Nonfarm Payrolls
Get Total Nonfarm Payroll Employment for the United States from the Bureau of Labor Statistics.
Nonfarm Payrolls is the headline monthly employment report and one of the most closely watched real-activity indicators in macroeconomics: it counts the number of paid US workers excluding farm employees, general government employees, private household employees and nonprofit organization employees. Sharp month-over-month changes are a core input to business-cycle dating (used directly by the NBER’s Business Cycle Dating Committee) and, through Okun’s Law, are closely tied to changes in the Unemployment Rate (see get_unemployment_rate).
The series is the monthly level of employment in thousands of persons, seasonally adjusted, so 156857 means 156.857 million jobs – not the monthly change that the headline “jobs added” number refers to. Use growth=True for that change.
Without a FRED API key the data comes from the Bureau of Labor Statistics’ keyless API, which gives the same figures but only for about the last three years. The full history, from 1939, comes from FRED when a FRED API key is set (see the fred_api_key parameter of the Economics class).
See definition: https://fred.stlouisfed.org/series/PAYEMS
Also known as: NFP, nonfarm employment, the “jobs report”.
Nonfarm Payrolls in Python or via the MCP
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_nonfarm_payrolls as shown below.
from financetoolkit import Economics
economics = Economics(
start_date='2020-01-01',
fred_api_key='FRED_API_KEY',
end_date="2025-12-31",
)
economics.get_nonfarm_payrolls()
Or, after setting up the Finance Toolkit MCP, ask:
How did total US nonfarm payroll employment develop from August to December 2025?
Which returns:
| Date | United States |
|---|---|
| 2025-08-01 | 158472 |
| 2025-09-01 | 158548 |
| 2025-10-01 | 158408 |
| 2025-11-01 | 158449 |
| 2025-12-01 | 158432 |
Parameters
get_nonfarm_payrolls accepts the following parameters.
| Parameter | Type | Description | Example |
|---|---|---|---|
rolling | int | The rolling window size to use for smoothing the data (simple moving average). Defaults to None. | 4 |
trailing | int | The trailing window size to use for summing the data over trailing periods. Defaults to None. | 4 |
growth | bool | Whether to return the growth data or the actual data. Defaults to False. | True |
lag | int | The number of periods to lag the data by. Defaults to 1. | 4 |
standardize | bool | Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False. | True |
rounding | int | None | The number of decimals to round the results to. Defaults to None. | 2 |