📊 census

U.S. Census Bureau demographic and population data including American Community Survey (ACS) estimates, decennial census results, and population estimates. Provides comprehensive demographic profiles, household characteristics, income distributions, educational attainment, housing statistics, and migration patterns at national, state, and county levels.

50 datasets · 674 columns

population_summary · table

State-level population summary showing total, male, and female population by year. Aggregates data from acs_population table.

View — columns are resolved by the query engine at runtime.

income_summary · table

State-level median household income and per capita income by year, from the ACS 5-Year acs_income table — about 2 years behind the current year. For a more current, single-year state estimate query acs1_income directly (no equivalent view exists for it yet).

View — columns are resolved by the query engine at runtime.

poverty_rate · table

State-level poverty rates calculated from poverty universe and below poverty level counts. Shows percentage of population below poverty level.

View — columns are resolved by the query engine at runtime.

education_attainment · table

State-level educational attainment showing population with high school diploma, bachelor's degree, master's degree, and doctorate. Includes percentages.

View — columns are resolved by the query engine at runtime.

unemployment_rate · table

State-level unemployment rates calculated from labor force and unemployed population. Shows labor force participation and unemployment percentages.

View — columns are resolved by the query engine at runtime.

county_vulnerability_profile · table

County-year social vulnerability profile combining ACS poverty rate (acs_poverty), senior/under-5 population share (acs_age), disability rate (acs_disability), and Spanish-limited-English-proficiency rate (acs_language) — the socioeconomic, household, and language themes of the CDC/ATSDR Social Vulnerability Index. limited_english_pct covers Spanish speakers with limited English proficiency only; acs_language has no combined-language limited-English-proficiency total. Enriched with a cross-schema join to disasters.disaster_declarations for lifetime (not year-matched) declaration and Individual-Assistance counts per county, since FEMA declarations are point-in-time events that don't line up with the ACS 5-year survey vintage. One row per county per ACS 5-year vintage.

View — columns are resolved by the query engine at runtime.

acs_population · table

American Community Survey population demographics including total population, age, sex, race, and ethnicity. Provides population counts at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_population	long	yes	Total population
male_population	long	yes	Male population
female_population	long	yes	Female population

acs_income · table

Household median income and per capita income from the ACS 5-Year survey, at state and county levels. A smoothed 5-year period estimate, published about 2 years behind the current year. For a more current but state-only, single-year estimate (wider margin of error) see acs1_income.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
median_household_income	long	yes	Median household income in the past 12 months
per_capita_income	long	yes	Per capita income in the past 12 months

acs_housing · table

Housing unit counts, occupancy status (occupied/vacant), median home value, and median gross rent from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_housing_units	long	yes	Total housing units
occupied_units	long	yes	Occupied housing units
vacant_units	long	yes	Vacant housing units
median_home_value	long	yes	Median value of owner-occupied housing units
median_rent	long	yes	Median gross rent

acs_education · table

Educational attainment counts for population 25 and over from the ACS 5-Year survey, at state and county levels — population 25+, high school diploma, bachelor's degree, master's degree, and doctorate. See the education_attainment view for derived rate percentages.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
pop_25_plus	long	yes	Total population 25 years and over
hs_graduate	long	yes	Regular high school diploma (excludes GED/equivalency)
bachelors	long	yes	Bachelor's degree only (excludes higher degrees)
masters	long	yes	Master's degree
doctorate	long	yes	Doctorate degree

acs_employment · table

Labor force status counts (civilian labor force, employed, unemployed, not in labor force) from the ACS 5-Year survey, at state and county levels. Raw counts only — see the unemployment_rate view for derived unemployment and labor-force-participation percentages.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
labor_force	long	yes	Civilian labor force (population 16 years and over)
employed	long	yes	Employed (civilian labor force)
unemployed	long	yes	Unemployed (civilian labor force)
not_in_labor_force	long	yes	Not in labor force

acs_poverty · table

Poverty universe (population for whom poverty status is determined) and count below poverty level from the ACS 5-Year survey, at state and county levels. Raw counts only, with no demographic breakdown — see the poverty_rate view for the derived poverty percentage.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
poverty_universe	long	yes	Population for whom poverty status is determined (excludes institutionalized, military, unrelated children under 15)
below_poverty	long	yes	Income below poverty level in past 12 months

decennial_population · table

Decennial Census total population plus White/Black/Asian-alone race counts, at state and county levels, for census years 2000, 2010, and 2020 (every 10 years). Unified schema across all years with columns normalized to canonical names regardless of year-specific API variable codes (P001001 vs P1_001N, etc.).

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_population	long	yes	Total population
white_alone	long	yes	Population identifying as White alone
black_alone	long	yes	Population identifying as Black or African American alone
asian_alone	long	yes	Population identifying as Asian alone

acs_race_ethnicity · table

Population counts by race (White, Black, American Indian/Alaska Native, Asian, Pacific Islander, other, two-or-more) and by Hispanic/Latino origin, from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
white_alone	long	yes	White alone
white_alone_moe	bigint	yes	90% CI margin of error for white_alone (Census variable B02001_002M; negative sentinels normalized to null)
black_alone	long	yes	Black or African American alone
black_alone_moe	bigint	yes	90% CI margin of error for black_alone (Census variable B02001_003M; negative sentinels normalized to null)
american_indian_alone	long	yes	American Indian and Alaska Native alone
american_indian_alone_moe	bigint	yes	90% CI margin of error for american_indian_alone (Census variable B02001_004M; negative sentinels normalized to null)
asian_alone	long	yes	Asian alone
asian_alone_moe	bigint	yes	90% CI margin of error for asian_alone (Census variable B02001_005M; negative sentinels normalized to null)
pacific_islander_alone	long	yes	Native Hawaiian and Other Pacific Islander alone
pacific_islander_alone_moe	bigint	yes	90% CI margin of error for pacific_islander_alone (Census variable B02001_006M; negative sentinels normalized to null)
other_race_alone	long	yes	Some other race alone
other_race_alone_moe	bigint	yes	90% CI margin of error for other_race_alone (Census variable B02001_007M; negative sentinels normalized to null)
two_or_more_races	long	yes	Two or more races
two_or_more_races_moe	bigint	yes	90% CI margin of error for two_or_more_races (Census variable B02001_008M; negative sentinels normalized to null)
hispanic_latino	long	yes	Hispanic or Latino origin (any race)
hispanic_latino_moe	bigint	yes	90% CI margin of error for hispanic_latino (Census variable B03003_003M; negative sentinels normalized to null)
not_hispanic_latino	long	yes	Not Hispanic or Latino
not_hispanic_latino_moe	bigint	yes	90% CI margin of error for not_hispanic_latino (Census variable B03003_002M; negative sentinels normalized to null)

acs_age · table

Median age and population counts by age bracket (under 5, 5-17, 18-64, 65+) from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
median_age	double	yes	Median age
median_age_moe	double	yes	90% CI margin of error for median_age (Census variable B01002_001M; negative sentinels normalized to null)
under_5_years	long	yes	Population under 5 years
age_5_to_17	long	yes	Population 5 to 17 years (school age)
age_18_to_64	long	yes	Working age population 18 to 64
age_65_and_over	long	yes	Senior population 65 years and over

