# All Employees: Federal Government — Tampa, FL Metropolitan Division (NSA)

All Employees: Federal Government — Tampa, FL Metropolitan Division (NSA) was down 4.3% year on year in September 2026, compared with −4.3% in August 2026.
The level stood at 17.60 thousands.
Over the past ten years it has ranged from −7.4% (Mar 2026) to 11.3% (Aug 2020), averaging 1.1%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-45294.PAYEMS.M.NSA.IND-90910000`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-federal-government-tampa-fl-metropolitan-division-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 17.60 thousands | −4.3 |
| August 2026 | 17.60 thousands | −4.3 |
| July 2026 | 17.60 thousands | −4.9 |
| June 2026 | 17.60 thousands | −4.9 |
| May 2026 | 17.60 thousands | −5.4 |
| April 2026 | 17.70 thousands | −5.9 |
| March 2026 | 17.60 thousands | −7.4 |
| February 2026 | 17.70 thousands | −7.3 |
| January 2026 | 17.70 thousands | −7.3 |
| December 2025 | 17.90 thousands | −6.8 |
| November 2025 | 17.90 thousands | −6.3 |
| October 2025 | 17.90 thousands | −6.3 |
| September 2025 | 18.40 thousands | −3.2 |
| August 2025 | 18.40 thousands | −2.6 |
| July 2025 | 18.50 thousands | −2.1 |
| June 2025 | 18.50 thousands | −1.6 |
| May 2025 | 18.60 thousands | −1.6 |
| April 2025 | 18.80 thousands | −0.5 |
| March 2025 | 19.00 thousands | 1.1 |
| February 2025 | 19.10 thousands | 1.6 |
| January 2025 | 19.10 thousands | 2.1 |
| December 2024 | 19.20 thousands | 1.6 |
| November 2024 | 19.10 thousands | 1.6 |
| October 2024 | 19.10 thousands | 2.7 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-45294.PAYEMS.M.NSA.IND-90910000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-45294.PAYEMS.M.NSA.IND-90910000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```