Census Bureau SAIPE state-and-county bulk files (keyless official text downloads, U.S. public domain): 510 per-state files stacked into a county x estimate-year panel (3,140-3,142 publishable counties per vintage, 31,408 rows over 2015-2024) with all-ages and child (0-17) poverty counts and rates plus 90% confidence intervals, median household income with intervals, year-over-year and 5-year poverty-rate momentum in percentage points and income YoY percent change. A documented 0-100 household-stress score (45% all-ages poverty rate + 35% child poverty rate + 20% inverse median income, winsorized at 1/99 and min-maxed within each year) is ranked nationally (stress_rank) and within each state, tiered s1-s4, with persistent-high-poverty (>=20% for 3 straight years), improving (YoY <= -1pp) and worsening (YoY >= +1pp) flags. Primary key: (county_fips, estimate_year). Cadence: yearly; each estimate year comes from its own SAIPE release (vintage stack, methodology revisions not restated), as_of is the latest vintage's file-release date and identical input produces an identical content hash. Caveats: model-based estimates (use the CI columns for significance); county-boundary revisions (notably Connecticut 2022) yield null momentum, never fabricated links. Sample use: order by stress_rank within an estimate year for the most stressed counties, or filter state_code for within-state household-strain geography.

Les titres et les descriptions proviennent des sources de données, en anglais.

Source: US County Poverty & Income Intelligence
Lignes: 31 408
Colonnes: 34
Cadence de la source: Annuelle
Dernière actualisation: 1 oct. 2026
Thème: poverty