acs_commuting · table

Commute mode counts (drove alone, carpooled, public transit, walked, bicycled, worked from home) and mean travel time to work, from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_workers	long	yes	Total workers 16 years and over
total_workers_moe	bigint	yes	90% CI margin of error for total_workers (Census variable B08301_001M; negative sentinels normalized to null)
drove_alone	long	yes	Workers who drove alone
drove_alone_moe	bigint	yes	90% CI margin of error for drove_alone (Census variable B08301_003M; negative sentinels normalized to null)
carpooled	long	yes	Workers who carpooled
carpooled_moe	bigint	yes	90% CI margin of error for carpooled (Census variable B08301_004M; negative sentinels normalized to null)
public_transit	long	yes	Workers using public transportation
public_transit_moe	bigint	yes	90% CI margin of error for public_transit (Census variable B08301_010M; negative sentinels normalized to null)
walked	long	yes	Workers who walked to work
walked_moe	bigint	yes	90% CI margin of error for walked (Census variable B08301_019M; negative sentinels normalized to null)
bicycle	long	yes	Workers who bicycled to work
bicycle_moe	bigint	yes	90% CI margin of error for bicycle (Census variable B08301_018M; negative sentinels normalized to null)
worked_from_home	long	yes	Workers who worked from home
worked_from_home_moe	bigint	yes	90% CI margin of error for worked_from_home (Census variable B08301_021M; negative sentinels normalized to null)
mean_travel_time	double	yes	Mean travel time to work (minutes)
mean_travel_time_moe	double	yes	90% CI margin of error for mean_travel_time (Census variable B08135_001M; negative sentinels normalized to null)

acs_health_insurance · table

Health insurance coverage counts (with/without coverage, public, private) from the ACS 5-Year survey, at state and county levels. Raw counts, not rates, and not broken out by age (age groups are summed into the totals).

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_population	long	yes	Total civilian noninstitutionalized population
total_population_moe	bigint	yes	90% CI margin of error for total_population (Census variable B27001_001M; negative sentinels normalized to null)
with_health_insurance	long	yes	Population with health insurance coverage
no_health_insurance	long	yes	Population without health insurance coverage
public_coverage	long	yes	Population with public health insurance
public_coverage_moe	bigint	yes	90% CI margin of error for public_coverage (Census variable B27003_004M; negative sentinels normalized to null)
private_coverage	long	yes	Population with private health insurance
private_coverage_moe	bigint	yes	90% CI margin of error for private_coverage (Census variable B27002_004M; negative sentinels normalized to null)

acs_language · table

Population 5+ counts by language spoken at home (English only, Spanish, Spanish with limited English proficiency, other Indo-European, Asian/Pacific Island, other), from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
population_5_plus	long	yes	Population 5 years and over
population_5_plus_moe	bigint	yes	90% CI margin of error for population_5_plus (Census variable B16001_001M; negative sentinels normalized to null)
english_only	long	yes	Speak only English at home
english_only_moe	bigint	yes	90% CI margin of error for english_only (Census variable B16001_002M; negative sentinels normalized to null)
spanish	long	yes	Speak Spanish at home
spanish_moe	bigint	yes	90% CI margin of error for spanish (Census variable B16001_003M; negative sentinels normalized to null)
spanish_limited_english	long	yes	Speak Spanish, limited English proficiency
spanish_limited_english_moe	bigint	yes	90% CI margin of error for spanish_limited_english (Census variable B16001_005M; negative sentinels normalized to null)
other_indo_european	long	yes	Speak other Indo-European language
other_indo_european_moe	bigint	yes	90% CI margin of error for other_indo_european (Census variable B16001_006M; negative sentinels normalized to null)
asian_pacific_languages	long	yes	Speak Asian and Pacific Island languages
asian_pacific_languages_moe	bigint	yes	90% CI margin of error for asian_pacific_languages (Census variable B16001_009M; negative sentinels normalized to null)
other_languages	long	yes	Speak other languages
other_languages_moe	bigint	yes	90% CI margin of error for other_languages (Census variable B16001_012M; negative sentinels normalized to null)

acs_disability · table

Population counts with any disability and by disability type (hearing, vision, cognitive, ambulatory), from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_population	long	yes	Total civilian noninstitutionalized population
total_population_moe	bigint	yes	90% CI margin of error for total_population (Census variable B18101_001M; negative sentinels normalized to null)
with_disability	long	yes	Population with a disability
hearing_difficulty	long	yes	Population with hearing difficulty
hearing_difficulty_moe	bigint	yes	90% CI margin of error for hearing_difficulty (Census variable B18102_004M; negative sentinels normalized to null)
vision_difficulty	long	yes	Population with vision difficulty
vision_difficulty_moe	bigint	yes	90% CI margin of error for vision_difficulty (Census variable B18103_004M; negative sentinels normalized to null)
cognitive_difficulty	long	yes	Population with cognitive difficulty
cognitive_difficulty_moe	bigint	yes	90% CI margin of error for cognitive_difficulty (Census variable B18104_004M; negative sentinels normalized to null)
ambulatory_difficulty	long	yes	Population with ambulatory difficulty
ambulatory_difficulty_moe	bigint	yes	90% CI margin of error for ambulatory_difficulty (Census variable B18105_004M; negative sentinels normalized to null)

acs_veterans · table

Veteran and nonveteran population counts, with a male/female veteran breakdown, from the ACS 5-Year survey, at state and county levels. No breakdown by period of service.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
civilian_population_18_plus	long	yes	Civilian population 18 years and over
civilian_population_18_plus_moe	bigint	yes	90% CI margin of error for civilian_population_18_plus (Census variable B21001_001M; negative sentinels normalized to null)
veterans	long	yes	Veteran population
veterans_moe	bigint	yes	90% CI margin of error for veterans (Census variable B21001_002M; negative sentinels normalized to null)
nonveterans	long	yes	Nonveteran population
nonveterans_moe	bigint	yes	90% CI margin of error for nonveterans (Census variable B21001_003M; negative sentinels normalized to null)
male_veterans	long	yes	Male veterans
male_veterans_moe	bigint	yes	90% CI margin of error for male_veterans (Census variable B21001_005M; negative sentinels normalized to null)
female_veterans	long	yes	Female veterans
female_veterans_moe	bigint	yes	90% CI margin of error for female_veterans (Census variable B21001_023M; negative sentinels normalized to null)

acs_migration · table

Population counts by prior-year residence (same house, moved within county, moved from a different county in the same state, moved from a different state, moved from abroad), from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
population_1_year_plus	long	yes	Population 1 year and over
population_1_year_plus_moe	bigint	yes	90% CI margin of error for population_1_year_plus (Census variable B07001_001M; negative sentinels normalized to null)
same_house	long	yes	Same house 1 year ago
same_house_moe	bigint	yes	90% CI margin of error for same_house (Census variable B07001_017M; negative sentinels normalized to null)
moved_within_county	long	yes	Moved within same county
moved_within_county_moe	bigint	yes	90% CI margin of error for moved_within_county (Census variable B07001_033M; negative sentinels normalized to null)
moved_from_different_county_same_state	long	yes	Moved from different county, same state
moved_from_different_county_same_state_moe	bigint	yes	90% CI margin of error for moved_from_different_county_same_state (Census variable B07001_049M; negative sentinels normalized to null)
moved_from_different_state	long	yes	Moved from different state
moved_from_different_state_moe	bigint	yes	90% CI margin of error for moved_from_different_state (Census variable B07001_065M; negative sentinels normalized to null)
moved_from_abroad	long	yes	Moved from abroad
moved_from_abroad_moe	bigint	yes	90% CI margin of error for moved_from_abroad (Census variable B07001_081M; negative sentinels normalized to null)

