (when Cancer Basemap first served it).
`period_end`	string	yes	End of the time period this estimate describes, e.g. ‘2022’.
`stratum_id`	string	yes	FK measure.stratum.
`value`	double		The published value. NULL whenever value_status != ‘reported’ — no suppressed cell ever reads as a number (SPEC.md Acceptance C).
`lower`	double		Interval lower bound, when published.
`upper`	double		Interval upper bound, when published.
`interval_level`	double		Confidence/margin level of lower/upper: 0.90 (ACS MOE), 0.95 (SCP CI), or NULL when no interval is published.
`numerator`	double		Numerator, when published.
`denominator`	double		Denominator, when published.
`value_status`	string	yes	Closed enum, never NULL: ‘reported’, ‘suppressed_small_count’, ‘suppressed_complementary’, ‘suppressed_reliability’, ‘not_available’, ‘not_applicable’ (SPEC.md § Suppression is a value, not a NULL). Enforced before write by merge.check_observations.
`reliability_flag`	string		Published separately from suppression, e.g. an unstable RSE flag.
`trend`	string		Source-published trend call, if any.

`measure.stratum`

Source-native stratification, one row per distinct combination a source publishes (SPEC.md § Measures). A lookup table, replaced wholesale per source via merge.write.

Business key: stratum_id
Sorted by: stratum_id

Column	Type	Required	Doc
`stratum_id`	string	yes	Business key.
`source`	string	yes	The provider whose native categories this stratum uses.
`sex`	string		Source-native sex category, or NULL.
`age_group`	string		Source-native age group, or NULL.
`race_ethnicity`	string		Source-native race/ethnicity category, or NULL. Never harmonized in place — mappings live in measure.stratum_map instead (SPEC.md § Measures).
`stage`	string		Source-native disease stage, or NULL.
`other`	string		Any other source-native stratifier.
`scheme`	string	yes	The classification scheme this stratum’s categories come from, e.g. ‘SCP_RACE_2024’, ‘OMB_1997’, ‘OMB_SPD15_2024’. Schemes diverge across releases of the same source; this is expected.

`facility` — Places care happens (mammography, FQHC, providers, screening).

`facility.site`

Places care happens (SPEC.md § Facilities). First writer: HRSA_HC (health-center service delivery / look-alike sites). Full Type-2 history via valid_from/valid_to – a site absent from a later snapshot is retired by the merge, which is the point for a source that only ever serves today’s list.

Business key: facility_id, source
Sorted by: source, kind, geo_id, facility_id

Column	Type	Required	Doc
`facility_id`	string	yes	Source’s own stable per-site id. For HRSA_HC, HRSA’s ‘BPHC Assigned Number’ – verified unique across the whole file. Part of the business key.
`source`	string	yes	Asserting provider, e.g. ‘HRSA_HC’. Part of the business key and of every writer’s merge scope, so sources stack in one table without one retiring another’s rows.
`source_release`	string		The source’s own release label, when it publishes one. NOT part of the business key – versioning here is deliberately unsettled (issue #19). NULL for a continuously-refreshed snapshot source like HRSA_HC: the snapshot date is recorded in provenance.release and raw’s own version column instead, since repeating it here would make every unchanged row look changed on every ingest; when Cancer Basemap saw a given version of the row is valid_from/valid_to, not source_release.
`kind`	string	yes	‘fqhc’ \| ‘rhc’ \| ‘mammography’ \| ‘lung_screening’ \| ‘provider’ \| ‘hospital’ \| ‘tri’ \| ‘superfund’. HRSA_HC rows are ‘fqhc’ for both true FQHCs and FQHC Look-Alikes; ‘tri’ is EPA Toxics Release Inventory facilities (#100); ‘superfund’ is EPA Superfund NPL sites (#99).
`name`	string		Site’s own name.
`address`	string		Single-line street address, city, state, postal code.
`lat`	double		Latitude, WGS84, as published by the source.
`lon`	double		Longitude, WGS84, as published by the source.
`geo_id`	string		FK geography.unit. SPEC.md calls for tract-level geo_id here; HRSA_HC publishes only county FIPS, so this is ‘county:’+FIPS for that source – a documented gap, not a tract lookup this module performs.
`geo_vintage`	int		FK geography.unit’s vintage. 2020 for HRSA_HC: the file’s Connecticut rows carry the nine 2022 planning regions (09110-09190) and its Alaska rows carry the current census areas (e.g. 02063, 02066), never a legacy code (verified 2026-09-18).
`attributes_json`	string		JSON object of source-specific attributes, keys documented per source. HRSA_HC keys: site_type (‘Permanent’\|‘Seasonal’\|‘Mobile Van’), operating_hours_reported (‘true’\|‘false’), grantee_name, grantee_id, status.

