US industry wage-pressure intelligence (monthly)
Monthly average hourly earnings (BLS Current Employment Statistics, seasonally adjusted, dollars per hour) for total private plus 10 supersectors - mining & logging, construction, manufacturing, trade/transportation/utilities, information, financial activities, professional & business services, education & health services, leisure & hospitality, other services - enriched into a join-ready wage-pressure panel: MoM and YoY growth, YoY acceleration in percentage points, percentile-of-own-trailing-36-month-history growth and level scores, a documented 0-100 wage-pressure index (0.6 growth / 0.4 level) with booming/strong/steady/soft/stalled bands, surge/cooling/record-high/preliminary flags, and the total-private benchmark broadcast on every row. Source: U.S. Bureau of Labor Statistics via the keyless Public Data API v2; federal public-domain data, safe for commercial use with attribution. Latest month is preliminary - BLS revises CES. Who joins this: a sales team (staffing, HR-tech, benefits, B2B services) joins (month, industry_code) to account prioritization - industries with accelerating wage growth are hiring and spending on talent; a B2B subscription business joins it to ICP expansion timing; an online shop joins it to labor-cost pass-through expectations by sector.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Lignes
- 880
- Colonnes
- 20
- Cadence de la source
- Mensuelle
- Dernière actualisation
- 30 sept. 2026
- Thème
- economics
| Colonne | Type | Description |
|---|---|---|
| month | string | ISO date of the month's first day. (unit: date) |
| industry_code | string | Machine code for the industry (total_private + 10 supersectors). |
| industry_name | string | Industry name. |
| country_code | string | ISO alpha-3 country code (USA). |
| country_name | string | Country name. |
| ahe_usd | float | Average hourly earnings, seasonally adjusted, dollars per hour (BLS CES). (unit: USD per hour) |
| ahe_mom_pct | float | Month-over-month growth of ahe_usd, percent. (unit: percent) |
| ahe_yoy_pct | float | Year-over-year growth of ahe_usd, percent. (unit: percent) |
| ahe_yoy_accel_pp | float | Change in ahe_yoy_pct vs the year-ago month, percentage points. (unit: percentage points) |
| growth_score | float | Percentile rank of ahe_yoy_pct in the industry's own trailing-36-month history, 0-100. |
| level_score | float | Percentile rank of ahe_usd in the industry's own trailing-36-month history, 0-100. |
| wage_pressure_index | float | Composite 0-100: 0.6 * growth_score + 0.4 * level_score. |
| intensity_band | string | booming (>=90) / strong (>=75) / steady (>=50) / soft (>=25) / stalled from the index; insufficient-history when history < 12 months. |
| surge | boolean | True when wage_pressure_index >= 70 and YoY acceleration is positive. |
| cooling | boolean | True when wage_pressure_index <= 30. |
| record_high_12m | boolean | True when ahe_usd is the trailing-12-month maximum. |
| preliminary | boolean | True for the latest month in the panel (BLS revises CES). |
| private_ahe_usd | float | Total-private average hourly earnings benchmark, dollars per hour, broadcast on every row. (unit: USD per hour) |
| private_ahe_yoy_pct | float | Year-over-year growth of the total-private benchmark, percent. (unit: percent) |
| row_hash | string | Deterministic sha256 row identity (first 16 hex chars). |
10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.
| month | industry_code | industry_name | country_code | country_name | ahe_usd | ahe_mom_pct | ahe_yoy_pct | ahe_yoy_accel_pp | growth_score | level_score | wage_pressure_index | intensity_band | surge | cooling | record_high_12m | preliminary | private_ahe_usd | private_ahe_yoy_pct | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-01-01 | construction | Construction | USA | United States | 31,22 | — | — | — | — | — | — | insufficient-history | false | false | true | false | 28,43 | — | cf06ce0fb92778e3 |
| 2020-01-01 | edu_health | Education and health services | USA | United States | 27,83 | — | — | — | — | — | — | insufficient-history | false | false | true | false | 28,43 | — | 090dab3e483c12af |
| 2020-01-01 | financial_activities | Financial activities | USA | United States | 36,69 | — | — | — | — | — | — | insufficient-history | false | false | true | false | 28,43 | — | 05f7ae6d94d9000a |
| 2020-01-01 | information | Information | USA | United States | 42,86 | — | — | — | — | — | — | insufficient-history | false | false | true | false | 28,43 | — | 79536acb2b0583fd |