acs_occupation · table

Employed civilian population counts by broad occupation category (management/business/ science/arts, service, sales/office, natural resources/construction/maintenance, production/transportation/moving), from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_employed	long	yes	Total employed civilian population 16+
total_employed_moe	bigint	yes	90% CI margin of error for total_employed (Census variable C24010_001M; negative sentinels normalized to null)
management_business_science_arts	long	yes	Management, business, science, and arts occupations
management_business_science_arts_moe	bigint	yes	90% CI margin of error for management_business_science_arts (Census variable C24010_003M; negative sentinels normalized to null)
service_occupations	long	yes	Service occupations
service_occupations_moe	bigint	yes	90% CI margin of error for service_occupations (Census variable C24010_019M; negative sentinels normalized to null)
sales_office	long	yes	Sales and office occupations
sales_office_moe	bigint	yes	90% CI margin of error for sales_office (Census variable C24010_027M; negative sentinels normalized to null)
natural_resources_construction_maintenance	long	yes	Natural resources, construction, and maintenance occupations
natural_resources_construction_maintenance_moe	bigint	yes	90% CI margin of error for natural_resources_construction_maintenance (Census variable C24010_030M; negative sentinels normalized to null)
production_transportation_moving	long	yes	Production, transportation, and material moving occupations
production_transportation_moving_moe	bigint	yes	90% CI margin of error for production_transportation_moving (Census variable C24010_037M; negative sentinels normalized to null)

acs_industry · table

Employed civilian population counts across 13 broad industry sectors (agriculture, construction, manufacturing, trade, transportation, information, finance, professional services, education/health, arts/entertainment, other services, public administration), from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_employed	long	yes	Total employed civilian population 16+
total_employed_moe	bigint	yes	90% CI margin of error for total_employed (Census variable C24030_001M; negative sentinels normalized to null)
agriculture_forestry_mining	long	yes	Agriculture, forestry, fishing, hunting, and mining
agriculture_forestry_mining_moe	bigint	yes	90% CI margin of error for agriculture_forestry_mining (Census variable C24030_003M; negative sentinels normalized to null)
construction	long	yes	Construction
construction_moe	bigint	yes	90% CI margin of error for construction (Census variable C24030_006M; negative sentinels normalized to null)
manufacturing	long	yes	Manufacturing
manufacturing_moe	bigint	yes	90% CI margin of error for manufacturing (Census variable C24030_007M; negative sentinels normalized to null)
wholesale_trade	long	yes	Wholesale trade
wholesale_trade_moe	bigint	yes	90% CI margin of error for wholesale_trade (Census variable C24030_008M; negative sentinels normalized to null)
retail_trade	long	yes	Retail trade
retail_trade_moe	bigint	yes	90% CI margin of error for retail_trade (Census variable C24030_009M; negative sentinels normalized to null)
transportation_utilities	long	yes	Transportation and warehousing, and utilities
transportation_utilities_moe	bigint	yes	90% CI margin of error for transportation_utilities (Census variable C24030_010M; negative sentinels normalized to null)
information	long	yes	Information
information_moe	bigint	yes	90% CI margin of error for information (Census variable C24030_013M; negative sentinels normalized to null)
finance_insurance_real_estate	long	yes	Finance and insurance, and real estate
finance_insurance_real_estate_moe	bigint	yes	90% CI margin of error for finance_insurance_real_estate (Census variable C24030_014M; negative sentinels normalized to null)
professional_scientific_management	long	yes	Professional, scientific, management, admin, and waste management
professional_scientific_management_moe	bigint	yes	90% CI margin of error for professional_scientific_management (Census variable C24030_017M; negative sentinels normalized to null)
educational_healthcare_social	long	yes	Educational services, health care, and social assistance
educational_healthcare_social_moe	bigint	yes	90% CI margin of error for educational_healthcare_social (Census variable C24030_021M; negative sentinels normalized to null)
arts_entertainment_recreation_food	long	yes	Arts, entertainment, recreation, accommodation, and food services
arts_entertainment_recreation_food_moe	bigint	yes	90% CI margin of error for arts_entertainment_recreation_food (Census variable C24030_024M; negative sentinels normalized to null)
other_services	long	yes	Other services (except public administration)
other_services_moe	bigint	yes	90% CI margin of error for other_services (Census variable C24030_027M; negative sentinels normalized to null)
public_administration	long	yes	Public administration
public_administration_moe	bigint	yes	90% CI margin of error for public_administration (Census variable C24030_028M; negative sentinels normalized to null)

acs_internet · table

Household counts with/without an internet subscription and with/without a computer, plus a with-broadband count (no corresponding without-broadband column), from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_households	long	yes	Total households
total_households_moe	bigint	yes	90% CI margin of error for total_households (Census variable B28002_001M; negative sentinels normalized to null)
with_internet	long	yes	Households with an internet subscription
with_internet_moe	bigint	yes	90% CI margin of error for with_internet (Census variable B28002_002M; negative sentinels normalized to null)
with_broadband	long	yes	Households with broadband internet
with_broadband_moe	bigint	yes	90% CI margin of error for with_broadband (Census variable B28002_004M; negative sentinels normalized to null)
no_internet	long	yes	Households without internet access
no_internet_moe	bigint	yes	90% CI margin of error for no_internet (Census variable B28002_013M; negative sentinels normalized to null)
with_computer	long	yes	Households with a computer
with_computer_moe	bigint	yes	90% CI margin of error for with_computer (Census variable B28001_002M; negative sentinels normalized to null)
no_computer	long	yes	Households without a computer
no_computer_moe	bigint	yes	90% CI margin of error for no_computer (Census variable B28001_011M; negative sentinels normalized to null)

acs_vehicle_access · table

Household counts by vehicle availability (no vehicle available vs. total households), from the ACS 5-Year survey table B08201 (Household Size by Vehicles Available), at state and county levels. no_vehicle_households / total_households is the standard "vehicle access" deprivation rate used alongside broadband (acs_internet) as a transportation/isolation proxy.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_households	long	yes	Total households
total_households_moe	bigint	yes	90% CI margin of error for total_households (Census variable B08201_001M; negative sentinels normalized to null)
no_vehicle_households	long	yes	Households with no vehicle available
no_vehicle_households_moe	bigint	yes	90% CI margin of error for no_vehicle_households (Census variable B08201_002M; negative sentinels normalized to null)

acs_nativity · table

Population counts by nativity and citizenship (native born, foreign born, naturalized citizen, not a citizen), from the ACS 5-Year survey, at state and county levels. native_born and foreign_born are both derived sums (B05001 has no single variable for either concept): native_born = born_in_us + born_in_pr_island_areas + born_abroad_american_parents (002+003+004), foreign_born = naturalized_citizen + not_a_citizen (005+006). The three native_born components are also exposed as their own columns — born_in_pr_island_areas in particular is analytically live on its own (most of Florida's Puerto Rico-born population), not just a summand. The full row identity is native_born + foreign_born = total_population, and at the component level born_in_us + born_in_pr_island_areas + born_abroad_american_parents + naturalized_citizen + not_a_citizen = total_population; both are DQ-asserted.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_population	long	yes	Total population
total_population_moe	bigint	yes	90% CI margin of error for total_population (Census variable B05001_001M; negative sentinels normalized to null)
native_born	long	yes	Native born (born in the US, plus Puerto Rico/island areas, plus abroad of American parents — sum of its three real components rather than a residual)
native_born_moe	bigint	yes	90% CI margin of error for native_born, aggregated per Census MOE-of-a-sum convention (sqrt of sum of squared component MOEs — B05001_002M/003M/004M; negative sentinels on any component normalize the whole value to null)
born_in_us	long	yes	Born in the United States (Census variable B05001_002E) — the largest component of native_born, exposed directly rather than only summed
born_in_us_moe	bigint	yes	90% CI margin of error for born_in_us (Census variable B05001_002M; negative sentinels normalized to null)
born_in_pr_island_areas	long	yes	Born in Puerto Rico or a US island area (Census variable B05001_003E) — analytically live on its own, not just a native_born component
born_in_pr_island_areas_moe	bigint	yes	90% CI margin of error for born_in_pr_island_areas (Census variable B05001_003M; negative sentinels normalized to null)
born_abroad_american_parents	long	yes	Born abroad of American parent(s) (Census variable B05001_004E)
born_abroad_american_parents_moe	bigint	yes	90% CI margin of error for born_abroad_american_parents (Census variable B05001_004M; negative sentinels normalized to null)
foreign_born	long	yes	Foreign born (naturalized citizens plus non-citizens; there is no single Census variable for this concept)
foreign_born_moe	bigint	yes	90% CI margin of error for foreign_born (Census variable B05001_006M; negative sentinels normalized to null)
naturalized_citizen	long	yes	Naturalized US citizen
naturalized_citizen_moe	bigint	yes	90% CI margin of error for naturalized_citizen (Census variable B05001_005M; negative sentinels normalized to null)
not_a_citizen	long	yes	Not a US citizen
not_a_citizen_moe	bigint	yes	90% CI margin of error for not_a_citizen (Census variable B05001_006M; negative sentinels normalized to null)