`catchment` — Cancer centers and the geographies they claim.

`catchment.center`

Cancer centers and the catchments they claim (SPEC.md § Catchment). First writer: NCI_OCC, from raw.nci__catchment_areas. Source: National Cancer Institute; cite DelNero et al., CEBP 2022, doi:10.1158/1055-9965.EPI-21-1230.

Business key: center_id, source
Sorted by: source, center_id

Column	Type	Required	Doc
`center_id`	string	yes	The declaring source’s id for the catchment; for NCI_OCC the shapefile ID. One per polygon, so a center with several sites (Mayo Clinic: three) has several ids. Part of the business key.
`source`	string	yes	Who declared the catchment, e.g. ‘NCI_OCC’ (NCI Office of Cancer Centers’ catchment map). Part of the business key and of the writer’s merge scope.
`name`	string	yes	Center name as published.
`designation_type`	string		‘Comprehensive Cancer Center’ \| ‘Cancer Center’.
`state`	string		Center’s state, as published.
`geo_description`	string		NCI’s description of the catchment’s reach: Full-State \| Sub-State \| Inter-State \| Multi-State \| Full-Inter-State.
`address`	string		Center address on one line.
`url`	string		Center web address.
`notes`	string		Caveats on the catchment’s membership, or NULL.

`catchment.member`

The counties each catchment claims (SPEC.md § Catchment): one row per (center, county) with overlap_fraction. First writer: NCI_OCC. Source: National Cancer Institute; cite DelNero et al., CEBP 2022, doi:10.1158/1055-9965.EPI-21-1230.

Business key: center_id, geo_id, geo_vintage, declared_by
Sorted by: declared_by, center_id, geo_id

Column	Type	Required	Doc
`center_id`	string	yes	FK catchment.center (with declared_by = center.source).
`geo_id`	string	yes	FK geography.unit: ‘county:<5-digit FIPS>’. Exception: the 10 American Samoa, Guam and Northern Mariana Islands county-equivalents under Hawai’i’s catchment are not in geography.unit yet (#203).
`geo_vintage`	int	yes	FK geography.unit’s vintage: 2020 – the Census 2020 county file the portal ships, Connecticut as its eight legacy counties.
`declared_by`	string	yes	Who declared membership: ‘NCI_OCC’ \| ‘CENTER_PR’ \| ‘PUBLISHED_PAPER’. NCI_OCC membership is derived here by overlaying NCI’s catchment polygon on Census cb_2020_us_county_500k (NCI publishes polygons, not county lists).
`overlap_fraction`	double		Share of the county’s area inside the catchment, 0-1 (equal-area EPSG:5070). 1.0 for a whole county; below 1 where the catchment cuts a county (e.g. Memorial Sloan Kettering’s circle; Norris covers 43% of Orange County, CA). A county is a member only if this is >= 0.01.

`provenance` — What each Cancer Basemap release was built from, and how we know.

`provenance.lineage`

Table- and column-level lineage DAG, one row per edge, captured at ingest with sqlglot (cancerbasemap.lineage, #140). Rebuildable from each ingest’s own SQL, so merge.write scopes it on (release, job, to_table) – no Type 2 history, same as provenance.release. The table-level DAG is SELECT DISTINCT from_table, to_table; never stored twice, since a table-level-only row (to_column NULL) is written only for a pair no column-level edge already covers.