Colonne	Type	Description
as_of	string	Release date (ISO) of the latest vintage's SAIPE file; identical input yields an identical content hash. (unit: date)
estimate_year	integer	SAIPE estimate reference year. (unit: year)
county_fips	string	5-digit FIPS (state 2 + county 3); stable primary key with estimate_year. (unit: id)
county_name	string	County-equivalent name from the SAIPE file.
state_code	string	USPS two-letter state/District code. (unit: code)
state_name	string	State/District name for the state_code.
country_code	string	Constant USA join key. (unit: code)
poverty_count	float	Modeled number of people in poverty (all ages). (unit: persons)
poverty_count_ci_lo	float	Lower 90% CI bound for poverty_count. (unit: persons)
poverty_count_ci_hi	float	Upper 90% CI bound for poverty_count. (unit: persons)
poverty_rate	float	Modeled poverty rate, all ages. (unit: percent)
poverty_rate_ci_lo	float	Lower bound of the 90% confidence interval for poverty_rate. (unit: percent)
poverty_rate_ci_hi	float	Upper bound of the 90% confidence interval for poverty_rate. (unit: percent)
child_poverty_count	float	Modeled number of related children ages 0-17 in poverty. (unit: persons)
child_poverty_count_ci_lo	float	Lower 90% CI bound for child_poverty_count. (unit: persons)
child_poverty_count_ci_hi	float	Upper 90% CI bound for child_poverty_count. (unit: persons)
child_poverty_rate	float	Modeled poverty rate, ages 0-17. (unit: percent)
child_poverty_rate_ci_lo	float	Lower 90% CI bound for child_poverty_rate. (unit: percent)
child_poverty_rate_ci_hi	float	Upper 90% CI bound for child_poverty_rate. (unit: percent)
median_hh_income	float	Modeled median household income. (unit: USD)
median_hh_income_ci_lo	float	Lower 90% CI bound for median_hh_income. (unit: USD)
median_hh_income_ci_hi	float	Upper 90% CI bound for median_hh_income. (unit: USD)
poverty_rate_yoy_pp	float	Year-over-year change in poverty_rate, percentage points; null when the county FIPS has no prior-year row (first year or boundary revision). (unit: percentage points)
poverty_rate_5y_pp	float	5-year change in poverty_rate, percentage points; null without a 5-year-prior row. (unit: percentage points)
median_income_yoy_pct	float	Year-over-year percent change in median_hh_income; null without a prior-year row. (unit: percent)
stress_score	float	Documented 0-100 household-stress score = 100(0.45min-max winsorized poverty_rate + 0.35min-max winsorized child_poverty_rate + 0.20min-max winsorized -median_hh_income), winsorized at 1/99 then min-maxed within each estimate year. (unit: score)
stress_rank	integer	National stress rank within the estimate year (1 = most stressed; ties broken by county_fips asc). (unit: rank)
stress_tier	string	Rank-quartile tier: s1 (most stressed 25%) .. s4. (unit: tier)
state_stress_rank	integer	Stress rank within the county's state and estimate year. (unit: rank)
persistent_high_poverty_flag	integer	1 when poverty_rate >= 20% for the current and two prior estimate years. (unit: flag)
improving_flag	integer	1 when poverty_rate_yoy_pp <= -1.0. (unit: flag)
worsening_flag	integer	1 when poverty_rate_yoy_pp >= +1.0. (unit: flag)
source_url	string	Canonical URL of the official SAIPE per-state bulk file for this row's vintage and state. (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	estimate_year	county_fips	county_name	state_code	state_name	country_code	poverty_count	poverty_count_ci_lo	poverty_count_ci_hi	poverty_rate	poverty_rate_ci_lo	poverty_rate_ci_hi	child_poverty_count	child_poverty_count_ci_lo	child_poverty_count_ci_hi	child_poverty_rate	child_poverty_rate_ci_lo	child_poverty_rate_ci_hi	median_hh_income	median_hh_income_ci_lo	median_hh_income_ci_hi	poverty_rate_yoy_pp	poverty_rate_5y_pp	median_income_yoy_pct	stress_score	stress_rank	stress_tier	state_stress_rank	source_url	row_hash
2026-01-07	2 015	01063	Greene County	AL	Alabama	USA	3 175	2 565	3 785	37,7	30,5	44,9	1 065	864	1 266	54,7	44,4	65	25 398	22 733	28 063	—	—	—	100	1	s1	1	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-al.txt	1df0841f2c664ffc
2026-01-07	2 015	01105	Perry County	AL	Alabama	USA	3 536	2 833	4 239	40	32,1	47,9	1 121	897	1 345	54,4	43,5	65,3	26 218	23 484	28 952	—	—	—	100	2	s1	2	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-al.txt	713858b3e14384c1
2026-01-07	2 015	21013	Bell County	KY	Kentucky	USA	11 772	10 223	13 321	44,7	38,8	50,6	3 239	2 735	3 743	56,8	48	65,6	23 968	21 529	26 407	—	—	—	100	3	s1	1	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-ky.txt	1f55f88ee377c8c8
2026-01-07	2 015	21051	Clay County	KY	Kentucky	USA	8 857	7 516	10 198	46,8	39,7	53,9	2 242	1 817	2 667	53	43	63	24 001	21 632	26 370	—	—	—	100	4	s1	2	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-ky.txt	9dc315f8fcc5f6ef
2026-01-07	2 015	21147	McCreary County	KY	Kentucky	USA	6 604	5 364	7 844	41,5	33,7	49,3	1 965	1 556	2 374	51,9	41,1	62,7	25 655	23 034	28 276	—	—	—	100	5	s1	3	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-ky.txt	58e7a013b4443f9c
2026-01-07	2 015	21189	Owsley County	KY	Kentucky	USA	1 847	1 439	2 255	42,4	33	51,8	576	452	700	61,6	48,4	74,8	23 341	20 890	25 792	—	—	—	100	6	s1	4	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-ky.txt	e83b8bfe5fe2bda1
2026-01-07	2 015	22035	East Carroll Parish	LA	Louisiana	USA	2 708	2 134	3 282	43,5	34,3	52,7	1 001	788	1 214	56,1	44,2	68	26 325	23 591	29 059	—	—	—	100	7	s1	1	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-la.txt	1b9df5c236c40131
2026-01-07	2 015	22065	Madison Parish	LA	Louisiana	USA	3 743	2 941	4 545	37,6	29,5	45,7	1 448	1 146	1 750	52,7	41,7	63,7	27 225	24 670	29 780	—	—	—	100	8	s1	2	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-la.txt	878db5502ccd8985
2026-01-07	2 015	28021	Claiborne County	MS	Mississippi	USA	3 717	3 123	4 311	46,3	38,9	53,7	1 073	878	1 268	54	44,2	63,8	26 959	24 153	29 765	—	—	—	100	9	s1	1	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-ms.txt	8241555995daae46
2026-01-07	2 015	28051	Holmes County	MS	Mississippi	USA	7 546	6 516	8 576	43,3	37,4	49,2	2 622	2 170	3 074	53,6	44,4	62,8	24 065	21 561	26 569	—	—	—	100	10	s1	2	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-ms.txt	5f6ab94de5655ee1