acs_marital_status · table

Marital status counts (never married, married, separated, widowed, divorced) by sex, for population 15 and over, from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
name	string	yes	Geographic area name from Census API
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
b12001_001e	string	yes	Population 15 years and over (total)
b12001_003e	string	yes	Male never married
b12001_004e	string	yes	Male now married (excluding separated)
b12001_006e	string	yes	Male separated
b12001_009e	string	yes	Male widowed
b12001_010e	string	yes	Male divorced
b12001_012e	string	yes	Female never married
b12001_013e	string	yes	Female now married (excluding separated)
b12001_015e	string	yes	Female separated
b12001_018e	string	yes	Female widowed
b12001_019e	string	yes	Female divorced

acs_household_type · table

Household counts by type (family vs nonfamily, married-couple, single householder with no spouse, living alone) plus average household size, from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_households	long	yes	Total households
total_households_moe	bigint	yes	90% CI margin of error for total_households (Census variable B11001_001M; negative sentinels normalized to null)
family_households	long	yes	Family households
family_households_moe	bigint	yes	90% CI margin of error for family_households (Census variable B11001_002M; negative sentinels normalized to null)
married_couple_family	long	yes	Married-couple family
married_couple_family_moe	bigint	yes	90% CI margin of error for married_couple_family (Census variable B11001_003M; negative sentinels normalized to null)
male_householder_no_spouse	long	yes	Male householder, no spouse present
male_householder_no_spouse_moe	bigint	yes	90% CI margin of error for male_householder_no_spouse (Census variable B11001_005M; negative sentinels normalized to null)
female_householder_no_spouse	long	yes	Female householder, no spouse present
female_householder_no_spouse_moe	bigint	yes	90% CI margin of error for female_householder_no_spouse (Census variable B11001_006M; negative sentinels normalized to null)
nonfamily_households	long	yes	Nonfamily households
nonfamily_households_moe	bigint	yes	90% CI margin of error for nonfamily_households (Census variable B11001_007M; negative sentinels normalized to null)
living_alone	long	yes	Householder living alone
living_alone_moe	bigint	yes	90% CI margin of error for living_alone (Census variable B11001_008M; negative sentinels normalized to null)
average_household_size	double	yes	Average household size
average_household_size_moe	double	yes	90% CI margin of error for average_household_size (Census variable B25010_001M; negative sentinels normalized to null)

acs_housing_tenure · table

Occupied housing unit counts by tenure (owner-occupied vs renter-occupied), plus median home value, median gross rent, and median year structure built, from the ACS 5-Year survey, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
occupied_units	long	yes	Total occupied housing units
occupied_units_moe	bigint	yes	90% CI margin of error for occupied_units (Census variable B25003_001M; negative sentinels normalized to null)
owner_occupied	long	yes	Owner-occupied units
owner_occupied_moe	bigint	yes	90% CI margin of error for owner_occupied (Census variable B25003_002M; negative sentinels normalized to null)
renter_occupied	long	yes	Renter-occupied units
renter_occupied_moe	bigint	yes	90% CI margin of error for renter_occupied (Census variable B25003_003M; negative sentinels normalized to null)
median_home_value	long	yes	Median value of owner-occupied units
median_home_value_moe	bigint	yes	90% CI margin of error for median_home_value (Census variable B25077_001M; negative sentinels normalized to null)
median_gross_rent	long	yes	Median gross rent
median_gross_rent_moe	bigint	yes	90% CI margin of error for median_gross_rent (Census variable B25064_001M; negative sentinels normalized to null)
median_year_built	long	yes	Median year structure built
median_year_built_moe	bigint	yes	90% CI margin of error for median_year_built (Census variable B25035_001M; negative sentinels normalized to null)

acs_housing_tenure_by_age · table

Occupied housing unit counts split by tenure (owner-occupied vs renter-occupied) and age of householder, from ACS 5-year table B25007 ("Tenure by Age of Householder"), at state and county levels. Age bands match B25007's published structure: 15-24, 25-34, 35-44, 45-54, 55-59, 60-64, 65-74, 75-84, 85+ (nine bands, identical for owners and renters). Lets a generation-cohort ownership analysis be computed directly in-engine — same age band, same vintage — rather than relying on third-party CPS reprocessing. A true generation-matched historical series still requires stitching multiple ACS vintages across the cohort's aging trajectory; this table exposes the single-vintage building block.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_occupied	long	yes	Total occupied housing units (all tenures, all ages)
total_occupied_moe	bigint	yes	90% CI margin of error for total_occupied (Census variable B25007_001M; negative sentinels normalized to null)
owner_occupied	long	yes	Owner-occupied units (all ages)
owner_occupied_moe	bigint	yes	90% CI margin of error for owner_occupied (Census variable B25007_002M; negative sentinels normalized to null)
owner_15_to_24	long	yes	Owner-occupied units where householder is 15 to 24 years
owner_15_to_24_moe	bigint	yes	90% CI margin of error for owner_15_to_24 (Census variable B25007_003M; negative sentinels normalized to null)
owner_25_to_34	long	yes	Owner-occupied units where householder is 25 to 34 years
owner_25_to_34_moe	bigint	yes	90% CI margin of error for owner_25_to_34 (Census variable B25007_004M; negative sentinels normalized to null)
owner_35_to_44	long	yes	Owner-occupied units where householder is 35 to 44 years
owner_35_to_44_moe	bigint	yes	90% CI margin of error for owner_35_to_44 (Census variable B25007_005M; negative sentinels normalized to null)
owner_45_to_54	long	yes	Owner-occupied units where householder is 45 to 54 years
owner_45_to_54_moe	bigint	yes	90% CI margin of error for owner_45_to_54 (Census variable B25007_006M; negative sentinels normalized to null)
owner_55_to_59	long	yes	Owner-occupied units where householder is 55 to 59 years
owner_55_to_59_moe	bigint	yes	90% CI margin of error for owner_55_to_59 (Census variable B25007_007M; negative sentinels normalized to null)
owner_60_to_64	long	yes	Owner-occupied units where householder is 60 to 64 years
owner_60_to_64_moe	bigint	yes	90% CI margin of error for owner_60_to_64 (Census variable B25007_008M; negative sentinels normalized to null)
owner_65_to_74	long	yes	Owner-occupied units where householder is 65 to 74 years
owner_65_to_74_moe	bigint	yes	90% CI margin of error for owner_65_to_74 (Census variable B25007_009M; negative sentinels normalized to null)
owner_75_to_84	long	yes	Owner-occupied units where householder is 75 to 84 years
owner_75_to_84_moe	bigint	yes	90% CI margin of error for owner_75_to_84 (Census variable B25007_010M; negative sentinels normalized to null)
owner_85_and_over	long	yes	Owner-occupied units where householder is 85 years and over
owner_85_and_over_moe	bigint	yes	90% CI margin of error for owner_85_and_over (Census variable B25007_011M; negative sentinels normalized to null)
renter_occupied	long	yes	Renter-occupied units (all ages)
renter_occupied_moe	bigint	yes	90% CI margin of error for renter_occupied (Census variable B25007_012M; negative sentinels normalized to null)
renter_15_to_24	long	yes	Renter-occupied units where householder is 15 to 24 years
renter_15_to_24_moe	bigint	yes	90% CI margin of error for renter_15_to_24 (Census variable B25007_013M; negative sentinels normalized to null)
renter_25_to_34	long	yes	Renter-occupied units where householder is 25 to 34 years
renter_25_to_34_moe	bigint	yes	90% CI margin of error for renter_25_to_34 (Census variable B25007_014M; negative sentinels normalized to null)
renter_35_to_44	long	yes	Renter-occupied units where householder is 35 to 44 years
renter_35_to_44_moe	bigint	yes	90% CI margin of error for renter_35_to_44 (Census variable B25007_015M; negative sentinels normalized to null)
renter_45_to_54	long	yes	Renter-occupied units where householder is 45 to 54 years
renter_45_to_54_moe	bigint	yes	90% CI margin of error for renter_45_to_54 (Census variable B25007_016M; negative sentinels normalized to null)
renter_55_to_59	long	yes	Renter-occupied units where householder is 55 to 59 years
renter_55_to_59_moe	bigint	yes	90% CI margin of error for renter_55_to_59 (Census variable B25007_017M; negative sentinels normalized to null)
renter_60_to_64	long	yes	Renter-occupied units where householder is 60 to 64 years
renter_60_to_64_moe	bigint	yes	90% CI margin of error for renter_60_to_64 (Census variable B25007_018M; negative sentinels normalized to null)
renter_65_to_74	long	yes	Renter-occupied units where householder is 65 to 74 years
renter_65_to_74_moe	bigint	yes	90% CI margin of error for renter_65_to_74 (Census variable B25007_019M; negative sentinels normalized to null)
renter_75_to_84	long	yes	Renter-occupied units where householder is 75 to 84 years
renter_75_to_84_moe	bigint	yes	90% CI margin of error for renter_75_to_84 (Census variable B25007_020M; negative sentinels normalized to null)
renter_85_and_over	long	yes	Renter-occupied units where householder is 85 years and over
renter_85_and_over_moe	bigint	yes	90% CI margin of error for renter_85_and_over (Census variable B25007_021M; negative sentinels normalized to null)

