US county socioeconomic intelligence (annual)
Census Bureau ACS 5-year estimates (keyless official bulk .dat, U.S. public domain): one row per county-equivalent (50 states + DC + Puerto Rico) for the 2024 vintage with median household and per-capita income (+MOEs), poverty rate, bachelor's-plus share, median home value and gross rent (+MOEs), owner-occupancy and uninsured shares recomputed from table cells, year-over-year change vs the 2023 vintage, national z-scores, a documented 0-100 prosperity_score (30% income + 25% inverse poverty + 20% college + 15% inverse uninsured + 10% home value, percentile ranks) ranked nationally and within-state with p1-p4 tiers, plus high-poverty, income-decline and insurance-gap flags. Primary key: (county_fips, acs_year). Cadence: yearly (upstream publishes one 5-year vintage per December). Caveats: MOEs only for direct estimates (derived shares carry none); vintages are in own-year dollars so YoY $ changes are not real terms; 5-year figures are period estimates. Sample use: join customers/orders/leads by county FIPS (or ZIP->county) to enrich demand, churn and lead-scoring models with income, poverty, education, housing and insurance signals.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Lignes
- 3 222
- Colonnes
- 38
- Cadence de la source
- Annuelle
- Dernière actualisation
- 29 sept. 2026
- Thème
- economy
| Colonne | Type | Description |
|---|---|---|
| as_of | string | Fixed vintage stamp: the ACS 5-year vintage year (identical input yields an identical content hash). (unit: year) |
| vintage | integer | ACS 5-year vintage year. (unit: year) |
| acs_year | integer | Reference vintage year of the row. (unit: year) |
| county_fips | string | 5-digit FIPS (state 2 + county 3); stable primary key with acs_year. (unit: id) |
| county_name | string | County-equivalent name (county, parish, borough, municipio, independent city). |
| state_fips | string | 2-digit state FIPS code. (unit: id) |
| state_code | string | USPS two-letter state/District code (PR for Puerto Rico). (unit: code) |
| state_name | string | State/District/Commonwealth name. |
| country_code | string | Constant USA join key. (unit: code) |
| median_hh_income | integer | Median household income, past 12 months, in vintage inflation-adjusted dollars (B19013_001). (unit: USD) |
| median_hh_income_moe | integer | Margin of error, 90% confidence, for median_hh_income. (unit: USD) |
| per_capita_income | integer | Per-capita income, past 12 months (B19301_001). (unit: USD) |
| per_capita_income_moe | integer | Margin of error for per_capita_income. (unit: USD) |
| poverty_rate_pct | float | Share of the poverty universe below the poverty line: B17001_002/B17001_001*100. (unit: percent) |
| college_plus_share_pct | float | Share of population 25+ with a bachelor's degree or higher: (B15003_022+023+024+025)/B15003_001*100. (unit: percent) |
| median_home_value | integer | Median value of owner-occupied housing units (B25077_001). (unit: USD) |
| median_home_value_moe | integer | Margin of error for median_home_value. (unit: USD) |
| median_gross_rent | integer | Median gross rent of renter-occupied units (B25064_001). (unit: USD) |
| median_gross_rent_moe | integer | Margin of error for median_gross_rent. (unit: USD) |
| owner_share_pct | float | Owner-occupied share of occupied units: B25003_002/B25003_001*100. (unit: percent) |
| uninsured_share_pct | float | Share of the civilian noninstitutionalized population with no health insurance: sum of the 18 B27001 'No health insurance coverage' cells / B27001_001*100. (unit: percent) |
| income_yoy_pct | float | Year-over-year change of median_hh_income vs the prior vintage, percent (own-year dollars, not real terms). (unit: percent) |
| poverty_yoy_pp | float | Year-over-year change of poverty_rate_pct vs the prior vintage, percentage points. (unit: percentage points) |
| home_value_yoy_pct | float | Year-over-year change of median_home_value vs the prior vintage, percent. (unit: percent) |
| rent_yoy_pct | float | Year-over-year change of median_gross_rent vs the prior vintage, percent. (unit: percent) |
| income_z | float | National z-score of median_hh_income across counties (sample std). (unit: z-score) |
| poverty_z | float | National z-score of poverty_rate_pct. (unit: z-score) |
| college_z | float | National z-score of college_plus_share_pct. (unit: z-score) |
| uninsured_z | float | National z-score of uninsured_share_pct. (unit: z-score) |
| prosperity_score | float | Documented 0-100 score = 100*(0.30*pct_rank (income) + 0.25*pct_rank(-poverty) + 0.20*pct_rank(college) + 0.15*pct_rank (-uninsured) + 0.10*pct_rank(home value)); null when any component is null. (unit: score) |
| prosperity_rank | integer | National prosperity rank (1 = most prosperous; ties broken by county_fips asc). (unit: rank) |
| prosperity_tier | string | Rank-quartile tier: p1 (top 25%) .. p4. (unit: tier) |
| state_prosperity_rank | integer | Prosperity rank within the county's state. (unit: rank) |
| high_poverty_flag | integer | 1 when poverty_rate_pct >= 20. (unit: flag) |
| income_decline_flag | integer | 1 when income_yoy_pct < 0. (unit: flag) |
| insurance_gap_flag | integer | 1 when uninsured_share_pct >= 12. (unit: flag) |
| source_url | string | Canonical URL of the official ACS 5-year bulk table directory for the vintage. (unit: URL) |
| row_hash | string | SHA-256 (16 hex) over the row's content fields; identical input yields an identical hash. (unit: hash) |
10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.