Sorted by: release, job, to_table, to_column

Column	Type	Required	Doc
`release`	string	yes	Cancer Basemap release whose ingest recorded this edge. FK provenance.release.release.
`job`	string	yes	The ingest module that produced this edge, by its module name (e.g. ‘ers_rucc’, ‘places’).
`to_table`	string	yes	Target table, dotted namespace.table (e.g. ‘measure.observation’).
`to_column`	string		Target column. NULL means this edge is table-level only: known to feed to_table, but not narrowed to one column – e.g. an output built in Python from a query’s rows rather than by the query’s own column aliases (measure.definition from PLACES’ MeasureId lookup).
`to_variable`	string		For a long table keyed by a literal value per row (measure_id in measure.observation; a future typed.*__long’s variable, #139), the specific key value this edge applies to, when the source SQL states it as a literal in that branch. NULL when the table isn’t keyed this way, or when the key is a computed expression rather than a literal – PLACES’ measure_id is built from two columns, not asserted as one value per branch, so its edges legitimately carry no to_variable.
`from_table`	string	yes	Source: a catalog table identifier, or – when from_kind=‘url’ – the upstream URL a raw table was landed from (the DAG’s root).
`from_column`	string		Source column. NULL for a table-level-only edge or a from_kind=‘url’ root edge.
`from_kind`	string	yes	‘table’ when from_table is a catalog table identifier, ‘url’ when it is the upstream URL a raw table was landed from.
`expression`	string		The SQL expression that produced to_column from from_column, verbatim from sqlglot (e.g. ‘CASE WHEN EP_POV150 = -999 THEN NULL ELSE EP_POV150 END’). NULL for a table-level-only or url-root edge.
`code_version`	string	yes	git sha of cancerbasemap (short form) at the time this edge was recorded, or the installed package version when git is unavailable.

`provenance.release`

One row per (Cancer Basemap release, source, source_version): what this release was built from. This is what makes a release reproducible — resolve it here to each source’s own version, then query each table at that release. Durable by design: unlike Iceberg snapshot summaries it does not expire. Keyed on source_version too (#78) so landing several source releases of one source under one catalog release keeps a row for each.

Business key: release, source, source_version
Sorted by: release, source, source_version

Column	Type	Required	Doc
`release`	string	yes	Cancer Basemap release, YYYY.MM with zero-padded corrections YYYY.MM.NN. Zero-padded because ‘2026.10.10’ sorts before ‘2026.10.2’ and release ordering would otherwise invert.
`source`	string	yes	Source key, e.g. scp, places, acs.
`source_version`	string	yes	The upstream version in the SOURCE’S OWN vocabulary, never normalised. Part of the business key together with release and source (#78): several source releases can land under one catalog release, and keying on (release, source) alone kept only the last one landed. Always populated — merge.manifest defaults it to the retrieval date when the source publishes no version label of its own, so it is never NULL.
`version_method`	string	yes	How the version was determined: release_number, http_last_modified, etag, ftp_index_probe, retrieval_date, unavailable. ‘unavailable’ is a legitimate value — a source that publishes no version is recorded as such, never given a fabricated one.
`retrieved_at`	string	yes	UTC timestamp at which the source was fetched.
`url`	string		Canonical URL fetched.
`checksum`	string		SHA-256 of the retrieved bytes, where computed.
`row_count`	int		Rows landed from this source, as a cheap integrity check.

Releases

What the release was built from — source, upstream version, and when it was retrieved. Its release column is the landing release the data came in under (2026.09, or a dated weekly snapshot such as 2026.10.26), not the release folder’s date.

	release	source	source_version	version_method	retrieved_at	row_count
0	2026.09	airtoxscreen_pollutant	2018	release_number	2026-09-20T16:23:32+00:00	76726
1	2026.09	airtoxscreen_pollutant	2019	release_number	2026-09-20T16:24:53+00:00	76726
2	2026.09	airtoxscreen_srcgrp	2018	release_number	2026-09-20T16:23:04+00:00	76726
3	2026.09	airtoxscreen_srcgrp	2019	release_number	2026-09-20T16:24:26+00:00	76726
4	2026.09	cancer_site_group	2026-09-19	retrieval_date	2026-09-20T16:28:28+00:00	114
...	...	...	...	...	...	...
63	2026.10.12	hrsa_sites	2026-10-12	retrieval_date	2026-10-12T12:31:05+00:00	19387
64	2026.10.19	fda_mqsa	2026-10-19	retrieval_date	2026-10-19T12:31:11+00:00	9136
65	2026.10.19	hrsa_sites	2026-10-19	retrieval_date	2026-10-19T12:31:50+00:00	19440
66	2026.10.26	fda_mqsa	2026-10-26	retrieval_date	2026-10-26T12:31:32+00:00	9138
67	2026.10.26	hrsa_sites	2026-10-26	retrieval_date	2026-10-26T12:32:12+00:00	19471

68 rows × 6 columns

Measures

Tables

raw — Sources as landed, verbatim, per source release.