acs_housing_year_built_detail · table

Housing units bracketed by decade of structure built (ACS 5-Year table B25034), at state and county levels — ten brackets (built 2020 or later, 2010-2019, 2000-2009, 1990-1999, 1980-1989, 1970-1979, 1960-1969, 1950-1959, 1940-1949, and 1939 or earlier) plus the table's own total. Complements acs_housing_tenure's median_year_built: a median only tells you 50% of units are older/newer than itself, not the share relative to an arbitrary threshold (e.g. "percent of housing stock built before 1980") — these brackets answer that directly. Verified live 2026-09-11: bracket sum matches the table's own total exactly (Bronx County NY, 2023 ACS5); pre-1939 share is far higher in an established Northeast county (Nantucket MA ~17%) than a Sun Belt boomtown (Maricopa AZ ~1%), matching known housing-stock-age geography. Tract-grain is NOT included — this codebase's declarative ACS infrastructure has no per-county tract fan-out mechanism; state and county grain only (see all_geographies).

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_units	long	yes	Total housing units (all vintages) — brackets below should sum to this
total_units_moe	bigint	yes	90% CI margin of error for total_units (Census variable B25034_001M; negative sentinels normalized to null)
built_2020_or_later	long	yes	Housing units built 2020 or later
built_2020_or_later_moe	bigint	yes	90% CI margin of error for built_2020_or_later (Census variable B25034_002M; negative sentinels normalized to null)
built_2010_to_2019	long	yes	Housing units built 2010 to 2019
built_2010_to_2019_moe	bigint	yes	90% CI margin of error for built_2010_to_2019 (Census variable B25034_003M; negative sentinels normalized to null)
built_2000_to_2009	long	yes	Housing units built 2000 to 2009
built_2000_to_2009_moe	bigint	yes	90% CI margin of error for built_2000_to_2009 (Census variable B25034_004M; negative sentinels normalized to null)
built_1990_to_1999	long	yes	Housing units built 1990 to 1999
built_1990_to_1999_moe	bigint	yes	90% CI margin of error for built_1990_to_1999 (Census variable B25034_005M; negative sentinels normalized to null)
built_1980_to_1989	long	yes	Housing units built 1980 to 1989
built_1980_to_1989_moe	bigint	yes	90% CI margin of error for built_1980_to_1989 (Census variable B25034_006M; negative sentinels normalized to null)
built_1970_to_1979	long	yes	Housing units built 1970 to 1979
built_1970_to_1979_moe	bigint	yes	90% CI margin of error for built_1970_to_1979 (Census variable B25034_007M; negative sentinels normalized to null)
built_1960_to_1969	long	yes	Housing units built 1960 to 1969
built_1960_to_1969_moe	bigint	yes	90% CI margin of error for built_1960_to_1969 (Census variable B25034_008M; negative sentinels normalized to null)
built_1950_to_1959	long	yes	Housing units built 1950 to 1959
built_1950_to_1959_moe	bigint	yes	90% CI margin of error for built_1950_to_1959 (Census variable B25034_009M; negative sentinels normalized to null)
built_1940_to_1949	long	yes	Housing units built 1940 to 1949
built_1940_to_1949_moe	bigint	yes	90% CI margin of error for built_1940_to_1949 (Census variable B25034_010M; negative sentinels normalized to null)
built_1939_or_earlier	long	yes	Housing units built 1939 or earlier
built_1939_or_earlier_moe	bigint	yes	90% CI margin of error for built_1939_or_earlier (Census variable B25034_011M; negative sentinels normalized to null)

acs_income_distribution · table

Household counts by ACS income bracket (under $10k through $200k+) plus total households and the Gini index of income inequality, from the ACS 5-Year survey at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_households	long	yes	Total households
total_households_moe	bigint	yes	90% CI margin of error for total_households (Census variable B19001_001M; negative sentinels normalized to null)
income_under_10k	long	yes	Households with income under $10,000
income_under_10k_moe	bigint	yes	90% CI margin of error for income_under_10k (Census variable B19001_002M; negative sentinels normalized to null)
income_10k_to_25k	long	yes	Households with income $10,000 to $24,999
income_25k_to_50k	long	yes	Households with income $25,000 to $49,999
income_50k_to_100k	long	yes	Households with income $50,000 to $99,999
income_100k_to_200k	long	yes	Households with income $100,000 to $199,999
income_200k_plus	long	yes	Households with income $200,000 or more
income_200k_plus_moe	bigint	yes	90% CI margin of error for income_200k_plus (Census variable B19001_017M; negative sentinels normalized to null)
gini_index	double	yes	Gini index of income inequality
gini_index_moe	double	yes	90% CI margin of error for gini_index (Census variable B19083_001M; negative sentinels normalized to null)

decennial_housing · table

Total, occupied, and vacant housing unit counts from the Decennial Census, at state and county levels, for census years 2000, 2010, and 2020 (every 10 years).

