US county wage & employment intelligence (annual)
Usage commercial OKÀ jour
Interroger dans l’atelierLe jeu complet n’est pas encore publié — revenez après la prochaine actualisation.Télécharger l'exemple CSVTélécharger l'exemple JSONLignes d’exemple seulement (jusqu’à 20) — pas le jeu de données complet.
Annual county-level U.S. wage and employment intelligence built as an intelligence layer over the Bureau of Labor Statistics Quarterly Census of Employment and Wages (QCEW) annual by-area files (keyless download, U.S. federal public domain): average weekly wage, annual pay, employment, establishments and total wages for every county, with BLS over-the-year changes, documented 0-100 wage-growth / jobs-growth / dynamism scores, ranks and tiers, surge/decline/elite-wage flags, and state + national wage context.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Lignes
- 3 275
- Colonnes
- 34
- Cadence de la source
- Annuelle
- Dernière actualisation
- 27 sept. 2026
- Thème
- economy
| Colonne | Type | Description |
|---|---|---|
| as_of | string | Reference year (YYYY) of the QCEW annual file; year-granular as-of stamping so identical upstream input yields an identical content hash. |
| year | integer | Reference year of the QCEW annual averages. |
| country | string | Canonical country name (United States) for every row. |
| country_code | string | ISO 3166-1 alpha-3 code for the United States (USA) — the join key for the 'Enrich with public data' feature. |
| state_code | string | Two-letter U.S. postal abbreviation of the county's state (or territory). |
| state_name | string | State / territory name of the county. |
| county_fips | string | Five-digit FIPS code identifying the county / county-equivalent. |
| county_name | string | County name as published in the QCEW area file. |
| annual_avg_employment | integer | Annual average covered employment (QCEW annual_avg_emplvl). |
| annual_avg_establishments | integer | Annual average number of establishments (QCEW annual_avg_estabs_count). |
| total_annual_wages_usd | integer | Total annual wages paid to covered workers, USD (QCEW total_annual_wages). |
| avg_weekly_wage_usd | float | Average weekly wage, USD (QCEW annual_avg_wkly_wage). |
| avg_annual_pay_usd | float | Average annual pay per employee, USD (QCEW avg_annual_pay). |
| employment_yoy_pct | float | Over-the-year percent change of annual average employment (BLS oty_annual_avg_emplvl_pct_chg), percent. |
| weekly_wage_yoy_pct | float | Over-the-year percent change of the average weekly wage (BLS oty_annual_avg_wkly_wage_pct_chg), percent. |
| establishments_yoy_pct | float | Over-the-year percent change of annual average establishments (BLS oty_annual_avg_estabs_count_pct_chg), percent. |
| total_wages_yoy_pct | float | Over-the-year percent change of total annual wages (BLS oty_total_annual_wages_pct_chg), percent. |
| wage_growth_score | float | Documented 0-100 score: min-max of winsorized weekly-wage YoY (bounds -10/+25 pct) across all counties. 100 = fastest wage growth. |
| jobs_growth_score | float | Documented 0-100 score: min-max of winsorized employment YoY (bounds -15/+20 pct) across all counties. 100 = fastest job growth. |
| county_dynamism_score | float | Documented 0-100 score: 50/50 blend of wage_growth_score and jobs_growth_score. 100 = hottest county labor market. |
| dynamism_rank | integer | Rank of county_dynamism_score across counties (1 = highest). |
| dynamism_tier | string | Quartile tier of dynamism_rank: d1 (top quartile) .. d4 (bottom quartile). |
| state_avg_weekly_wage_usd | float | Statewide average weekly wage (QCEW statewide aggregate), USD. |
| state_employment_yoy_pct | float | Statewide over-the-year employment change, percent. |
| us_avg_weekly_wage_usd | float | National average weekly wage (QCEW U.S.-total aggregate), USD. |
| us_employment_yoy_pct | float | National over-the-year employment change, percent. |
| wage_vs_state_pct | float | County average weekly wage minus state average, as percent of the state average. |
| wage_vs_us_pct | float | County average weekly wage minus the national average, as percent of the national average. |
| wage_surge_flag | boolean | True when weekly_wage_yoy_pct is at/above the panel p90 threshold (see provenance). |
| jobs_surge_flag | boolean | True when employment_yoy_pct is at/above the panel p90 threshold. |
| employment_decline_flag | boolean | True when employment_yoy_pct <= -3.0. |
| elite_wage_flag | boolean | True when avg_weekly_wage_usd is at/above the panel p90 wage level. |
| source_url | string | BLS QCEW annual by-area ZIP URL the panel was built from. |
| row_hash | string | SHA-256 (16 hex chars) over the row's content fields; identical input yields an identical hash, so a re-run on unchanged upstream data is a no-op. |
10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.