| as_of | vintage | acs_year | county_fips | county_name | state_fips | state_code | state_name | country_code | median_hh_income | median_hh_income_moe | per_capita_income | per_capita_income_moe | poverty_rate_pct | college_plus_share_pct | median_home_value | median_home_value_moe | median_gross_rent | median_gross_rent_moe | owner_share_pct | uninsured_share_pct | income_yoy_pct | poverty_yoy_pp | home_value_yoy_pct | rent_yoy_pct | income_z | poverty_z | college_z | uninsured_z | prosperity_score | prosperity_rank | prosperity_tier | state_prosperity_rank | high_poverty_flag | income_decline_flag | insurance_gap_flag | source_url | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2024 | 2 024 | 2 024 | 51610 | Falls Church city | 51 | VA | Virginia | USA | 143 262 | 15 432 | 88 790 | 6 035 | 4,02 | 80,53 | 1 055 600 | 60 266 | 2 190 | 104 | 52,53 | 1,7 | -7,41 | 0,38 | 4,99 | -0,68 | 0,024 | -1,451 | 5,466 | -1,476 | 99,79 | 1 | p1 | 1 | 0 | 1 | 0 | https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/ | d947d69a2c8bc970 |
| 2024 | 2 024 | 2 024 | 35028 | Los Alamos County | 35 | NM | New Mexico | USA | 147 139 | 10 556 | 74 704 | 4 431 | 3,53 | 69,74 | 495 800 | 24 607 | 1 375 | 119 | 74,83 | 2,49 | 2,76 | 0,6 | 9,57 | 5,12 | 0,024 | -1,516 | 4,409 | -1,314 | 99,28 | 2 | p1 | 1 | 0 | 0 | 0 | https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/ | 2bc7925257915fc1 |
| 2024 | 2 024 | 2 024 | 25007 | Dukes County | 25 | MA | Massachusetts | USA | 125 786 | 14 169 | 79 756 | 15 344 | 4,43 | 51,9 | 1 165 800 | 68 458 | 1 277 | 413 | 82,08 | 2,15 | 22,9 | -0,95 | 5,59 | -6,86 | 0,023 | -1,396 | 2,662 | -1,385 | 98,93 | 3 | p1 | 1 | 0 | 0 | 0 | https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/ | 47d2b7106fe54ae1 |
| 2024 | 2 024 | 2 024 | 34019 | Hunterdon County | 34 | NJ | New Jersey | USA | 141 715 | 3 618 | 72 227 | 2 148 | 3,99 | 57,38 | 517 200 | 12 844 | 1 687 | 51 | 85,14 | 2,8 | 1,62 | 0,15 | 3,69 | -1,17 | 0,024 | -1,454 | 3,199 | -1,251 | 98,93 | 4 | p1 | 1 | 0 | 0 | 0 | https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/ | 30e3f1997339bc7b |
| 2024 | 2 024 | 2 024 | 08035 | Douglas County | 08 | CO | Colorado | USA | 149 594 | 2 519 | 69 608 | 1 168 | 3,77 | 62,02 | 713 600 | 5 715 | 2 193 | 33 | 77,39 | 3,87 | 2,65 | 0,54 | 5,88 | 4,68 | 0,025 | -1,485 | 3,654 | -1,034 | 98,58 | 5 | p1 | 1 | 0 | 0 | 0 | https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/ | 6eb7bdca88f8d86a |
| 2024 | 2 024 | 2 024 | 27019 | Carver County | 27 | MN | Minnesota | USA | 125 946 | 3 700 | 60 893 | 1 598 | 4,42 | 50,44 | 453 600 | 7 396 | 1 514 | 76 | 81,48 | 2,15 | 2,28 | 0,2 | 6,25 | 4,85 | 0,023 | -1,397 | 2,52 | -1,384 | 98,27 | 6 | p1 | 1 | 0 | 0 | 0 | https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/ | a80970a60dc1f3d8 |
| 2024 | 2 024 | 2 024 | 25021 | Norfolk County | 25 | MA | Massachusetts | USA | 130 739 | 2 551 | 71 758 | 887 | 6,69 | 58,78 | 683 900 | 5 690 | 2 149 | 29 | 68,75 | 1,87 | 3,35 | 0,06 | 5,31 | 3,72 | 0,023 | -1,097 | 3,336 | -1,441 | 98,01 | 7 | p1 | 2 | 0 | 0 | 0 | https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/ | 6742c90e7428a4bd |