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
total_housing_units	long	yes	Total housing units
occupied_units	long	yes	Occupied housing units
vacant_units	long	yes	Vacant housing units

pep_population · table

Population Estimates Program (PEP) annual population estimate, at state and county levels, for the years between decennial censuses. Data years <= 2020 come from the pep/population dataset (which also includes a population density column for those years); data years >= 2021 come from the shared latest pep/charv vintage (population only). The vintage column identifies which of the two source datasets produced each row, so the two never double-claim a data year. KNOWN GAP: year 2020 itself is absent from production despite being within the pep/population vintage's range — see observedCoverage below (contiguous: false) before assuming a query over 2019-2021 has every year.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
population	long	yes	Total population estimate
density	double	yes	Population density (only for pep/population data years, i.e. <= 2020)
vintage	string	yes	PEP data vintage used to fetch this row: either the data year itself (pep/population, data years <= 2020) or the shared latest published vintage (pep/charv, data years >= 2021). Distinguishes the two source datasets so a data year is never ambiguous between them.

cbp_establishments · table

County Business Patterns provides annual data on business establishments, employment, and payroll by industry (NAICS) at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
naics_code	string	yes	2017 NAICS industry code
establishments	long	yes	Number of establishments
employees	long	yes	Number of employees (mid-March)
annual_payroll	long	yes	Annual payroll ($1,000)
first_quarter_payroll	long	yes	First quarter payroll ($1,000)

acs1_population · table

ACS 1-Year population estimates (total, male, female population, median age), state level only (areas with 65,000+ population — no county breakout). More current than the 5-year table but based on a smaller annual sample, so estimates carry wider margins of error.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
total_population	long	yes	Total population
total_population_moe	bigint	yes	90% CI margin of error for total_population (Census variable B01001_001M; negative sentinels normalized to null)
male_population	long	yes	Male population
male_population_moe	bigint	yes	90% CI margin of error for male_population (Census variable B01001_002M; negative sentinels normalized to null)
female_population	long	yes	Female population
female_population_moe	bigint	yes	90% CI margin of error for female_population (Census variable B01001_026M; negative sentinels normalized to null)
median_age	double	yes	Median age
median_age_moe	double	yes	90% CI margin of error for median_age (Census variable B01002_001M; negative sentinels normalized to null)

acs1_income · table

Household median income and per capita income from the ACS 1-Year survey, state level only (areas with 65,000+ population — no county breakout). More current than the 5-year acs_income table (about 1 year behind vs. 2), but based on a smaller annual sample, so estimates carry wider margins of error.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
median_household_income	long	yes	Median household income
median_household_income_moe	bigint	yes	90% CI margin of error for median_household_income (Census variable B19013_001M; negative sentinels normalized to null)
per_capita_income	long	yes	Per capita income
per_capita_income_moe	bigint	yes	90% CI margin of error for per_capita_income (Census variable B19301_001M; negative sentinels normalized to null)

economic_census · table

Economic Census provides comprehensive business statistics including establishments, employment, payroll, and sales by industry. Uses dimension resolver to handle NAICS version differences: - 2017: Uses NAICS2017 variable - 2022: Uses NAICS2022 variable Partitioned by year only (not geography) to reduce file count.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
naics_code	string	yes	NAICS industry code (version depends on census year)
establishments	long	yes	Number of establishments
employees	long	yes	Number of employees
payroll	long	yes	Annual payroll ($1,000)
sales	long	yes	Total sales/receipts ($1,000)

saipe_poverty · table

Small Area Income and Poverty Estimates (SAIPE) annual estimates of median household income, poverty count, and poverty rate (all ages and ages 0-17), at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
all_ages_poverty_count	long	yes	All ages in poverty count estimate
all_ages_poverty_rate	double	yes	All ages poverty rate estimate
child_poverty_count	long	yes	Ages 0-17 in poverty count estimate
child_poverty_rate	double	yes	Ages 0-17 poverty rate estimate
median_household_income	long	yes	Median household income estimate

sahie_insurance · table

Small Area Health Insurance Estimates (SAHIE) annual estimates of insured/uninsured population counts and insured/uninsured rates, at state and county levels.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
insured_count	long	yes	Number insured estimate
uninsured_count	long	yes	Number uninsured estimate
insured_rate	double	yes	Percent insured estimate
uninsured_rate	double	yes	Percent uninsured estimate

bds_dynamics · table

Business Dynamics Statistics annual job creation, job destruction, net job creation, establishment, firm, and employee counts, at state level. No industry or firm- characteristics breakdown in this table.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
job_creation	long	yes	Number of jobs created
job_destruction	long	yes	Number of jobs destroyed
net_job_creation	long	yes	Net job creation (creation - destruction)
establishments	long	yes	Number of establishments
firms	long	yes	Number of firms
employees	long	yes	Number of employees

abs_characteristics · table

Annual Business Survey (ABS) employer-firm counts, sales receipts, employee counts, and annual payroll, at state level. No owner-demographic (race, sex, veteran, education) breakdown in this table.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
firms	long	yes	Number of employer firms
receipts	long	yes	Sales receipts ($1,000)
employees	long	yes	Number of employees
payroll	long	yes	Annual payroll ($1,000)

nonemployer_statistics · table

Nonemployer Statistics establishment counts and total receipts by NAICS industry, for businesses with no paid employees (self-employed/unincorporated), at state and county levels. Physically partitioned by year only (not geography) to reduce file count.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
county	string	yes	County FIPS code (3 digits, within state)
county_fips	string	yes	5-digit county FIPS code (state + county) for joining to geo.counties
naics_code	string	yes	NAICS industry code (canonical header; source variable is the vintage-specific NAICS20xx, normalized by CensusResponseTransformer)
establishments	long	yes	Number of nonemployer establishments
receipts	long	yes	Total receipts ($1,000)

building_permits · table

Building Permits Survey tracks new privately-owned residential construction permits by state. Uses December cumulative (YTD) totals. Data from https://www2.census.gov/econ/bps/State/ URL format is stYYMMy.txt where YYMM is year-month code (e.g., 2212 = Dec 2022). Partition 'period_code' stores the raw YYMM code for URL compatibility only — it is NOT a year (e.g. 2012 is Dec 2020, not 2012) and must never be filtered as one. Use the derived survey_year / survey_month columns (parsed from survey_date) for year/month filtering.

Column	Type	Null	Description
survey_date	string	yes	Survey date in YYYYMM format
state_fips	string	yes	State FIPS code (2-digit)
state_name	string	yes	State name
single_family_units	string	yes	Single-family housing units authorized
single_family_value_thousands	string	yes	Value of single-family permits ($1000)
duplex_units	string	yes	Duplex housing units authorized
duplex_value_thousands	string	yes	Value of duplex permits ($1000)
three_four_unit_units	string	yes	3-4 unit housing units authorized
three_four_unit_value_thousands	string	yes	Value of 3-4 unit permits ($1000)
five_plus_unit_units	string	yes	5+ unit housing units authorized
five_plus_unit_value_thousands	string	yes	Value of 5+ unit permits ($1000)
survey_year	INTEGER	yes	Calendar year parsed from survey_date (YYYYMM); the real time filter target
survey_month	INTEGER	yes	Calendar month (1-12) parsed from survey_date (YYYYMM)

qwi_employment · table

LEHD Quarterly Workforce Indicators, Sex-by-Age tabulation at state level (all industries, private ownership). One row per state x quarter x demographic cell. Ingested from the per-state bulk CSV rather than the per-quarter API: one file carries that state's whole history, so a release costs 51 fetches instead of ~4,700, and every published measure and suppression flag is retained rather than a five-variable projection. Payroll is entirely NULL (sPayroll=5) in every row as of R2021Q4 onward -- Census permanently suppressed QWI Total Payroll measures for privacy protection and redirects users to BLS QCEW instead; this is a source-side omission, not an ingestion gap.