| as_of | year | country | country_code | state_code | state_name | county_fips | county_name | annual_avg_employment | annual_avg_establishments | total_annual_wages_usd | avg_weekly_wage_usd | avg_annual_pay_usd | employment_yoy_pct | weekly_wage_yoy_pct | establishments_yoy_pct | total_wages_yoy_pct | wage_growth_score | jobs_growth_score | county_dynamism_score | dynamism_rank | dynamism_tier | state_avg_weekly_wage_usd | state_employment_yoy_pct | us_avg_weekly_wage_usd | us_employment_yoy_pct | wage_vs_state_pct | wage_vs_us_pct | wage_surge_flag | jobs_surge_flag | employment_decline_flag | elite_wage_flag | source_url | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2025 | 2 025 | United States | USA | AL | Alabama | 01001 | Autauga County, Alabama | 12 976 | 1 190 | 687 324 140 | 1 019 | 52 968 | 4,8 | 4,3 | 6,2 | 9,2 | 40,86 | 56,57 | 48,72 | 261 | d1 | 1 240 | 0,6 | 1 514 | 0,5 | -17,82 | -32,69 | false | true | false | false | https://data.bls.gov/cew/data/files/2025/csv/2025_annual_by_area.zip | 166eb890a53f17c9 |
| 2025 | 2 025 | United States | USA | AL | Alabama | 01003 | Baldwin County, Alabama | 87 943 | 9 357 | 4 692 370 432 | 1 026 | 53 357 | 3,3 | 4,3 | 6,9 | 7,8 | 40,86 | 52,29 | 46,58 | 423 | d1 | 1 240 | 0,6 | 1 514 | 0,5 | -17,26 | -32,23 | false | true | false | false | https://data.bls.gov/cew/data/files/2025/csv/2025_annual_by_area.zip | 9723782427a545a9 |
| 2025 | 2 025 | United States | USA | AL | Alabama | 01005 | Barbour County, Alabama | 7 689 | 597 | 360 113 886 | 901 | 46 834 | -0,3 | 2,7 | 0,3 | 2,4 | 36,29 | 42 | 39,14 | 2 360 | d3 | 1 240 | 0,6 | 1 514 | 0,5 | -27,34 | -40,49 | false | false | false | false | https://data.bls.gov/cew/data/files/2025/csv/2025_annual_by_area.zip | 611222c416944bcf |
| 2025 | 2 025 | United States | USA | AL | Alabama | 01007 | Bibb County, Alabama | 4 917 | 468 | 275 205 753 | 1 076 | 55 967 | 1,8 | 5,5 | 5,2 | 7,4 | 44,29 | 48 | 46,14 | 473 | d1 | 1 240 | 0,6 | 1 514 | 0,5 | -13,23 | -28,93 | false | false | false | false | https://data.bls.gov/cew/data/files/2025/csv/2025_annual_by_area.zip | b2c73f442a293c8a |
| 2025 | 2 025 | United States | USA | AL | Alabama | 01009 | Blount County, Alabama | 9 229 | 1 006 | 441 533 456 | 920 | 47 842 | 1,5 | 4,7 | 5,2 | 6,3 | 42 | 47,14 | 44,57 | 727 | d1 | 1 240 | 0,6 | 1 514 | 0,5 | -25,81 | -39,23 | false | false | false | false | https://data.bls.gov/cew/data/files/2025/csv/2025_annual_by_area.zip | b0b024ca5e14b07c |
| 2025 | 2 025 | United States | USA | AL | Alabama | 01011 | Bullock County, Alabama | 2 613 | 214 | 132 128 216 | 973 | 50 571 | -6,3 | -0,2 | 2,9 | -6,5 | 28 | 24,86 | 26,43 | 3 222 | d4 | 1 240 | 0,6 | 1 514 | 0,5 | -21,53 | -35,73 | false | false | true | false | https://data.bls.gov/cew/data/files/2025/csv/2025_annual_by_area.zip | 43cef40b4907b3cb |
| 2025 | 2 025 | United States | USA | AL | Alabama | 01013 | Butler County, Alabama | 6 796 | 527 | 324 847 256 | 919 | 47 800 | 0,1 | 4,1 | 0,2 | 4,2 | 40,29 | 43,14 | 41,72 | 1 540 | d2 | 1 240 | 0,6 | 1 514 | 0,5 | -25,89 | -39,3 | false | false | false | false | https://data.bls.gov/cew/data/files/2025/csv/2025_annual_by_area.zip | c15120251f764370 |