Profilé le 1 oct. 2026 à partir de l’instantané 20261001T163738Z-f5e459e50342

Mesuré

Complétude: 97,9 %
Lignes: 31 408
Colonnes: 34
Colonnes incomplètes: 3

Colonne	Manquant	Distinctes	Plage	Distribution
as_ofvarchar	0 %	1	—	2026-01-0731 408
estimate_yearbigint	0 %	11	2 015 → 2 024médiane 2 020
county_fipsvarchar	0 %	2 775	—	0100110 0100310 0100510
county_namevarchar	0 %	1 679	—	Washington County300 Jefferson County250 Franklin County240
state_codevarchar	0 %	55	—	TX2 540 GA1 590 VA1 330
state_namevarchar	0 %	57	—	Texas2 540 Georgia1 590 Virginia1 330
country_codevarchar	0 %	1	—	USA31 408
poverty_countdouble	0 %	12 430	2 → 1 675 802médiane 3 732	623 hors du 1er–99e centile
poverty_count_ci_lodouble	0 %	13 332	1 → 1 635 262médiane 2 955	625 hors du 1er–99e centile
poverty_count_ci_hidouble	0 %	15 898	3 → 1 716 342médiane 4 502	629 hors du 1er–99e centile
poverty_ratedouble	0 %	445	2,6 → 56,7médiane 13,8	587 hors du 1er–99e centile
poverty_rate_ci_lodouble	0 %	282	2,1 → 47,4médiane 11,1	589 hors du 1er–99e centile
poverty_rate_ci_hidouble	0 %	528	3,1 → 71médiane 16,5	586 hors du 1er–99e centile
child_poverty_countdouble	0 %	8 744	1 → 527 528médiane 1 118	616 hors du 1er–99e centile
child_poverty_count_ci_lodouble	0 %	7 910	0 → 510 057médiane 808	615 hors du 1er–99e centile
child_poverty_count_ci_hidouble	0 %	9 705	1 → 544 999médiane 1 426	622 hors du 1er–99e centile
child_poverty_ratedouble	0 %	604	2,4 → 88,7médiane 19,1	614 hors du 1er–99e centile
child_poverty_rate_ci_lodouble	0 %	414	1,5 → 60,2médiane 14	618 hors du 1er–99e centile
child_poverty_rate_ci_hidouble	0 %	731	3,2 → 100médiane 24,1	625 hors du 1er–99e centile
median_hh_incomedouble	0 %	25 956	22 045 → 177 457médiane 54 556	630 hors du 1er–99e centile
median_hh_income_ci_lodouble	0 %	22 285	19 634 → 168 768médiane 49 631	630 hors du 1er–99e centile
median_hh_income_ci_hidouble	0 %	22 158	23 923 → 186 146médiane 59 501	630 hors du 1er–99e centile
poverty_rate_yoy_ppdouble	10 %	661	-14,3 → 14,5médiane -0,2	554 hors du 1er–99e centile
poverty_rate_5y_ppdouble	50,1 %	769	-17,8 → 19,9médiane -0,9	307 hors du 1er–99e centile
median_income_yoy_pctdouble	10 %	29 721	-46,83 → 107,32médiane 4,13	566 hors du 1er–99e centile
stress_scoredouble	0 %	6 488	0 → 100médiane 39,32	629 hors du 1er–99e centile
stress_rankbigint	0 %	3 178	1 → 3 142médiane 1 571	618 hors du 1er–99e centile
stress_tiervarchar	0 %	4	—	s47 855 s27 853 s17 850
state_stress_rankbigint	0 %	265	1 → 254médiane 39	310 hors du 1er–99e centile
persistent_high_poverty_flagbigint	0 %	2	0 → 1médiane 0
improving_flagbigint	0 %	2	0 → 1médiane 0
worsening_flagbigint	0 %	2	0 → 1médiane 0
source_urlvarchar	0 %	407	—	https://www2.census.gov/programs-surveys/saipe/datasets/2015/2015-state-and-county/est15-tx.txt254 https://www2.census.gov/programs-surveys/saipe/datasets/2016/2016-state-and-county/est16-tx.txt254 https://www2.census.gov/programs-surveys/saipe/datasets/2017/2017-state-and-county/est17-tx.txt254
row_hashvarchar	0 %	37 113	—	0001138a98d3c9441 0001f1640a169bf51 0002fdfbe8d5310b1

1 oct. 2026Actuelle
20261001T163738Z-f5e459e50342 · sha256 f5e459e50342…
31 408 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

curl "https://datazimuts.com/v1/datasets/us_county_poverty_income_intel/us_county_poverty_income_annual" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/us_county_poverty_income_intel/us_county_poverty_income_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/us_county_poverty_income_intel/us_county_poverty_income_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 20261001T163738Z-f5e459e50342 et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.

APA

US County Poverty & Income Intelligence. (2026). US county poverty & income intelligence (annual) [Data set, snapshot 20261001T163738Z-f5e459e50342, sha256 f5e459e50342]. Datazimuts. Retrieved 2026-10-02, from https://datazimuts.com/fr/datasets/us_county_poverty_income_intel/us_county_poverty_income_annual?snapshot=20261001T163738Z-f5e459e50342

BibTeX

@misc{dz_us_county_poverty_income_intel_us_county_f5e459e5,
  title        = {{US county poverty \& income intelligence (annual)}},
  author       = {{US County Poverty \& Income Intelligence}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/fr/datasets/us_county_poverty_income_intel/us_county_poverty_income_annual?snapshot=20261001T163738Z-f5e459e50342}},
  note         = {Snapshot 20261001T163738Z-f5e459e50342, sha256 f5e459e50342335dd3764ad5aa3b83212a759b70eefae0548c073c3075451f69; accessed 2026-10-02}
}

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.

Type

Axe X

Valeur

Agrégat

Thème

HTML

<iframe src="https://datazimuts.com/embed/chart?dataset=us_county_poverty_income_intel%2Fus_county_poverty_income_annual&lang=fr&theme=auto&snapshot=20261001T163738Z-f5e459e50342&x=estimate_year&y=estimate_year&agg=avg" title="US county poverty & income intelligence (annual)" width="100%" height="380" style="border:0" loading="lazy"></iframe>

Connectez-vous pour commenter

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.

US county poverty & income intelligence (annual)

Suivre ce jeu de données

Citer cet instantané

Intégrer un tableau ou un graphique

Utiliser votre propre clé d’IA