Column	Type	Null	Description
periodicity	varchar	yes
seasonadj	varchar	yes
geo_level	varchar	yes
geography	varchar	yes
ind_level	varchar	yes
industry	varchar	yes
ownercode	varchar	yes
sex	varchar	yes
agegrp	varchar	yes
race	varchar	yes
ethnicity	varchar	yes
education	varchar	yes
firmage	varchar	yes
firmsize	varchar	yes
year	int	yes
quarter	int	yes
agg_level	varchar	yes
Emp	bigint	yes
EmpEnd	bigint	yes
EmpS	bigint	yes
EmpTotal	bigint	yes
EmpSpv	bigint	yes
HirA	bigint	yes
HirN	bigint	yes
HirR	bigint	yes
Sep	bigint	yes
HirAEnd	bigint	yes
SepBeg	bigint	yes
HirAEndRepl	bigint	yes
HirAEndR	double	yes
SepBegR	double	yes
HirAEndReplR	double	yes
HirAS	bigint	yes
HirNS	bigint	yes
SepS	bigint	yes
SepSnx	bigint	yes
TurnOvrS	double	yes
FrmJbGn	bigint	yes
FrmJbLs	bigint	yes
FrmJbC	bigint	yes
FrmJbGnS	bigint	yes
FrmJbLsS	bigint	yes
FrmJbCS	bigint	yes
EarnS	bigint	yes
EarnBeg	bigint	yes
EarnHirAS	bigint	yes
EarnHirNS	bigint	yes
EarnSepS	bigint	yes
Payroll	bigint	yes
sEmp	int	yes
sEmpEnd	int	yes
sEmpS	int	yes
sEmpTotal	int	yes
sEmpSpv	int	yes
sHirA	int	yes
sHirN	int	yes
sHirR	int	yes
sSep	int	yes
sHirAEnd	int	yes
sSepBeg	int	yes
sHirAEndRepl	int	yes
sHirAEndR	int	yes
sSepBegR	int	yes
sHirAEndReplR	int	yes
sHirAS	int	yes
sHirNS	int	yes
sSepS	int	yes
sSepSnx	int	yes
sTurnOvrS	int	yes
sFrmJbGn	int	yes
sFrmJbLs	int	yes
sFrmJbC	int	yes
sFrmJbGnS	int	yes
sFrmJbLsS	int	yes
sFrmJbCS	int	yes
sEarnS	int	yes
sEarnBeg	int	yes
sEarnHirAS	int	yes
sEarnHirNS	int	yes
sEarnSepS	int	yes
sPayroll	int	yes

lodes_workplace · table

LEHD Origin-Destination Employment Statistics (LODES) Workplace Area Characteristics (WAC): total job counts at the workplace census block level, broken out by worker age bracket (<=29, 30-54, 55+) and by monthly earnings tier, partitioned by state and year.

Column	Type	Null	Description
w_geocode	string	yes	Workplace census block code (15 digits)
c000	string	yes	Total number of jobs
ca01	string	yes	Jobs for workers age 29 or younger
ca02	string	yes	Jobs for workers age 30 to 54
ca03	string	yes	Jobs for workers age 55 or older
ce01	string	yes	Jobs with monthly earnings $1,250 or less
ce02	string	yes	Jobs with monthly earnings $1,251 to $3,333
ce03	string	yes	Jobs with monthly earnings $3,333 or more

acs_earnings_by_education · table

Median earnings in the past 12 months by sex and educational attainment, for the population 25 years and over, from the ACS 5-Year survey table B20004, state level only (no county breakout — the table is fetched with for=state:, unlike most other acs_ tables in this schema which also carry a county grain). Reports total, male, and female median earnings (dollars) at 6 attainment levels: less than high school, high school graduate (includes equivalency), some college or associate's degree, bachelor's degree, and graduate or professional degree. Complements acs_education (population counts by attainment, no earnings) and acs_income (household income, not tied to the householder's own educational attainment).

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
median_earnings_total	long	yes	Median earnings, total population 25+ with earnings
median_earnings_total_moe	bigint	yes	90% CI margin of error for median_earnings_total (Census variable B20004_001M; negative sentinels normalized to null)
median_earnings_less_than_hs	long	yes	Median earnings, less than high school graduate
median_earnings_less_than_hs_moe	bigint	yes	90% CI margin of error for median_earnings_less_than_hs (Census variable B20004_002M; negative sentinels normalized to null)
median_earnings_hs_graduate	long	yes	Median earnings, high school graduate (includes equivalency)
median_earnings_hs_graduate_moe	bigint	yes	90% CI margin of error for median_earnings_hs_graduate (Census variable B20004_003M; negative sentinels normalized to null)
median_earnings_some_college	long	yes	Median earnings, some college or associate's degree
median_earnings_some_college_moe	bigint	yes	90% CI margin of error for median_earnings_some_college (Census variable B20004_004M; negative sentinels normalized to null)
median_earnings_bachelors	long	yes	Median earnings, bachelor's degree
median_earnings_bachelors_moe	bigint	yes	90% CI margin of error for median_earnings_bachelors (Census variable B20004_005M; negative sentinels normalized to null)
median_earnings_graduate_degree	long	yes	Median earnings, graduate or professional degree
median_earnings_graduate_degree_moe	bigint	yes	90% CI margin of error for median_earnings_graduate_degree (Census variable B20004_006M; negative sentinels normalized to null)
median_earnings_male_total	long	yes	Median earnings, male, total 25+ with earnings
median_earnings_male_total_moe	bigint	yes	90% CI margin of error for median_earnings_male_total (Census variable B20004_007M; negative sentinels normalized to null)
median_earnings_male_less_than_hs	long	yes	Median earnings, male, less than high school graduate
median_earnings_male_less_than_hs_moe	bigint	yes	90% CI margin of error for median_earnings_male_less_than_hs (Census variable B20004_008M; negative sentinels normalized to null)
median_earnings_male_hs_graduate	long	yes	Median earnings, male, high school graduate (includes equivalency)
median_earnings_male_hs_graduate_moe	bigint	yes	90% CI margin of error for median_earnings_male_hs_graduate (Census variable B20004_009M; negative sentinels normalized to null)
median_earnings_male_some_college	long	yes	Median earnings, male, some college or associate's degree
median_earnings_male_some_college_moe	bigint	yes	90% CI margin of error for median_earnings_male_some_college (Census variable B20004_010M; negative sentinels normalized to null)
median_earnings_male_bachelors	long	yes	Median earnings, male, bachelor's degree
median_earnings_male_bachelors_moe	bigint	yes	90% CI margin of error for median_earnings_male_bachelors (Census variable B20004_011M; negative sentinels normalized to null)
median_earnings_male_graduate_degree	long	yes	Median earnings, male, graduate or professional degree
median_earnings_male_graduate_degree_moe	bigint	yes	90% CI margin of error for median_earnings_male_graduate_degree (Census variable B20004_012M; negative sentinels normalized to null)
median_earnings_female_total	long	yes	Median earnings, female, total 25+ with earnings
median_earnings_female_total_moe	bigint	yes	90% CI margin of error for median_earnings_female_total (Census variable B20004_013M; negative sentinels normalized to null)
median_earnings_female_less_than_hs	long	yes	Median earnings, female, less than high school graduate
median_earnings_female_less_than_hs_moe	bigint	yes	90% CI margin of error for median_earnings_female_less_than_hs (Census variable B20004_014M; negative sentinels normalized to null)
median_earnings_female_hs_graduate	long	yes	Median earnings, female, high school graduate (includes equivalency)
median_earnings_female_hs_graduate_moe	bigint	yes	90% CI margin of error for median_earnings_female_hs_graduate (Census variable B20004_015M; negative sentinels normalized to null)
median_earnings_female_some_college	long	yes	Median earnings, female, some college or associate's degree
median_earnings_female_some_college_moe	bigint	yes	90% CI margin of error for median_earnings_female_some_college (Census variable B20004_016M; negative sentinels normalized to null)
median_earnings_female_bachelors	long	yes	Median earnings, female, bachelor's degree
median_earnings_female_bachelors_moe	bigint	yes	90% CI margin of error for median_earnings_female_bachelors (Census variable B20004_017M; negative sentinels normalized to null)
median_earnings_female_graduate_degree	long	yes	Median earnings, female, graduate or professional degree
median_earnings_female_graduate_degree_moe	bigint	yes	90% CI margin of error for median_earnings_female_graduate_degree (Census variable B20004_018M; negative sentinels normalized to null)