| 2020-01-01 | leisure_hospitality | Leisure and hospitality | USA | United States | 16,84 | — | — | — | — | — | — | insufficient-history | false | false | true | false | 28,43 | — | 3353ebec5336d6d9 |
| 2020-01-01 | manufacturing | Manufacturing | USA | United States | 28,2 | — | — | — | — | — | — | insufficient-history | false | false | true | false | 28,43 | — | a5f80ccf4c34cf11 |
| 2020-01-01 | mining_logging | Mining and logging | USA | United States | 34,41 | — | — | — | — | — | — | insufficient-history | false | false | true | false | 28,43 | — | 477b4989dfca95c1 |
| 2020-01-01 | other_services | Other services | USA | United States | 25,6 | — | — | — | — | — | — | insufficient-history | false | false | true | false | 28,43 | — | c81b292d532a92bb |
| 2020-01-01 | prof_business | Professional and business services | USA | United States | 34,3 | — | — | — | — | — | — | insufficient-history | false | false | true | false | 28,43 | — | 08391765cd2a6403 |
| 2020-01-01 | total_private | Total private | USA | United States | 28,43 | — | — | — | — | — | — | insufficient-history | false | false | true | false | 28,43 | — | 5fc76067122ee0fc |
Profilé le 1 oct. 2026 à partir de l’instantané 20260930T171616Z-c16d2a3b910b
Mesuré- Complétude
- 93,4 %
- Lignes
- 880
- Colonnes
- 20
- Colonnes incomplètes
- 7
| Colonne | Manquant | Distinctes | Plage | Distribution |
|---|---|---|---|---|
| monthvarchar | 0 % | 73 | — |
|
| industry_codevarchar | 0 % | 11 | — |
|
| industry_namevarchar | 0 % | 12 | — |
|
| country_codevarchar | 0 % | 1 | — |
|
| country_namevarchar | 0 % | 1 | — |
|
| ahe_usddouble | 0 % | 757 | 16,84 → 55,7médiane 34,52 | 18 hors du 1er–99e centile |
| ahe_mom_pctdouble | 1,3 % | 211 | -3,27 → 7,76médiane 0,35 | 18 hors du 1er–99e centile |
| ahe_yoy_pctdouble | 15 % | 320 | -1,33 → 13,83médiane 4,27 | 16 hors du 1er–99e centile |
| ahe_yoy_accel_ppdouble | 30 % | 384 | -7,21 → 12,57médiane -0,31 | 14 hors du 1er–99e centile |
| growth_scoredouble | 28,8 % | 215 | 1,4 → 98,6médiane 38 | 7 hors du 1er–99e centile |
| level_scoredouble | 13,8 % | 58 | 34,6 → 98,6médiane 98,6 | 8 hors du 1er–99e centile |
| wage_pressure_indexdouble | 28,8 % | 262 | 35,8 → 98,6médiane 61,9 | 10 hors du 1er–99e centile |
| intensity_bandvarchar | 0 % | 5 | — |
|
| surgeboolean | 0 % | 2 | — |
|
| coolingboolean | 0 % | 1 | — |
|
| record_high_12mboolean | 0 % | 2 | — |
|
| preliminaryboolean | 0 % | 2 | — |
|
| private_ahe_usddouble | 0 % | 74 | 28,43 → 37,75médiane 33,47 | |
| private_ahe_yoy_pctdouble | 15 % | 73 | 0,6 → 5,89médiane 4,17 | |
| row_hashvarchar | 0 % | 1 057 | — |
|
- Actuelle
20260930T171616Z-c16d2a3b910b · sha256 c16d2a3b910b…
880 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/us_industry_wage_pressure_intel/us_industry_wage_pressure_monthly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/us_industry_wage_pressure_intel/us_industry_wage_pressure_monthly").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_industry_wage_pressure_intel/us_industry_wage_pressure_monthly
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 20260930T171616Z-c16d2a3b910b et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
. (2026). US industry wage-pressure intelligence (monthly) [Data set, snapshot 20260930T171616Z-c16d2a3b910b, sha256 c16d2a3b910b]. Datazimuts. Retrieved 2026-10-01, from https://datazimuts.com/fr/datasets/us_industry_wage_pressure_intel/us_industry_wage_pressure_monthly?snapshot=20260930T171616Z-c16d2a3b910b
@misc{dz_us_industry_wage_pressure_intel_us_indus_c16d2a3b,
title = {{US industry wage-pressure intelligence (monthly)}},
author = {{}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/fr/datasets/us_industry_wage_pressure_intel/us_industry_wage_pressure_monthly?snapshot=20260930T171616Z-c16d2a3b910b}},
note = {Snapshot 20260930T171616Z-c16d2a3b910b, sha256 c16d2a3b910b0ff581c3c9f86d206c3b895730708cc01e18d9cc8f5cd8b96aa7; accessed 2026-10-01}
}Intégrer un tableau ou un graphique
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<iframe src="https://datazimuts.com/embed/chart?dataset=us_industry_wage_pressure_intel%2Fus_industry_wage_pressure_monthly&lang=fr&theme=auto&snapshot=20260930T171616Z-c16d2a3b910b&x=month&y=ahe_usd&agg=avg" title="US industry wage-pressure intelligence (monthly)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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