| 2025 | 2 025 | United States | USA | AL | Alabama | 01015 | Calhoun County, Alabama | 43 473 | 2 912 | 2 279 218 751 | 1 008 | 52 428 | -0,7 | 2 | 3 | 1,4 | 34,29 | 40,86 | 37,58 | 2 676 | d4 | 1 240 | 0,6 | 1 514 | 0,5 | -18,71 | -33,42 | false | false | false | false | https://data.bls.gov/cew/data/files/2025/csv/2025_annual_by_area.zip | d32699d529e094d1 |
| 2025 | 2 025 | United States | USA | AL | Alabama | 01017 | Chambers County, Alabama | 9 358 | 823 | 490 482 028 | 1 008 | 52 414 | 3 | 0,5 | 5,6 | 3,5 | 30 | 51,43 | 40,72 | 1 906 | d3 | 1 240 | 0,6 | 1 514 | 0,5 | -18,71 | -33,42 | false | false | false | false | https://data.bls.gov/cew/data/files/2025/csv/2025_annual_by_area.zip | d4dce0b03d483e2a |
| 2025 | 2 025 | United States | USA | AL | Alabama | 01019 | Cherokee County, Alabama | 5 446 | 525 | 254 267 491 | 898 | 46 692 | 1,8 | 4,5 | 5,4 | 6,4 | 41,43 | 48 | 44,72 | 700 | d1 | 1 240 | 0,6 | 1 514 | 0,5 | -27,58 | -40,69 | false | false | false | false | https://data.bls.gov/cew/data/files/2025/csv/2025_annual_by_area.zip | f732c63329a76d10 |
- Actuelle
20260927T082103Z-d14ab4e82c91 · sha256 d14ab4e82c91…
3 275 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/qcew_county_wage_intel/us_county_wage_employment_intel_annual" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/qcew_county_wage_intel/us_county_wage_employment_intel_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/qcew_county_wage_intel/us_county_wage_employment_intel_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.
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Épinglé à l’instantané 20260927T082103Z-d14ab4e82c91 et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
APA
BLS QCEW — US county wage & employment intelligence. (2026). US county wage & employment intelligence (annual) [Data set, snapshot 20260927T082103Z-d14ab4e82c91, sha256 d14ab4e82c91]. Datazimuts. Retrieved 2026-09-27, from https://datazimuts.com/fr/datasets/qcew_county_wage_intel/us_county_wage_employment_intel_annual?snapshot=20260927T082103Z-d14ab4e82c91
BibTeX
@misc{dz_qcew_county_wage_intel_us_county_wage_em_d14ab4e8,
title = {{US county wage \& employment intelligence (annual)}},
author = {{BLS QCEW — US county wage \& employment intelligence}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/fr/datasets/qcew_county_wage_intel/us_county_wage_employment_intel_annual?snapshot=20260927T082103Z-d14ab4e82c91}},
note = {Snapshot 20260927T082103Z-d14ab4e82c91, sha256 d14ab4e82c91c2851be14203bf8bf8ab24a2dcdd5dd752a03cc7463c317897d3; accessed 2026-09-27}
}Intégrer un tableau ou un graphique
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HTML
<iframe src="https://datazimuts.com/embed/chart?dataset=qcew_county_wage_intel%2Fus_county_wage_employment_intel_annual&lang=fr&theme=auto&snapshot=20260927T082103Z-d14ab4e82c91&x=year&y=year&agg=avg" title="US county wage & employment intelligence (annual)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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