| 2024 | 2 024 | 2 024 | 36059 | Nassau County | 36 | NY | New York | USA | 146 202 | 1 472 | 64 198 | 729 | 5,42 | 49,68 | 684 700 | 2 833 | 2 252 | 41 | 81,95 | 3,8 | 1,95 | 0,1 | 3,95 | 2,6 | 0,024 | -1,265 | 2,445 | -1,046 | 97,55 | 8 | p1 | 1 | 0 | 0 | 0 | https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/ | 45bd452570d32584 |
| 2024 | 2 024 | 2 024 | 47187 | Williamson County | 47 | TN | Tennessee | USA | 135 594 | 4 044 | 66 219 | 1 469 | 4,64 | 62,69 | 751 900 | 14 835 | 1 969 | 53 | 78,81 | 4,43 | 3,35 | 0,13 | 11,61 | 3,91 | 0,023 | -1,368 | 3,719 | -0,919 | 97,5 | 9 | p1 | 1 | 0 | 0 | 0 | https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/ | a4555fa0f5aa0ee2 |
| 2024 | 2 024 | 2 024 | 24027 | Howard County | 24 | MD | Maryland | USA | 149 763 | 3 158 | 67 501 | 1 195 | 5,23 | 64,46 | 597 900 | 6 060 | 2 099 | 33 | 71,48 | 4,23 | 1,89 | 0,12 | 3,68 | 2,99 | 0,025 | -1,29 | 3,892 | -0,96 | 97,48 | 10 | p1 | 1 | 0 | 0 | 0 | https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/ | 9ff6252a7dad17b8 |
- Actuelle
20260929T075151Z-a245a46e401b · sha256 a245a46e401b…
3 222 lignes · premier instantané
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/census_acs_county_intel/us_county_socioeconomic_annual" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/census_acs_county_intel/us_county_socioeconomic_annual").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)Point d’accès API : https://datazimuts.com/v1/datasets/census_acs_county_intel/us_county_socioeconomic_annual
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.
D’où viennent ces données et ce qui en a été fait. Le travail des autres apparaît sous forme de décomptes ; seuls les projets partagés sont nommés.
Citer cet instantané
Épinglé à l’instantané 20260929T075151Z-a245a46e401b et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
Census ACS County Socioeconomic Intelligence. (2026). US county socioeconomic intelligence (annual) [Data set, snapshot 20260929T075151Z-a245a46e401b, sha256 a245a46e401b]. Datazimuts. Retrieved 2026-09-30, from https://datazimuts.com/fr/datasets/census_acs_county_intel/us_county_socioeconomic_annual?snapshot=20260929T075151Z-a245a46e401b
@misc{dz_census_acs_county_intel_us_county_socioe_a245a46e,
title = {{US county socioeconomic intelligence (annual)}},
author = {{Census ACS County Socioeconomic Intelligence}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/fr/datasets/census_acs_county_intel/us_county_socioeconomic_annual?snapshot=20260929T075151Z-a245a46e401b}},
note = {Snapshot 20260929T075151Z-a245a46e401b, sha256 a245a46e401bdbef123697d09e32cf1e462a528fe515c6e9b4e62209638a62b8; accessed 2026-09-30}
}Intégrer un tableau ou un graphique
Collez ce code dans n’importe quelle page. L’intégration est épinglée au même instantané, suit le thème clair ou sombre du lecteur et affiche toujours la source, la licence et un lien de retour.
<iframe src="https://datazimuts.com/embed/chart?dataset=census_acs_county_intel%2Fus_county_socioeconomic_annual&lang=fr&theme=auto&snapshot=20260929T075151Z-a245a46e401b&x=acs_year&y=vintage&agg=avg" title="US county socioeconomic intelligence (annual)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
Posez une question sur ce jeu de données. Les réponses viennent uniquement de sa fiche, de son profil mesuré et de son historique, et citent les faits utilisés.