# All Employees: Total Nonfarm — North Port-Bradenton-Sarasota, FL (NSA)

All Employees: Total Nonfarm — North Port-Bradenton-Sarasota, FL (NSA) was up 1.2% year on year in September 2026, compared with 0.9% in August 2026.
The level stood at 356.9 thousands.
Over the past ten years it has ranged from −14.3% (Apr 2020) to 16.1% (Apr 2021), averaging 2.3%.
The next update is expected on 23 November 2026.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-35840.PAYEMS.M.NSA`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-total-nonfarm-north-port-bradenton-sarasota-fl-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 356.9 thousands | 1.2 |
| August 2026 | 357.3 thousands | 0.9 |
| July 2026 | 357.2 thousands | 0.9 |
| June 2026 | 359.4 thousands | 1.2 |
| May 2026 | 360.5 thousands | 0.6 |
| April 2026 | 362.7 thousands | 0.7 |
| March 2026 | 360.3 thousands | 0.2 |
| February 2026 | 359.5 thousands | 0.08 |
| January 2026 | 357.7 thousands | 0.4 |
| December 2025 | 361.0 thousands | 1.7 |
| November 2025 | 359.0 thousands | 1.6 |
| October 2025 | 355.6 thousands | 3.9 |
| September 2025 | 352.6 thousands | 0.9 |
| August 2025 | 354.1 thousands | 1.5 |
| July 2025 | 353.9 thousands | 1.5 |
| June 2025 | 355.0 thousands | 1.1 |
| May 2025 | 358.2 thousands | 1.3 |
| April 2025 | 360.1 thousands | 1.7 |
| March 2025 | 359.6 thousands | 1.7 |
| February 2025 | 359.2 thousands | 2.0 |
| January 2025 | 356.1 thousands | 1.9 |
| December 2024 | 354.9 thousands | 1.2 |
| November 2024 | 353.5 thousands | 1.2 |
| October 2024 | 342.2 thousands | −1.1 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-35840.PAYEMS.M.NSA"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-35840.PAYEMS.M.NSA",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```