raw.acs__county

raw.acs__tract

raw.airtoxscreen__tract_risk

raw.airtoxscreen__tract_risk_pollutant

raw.bls__laus_area

raw.bls__laus_county

raw.bls__laus_footnote

raw.bls__laus_measure

raw.bls__laus_series

raw.canceronice__cancer_site_group

raw.census__gazetteer_cd

raw.census__gazetteer_counties

raw.census__gazetteer_sldl

raw.census__gazetteer_sldu

raw.census__gazetteer_tracts

raw.census__state_fips

raw.ejscreen__blockgroup

raw.ejscreen__tract

raw.epa__radon_zones

raw.epa__tri_basic

raw.ers__food_access

raw.ers__food_access_sram

raw.ers__ruca_tract

raw.ers__rucc

raw.fda__mqsa_facilities

raw.geography__county_recodes

raw.hrsa__ahrf

raw.hrsa__health_center_sites

raw.hrsa__hpsa_primary_care

raw.nci__catchment_areas

raw.places__county

raw.places__tract

raw.scp__incidence

raw.scp__mortality

raw.scp__risk

raw.sdwis__geographic_areas

raw.sdwis__pub_water_systems

raw.sdwis__ref_ansi_areas

raw.sdwis__violations_enforcement

raw.seer__cod_recode

raw.seer__site_recode

raw.superfund__npl_frs

raw.superfund__npl_status

raw.svi__county

raw.svi__county_2000

raw.svi__county_2010

raw.svi__tract

raw.svi__tract_2000

raw.svi__tract_2010

raw.teenvaxview__coverage

geography — Units, vintages, crosswalks, aliases — the spine every fact joins through.

geography.alias

geography.unit

measure — Every published number, in one stacked long table, plus its definitions.

measure.cancer_site

measure.cancer_site_group

measure.definition

measure.observation

measure.stratum

facility — Places care happens (mammography, FQHC, providers, screening).

facility.site

catchment — Cancer centers and the geographies they claim.

catchment.center

catchment.member

provenance — What each Cancer Basemap release was built from, and how we know.

provenance.lineage

provenance.release

Releases

`raw` — Sources as landed, verbatim, per source release.

`raw.acs__county`

`raw.acs__tract`

`raw.airtoxscreen__tract_risk`

`raw.airtoxscreen__tract_risk_pollutant`

`raw.bls__laus_area`

`raw.bls__laus_county`

`raw.bls__laus_footnote`

`raw.bls__laus_measure`

`raw.bls__laus_series`

`raw.canceronice__cancer_site_group`

`raw.census__gazetteer_cd`

`raw.census__gazetteer_counties`

`raw.census__gazetteer_sldl`

`raw.census__gazetteer_sldu`

`raw.census__gazetteer_tracts`

`raw.census__state_fips`

`raw.ejscreen__blockgroup`

`raw.ejscreen__tract`

`raw.epa__radon_zones`

`raw.epa__tri_basic`

`raw.ers__food_access`

`raw.ers__food_access_sram`

`raw.ers__ruca_tract`

`raw.ers__rucc`

`raw.fda__mqsa_facilities`

`raw.geography__county_recodes`

`raw.hrsa__ahrf`

`raw.hrsa__health_center_sites`

`raw.hrsa__hpsa_primary_care`

`raw.nci__catchment_areas`

`raw.places__county`

`raw.places__tract`

`raw.scp__incidence`

`raw.scp__mortality`

`raw.scp__risk`

`raw.sdwis__geographic_areas`

`raw.sdwis__pub_water_systems`

`raw.sdwis__ref_ansi_areas`

`raw.sdwis__violations_enforcement`

`raw.seer__cod_recode`

`raw.seer__site_recode`

`raw.superfund__npl_frs`

`raw.superfund__npl_status`

`raw.svi__county`

`raw.svi__county_2000`

`raw.svi__county_2010`

`raw.svi__tract`

`raw.svi__tract_2000`

`raw.svi__tract_2010`

`raw.teenvaxview__coverage`

`geography` — Units, vintages, crosswalks, aliases — the spine every fact joins through.

`geography.alias`

`geography.unit`

`measure` — Every published number, in one stacked long table, plus its definitions.

`measure.cancer_site`

`measure.cancer_site_group`

`measure.definition`

`measure.observation`

`measure.stratum`

`facility` — Places care happens (mammography, FQHC, providers, screening).

`facility.site`

`catchment` — Cancer centers and the geographies they claim.

`catchment.center`

`catchment.member`

`provenance` — What each Cancer Basemap release was built from, and how we know.

`provenance.lineage`

`provenance.release`