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BLS nonfarm payroll employment, hours and earnings

Monthly U.S. employment statistics from the BLS Current Employment Statistics (CES) survey: total nonfarm employment and total private employment (thousands of jobs), average weekly hours, and average hourly earnings of all employees on private nonfarm payrolls (dollars). Seasonally adjusted.

Source: U.S. Bureau of Labor Statistics944 lignesMis à jour: 22/09/2026
employmentlaborwagesusjobs

Qualité

100

Attribution

U.S. Bureau of Labor Statistics

Schéma

ColonneTypeDescription
datetimestampMonth of observation, mapped from the BLS API 'year' and 'period' fields (for example '2026' + 'M08' becomes 2026-08-01). Only monthly periods are kept.
series_idstringBLS series identifier, e.g. 'CES0000000001' or 'CUSR0000SA0'. Encodes the survey, area, item, and seasonal adjustment; formats are documented at bls.gov/help/hlpforma.htm.
series_labelstringOfficial BLS series title from the Bureau's series catalog (data.bls.gov/timeseries), e.g. 'All employees, thousands, total nonfarm, seasonally adjusted'.
valuefloatObserved value from the BLS API 'value' field. Units follow the series definition: employment and unemployment levels are in thousands of persons/jobs, average hourly earnings in dollars, weekly hours in hours, rates in percent, and CPI/PPI series in index points. Missing observations are null.

Exemple de lignes

dateseries_idseries_labelvalue
2007-01-01T00:00:00CES0000000001All employees, thousands, total nonfarm, seasonally adjusted137472
2007-02-01T00:00:00CES0000000001All employees, thousands, total nonfarm, seasonally adjusted137560
2007-03-01T00:00:00CES0000000001All employees, thousands, total nonfarm, seasonally adjusted137784
2007-04-01T00:00:00CES0000000001All employees, thousands, total nonfarm, seasonally adjusted137847
2007-05-01T00:00:00CES0000000001All employees, thousands, total nonfarm, seasonally adjusted137992

Télécharger un échantillon

Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).

Utiliser avec un LLM

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/bls/bls_nonfarm_payroll" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/bls/bls_nonfarm_payroll").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/bls/bls_nonfarm_payroll

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.

BLS nonfarm payroll employment, hours and earnings