acs_nativity_by_education · table

Joint nativity-by-education counts for the population 25 years and over, from the ACS 5-Year survey table B06009 (Place of Birth by Educational Attainment in the United States), state level only (no county breakout). Unlike acs_nativity (population by nativity only) and acs_education (population by attainment only), this table carries the actual joint counts — e.g. foreign_born_bachelors_or_higher is the real number of foreign-born adults with a bachelor's degree or higher, not an estimate derived by assuming independence across the two separate tables.

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
pop_25_plus	long	yes	Total population 25 years and over
pop_25_plus_moe	bigint	yes	90% CI margin of error for pop_25_plus (Census variable B06009_001M; negative sentinels normalized to null)
foreign_born_pop_25_plus	long	yes	Foreign-born population 25 years and over
foreign_born_pop_25_plus_moe	bigint	yes	90% CI margin of error for foreign_born_pop_25_plus (Census variable B06009_025M; negative sentinels normalized to null)
foreign_born_less_than_hs	long	yes	Foreign born, less than high school graduate
foreign_born_less_than_hs_moe	bigint	yes	90% CI margin of error for foreign_born_less_than_hs (Census variable B06009_026M; negative sentinels normalized to null)
foreign_born_hs_graduate	long	yes	Foreign born, high school graduate (includes equivalency)
foreign_born_hs_graduate_moe	bigint	yes	90% CI margin of error for foreign_born_hs_graduate (Census variable B06009_027M; negative sentinels normalized to null)
foreign_born_some_college	long	yes	Foreign born, some college or associate's degree
foreign_born_some_college_moe	bigint	yes	90% CI margin of error for foreign_born_some_college (Census variable B06009_028M; negative sentinels normalized to null)
foreign_born_bachelors	long	yes	Foreign born, bachelor's degree
foreign_born_bachelors_moe	bigint	yes	90% CI margin of error for foreign_born_bachelors (Census variable B06009_029M; negative sentinels normalized to null)
foreign_born_graduate_degree	long	yes	Foreign born, graduate or professional degree
foreign_born_graduate_degree_moe	bigint	yes	90% CI margin of error for foreign_born_graduate_degree (Census variable B06009_030M; negative sentinels normalized to null)
foreign_born_bachelors_or_higher	long	yes	Foreign born with a bachelor's degree or higher (029E + 030E)
native_bachelors_or_higher	long	yes	Native-born with a bachelor's degree or higher — sums the bachelor's (011E/017E/023E) and graduate-or-professional (012E/018E/024E) cells across B06009's three native-birthplace categories (born in state of residence, born in another US state, native born outside the US).

acs_income_by_nativity · table

Median household income and household counts by nativity of the householder (total, native, foreign born, foreign born naturalized citizen, foreign born not a citizen), from the ACS 5-Year subject table S0501 (Selected Characteristics of the Native and Foreign-Born Populations), state level only (no county breakout). S0501 classifies households by the nativity of the population column; row 089 (households_) is the households-count denominator and row 101 (median_household_income_) the dollar estimate, for each of the 5 nativity columns S0501 defines (C01 total, C02 native, C03 foreign born, C04 foreign born naturalized citizen, C05 foreign born not a citizen). Fetched from the acs5/subject endpoint (a different Census API dataset path than the acs5 detailed-table endpoint the other acs_* tables in this schema use).

Column	Type	Null	Description
geo_name	string	yes	Geographic area name
state	string	yes	State FIPS code (2 digits)
households_total	long	yes	Total households
households_native	long	yes	Households classified under the native population
households_foreign_born	long	yes	Households classified under the foreign-born population
households_naturalized	long	yes	Households classified under the foreign-born, naturalized-citizen population
households_noncitizen	long	yes	Households classified under the foreign-born, not-a-citizen population
median_household_income_total	long	yes	Median household income, all households (dollars)
median_household_income_native	long	yes	Median household income, native population (dollars)
median_household_income_foreign_born	long	yes	Median household income, foreign-born population (dollars)
median_household_income_naturalized	long	yes	Median household income, foreign-born naturalized-citizen population (dollars)
median_household_income_noncitizen	long	yes	Median household income, foreign-born not-a-citizen population (dollars)

cps_voting_supplement · table

State-level reported voting and registration rates for the citizen voting-age population, from the Census Bureau's Current Population Survey (CPS) Voting and Registration Supplement — a biennial November survey module (even years only: congressional and presidential election years), not part of the ACS and not on the acs5 endpoint. The CPS API (api.census.gov/data/{year}/cps/voting/nov) returns person-level survey microdata (one row per respondent, with person weight PWSSWGT), not a pre-tabulated table, so this table is a weighted state-level aggregation of that microdata computed by CpsVotingSupplementTransformer: voted_rate_pct / registered_rate_pct are the population-weighted share of respondents answering "Yes" to PES1 (did you vote?) / PES2 (registered to vote?), among respondents who gave a Yes/No answer (excluding "Not in Universe", "Refused", "Don't Know"). population_reported_voted / population_reported_registered are the weighted denominators (the estimated citizen voting-age population that answered the question); sample_size_voted / sample_size_registered are the unweighted respondent counts backing each estimate, for margin-of-error context. Available biennially from 1996 (the earliest api.census.gov vintage for this dataset with PES1/PES2 variable coding stable through the most recent cycle — the November 1994 file predates api.census.gov and used different variable codes, PES3/PES4, for the same two questions, so 1994 is not in this table). CAUTION for turnout-gap or turnout-rate comparisons across states: this table is SELF-REPORTED turnout among the citizen voting-age population, known to systematically OVER-REPORT relative to actual counted votes (social-desirability bias) — it is NOT voting-eligible population (VEP), the standard denominator the turnout literature actually uses (Cantoni & Pons; McDonald/US Elections Project). For any question comparing turnout RATES between groups of states (e.g. by a policy like voter-ID requirements), prefer pairing real certified vote totals (e.g. officials.presidential_election_results or an equivalent FEC/certified- results table) with a VEP-style population denominator instead of this table's self-reported rate — this table alone will overstate turnout by roughly 10 points and can misstate a gap's size even when the direction is right.

Column	Type	Null	Description
state	string	yes	State FIPS code (2 digits), from the Census API for=state:* geography clause
sample_size_voted	long	yes	Unweighted respondent count answering the vote question (PES1) Yes or No
population_reported_voted	double	yes	Weighted citizen voting-age population answering the vote question Yes or No
population_voted	double	yes	Weighted population reporting they voted (PES1 = Yes)
voted_rate_pct	double	yes	Reported voting rate — 100 * population_voted / population_reported_voted
sample_size_registered	long	yes	Unweighted respondent count answering the registration question (PES2) Yes or No
population_reported_registered	double	yes	Weighted citizen voting-age population answering the registration question Yes or No
population_registered	double	yes	Weighted population reporting they are registered (PES2 = Yes)
registered_rate_pct	double	yes	Reported registration rate — 100 * population_registered / population_reported_registered