# All Employees: Total Private — San Antonio-New Braunfels, TX (NSA)

All Employees: Total Private — San Antonio-New Braunfels, TX (NSA) was up 0.9% year on year in September 2026, compared with 1.0% in August 2026.
The level stood at 1,001.9 thousands.
Over the past ten years it has ranged from −13.4% (Apr 2020) to 12.4% (Apr 2021), averaging 1.9%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-41700.PAYEMS.M.NSA.IND-05000000`
- 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-private-san-antonio-new-braunfels-tx-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 1,001.9 thousands | 0.9 |
| August 2026 | 1,008.4 thousands | 1.0 |
| July 2026 | 1,007.2 thousands | 1.1 |
| June 2026 | 1,011.6 thousands | 1.3 |
| May 2026 | 1,007.1 thousands | 0.6 |
| April 2026 | 1,001.6 thousands | 0.3 |
| March 2026 | 996.7 thousands | 0.7 |
| February 2026 | 994.2 thousands | 0.3 |
| January 2026 | 995.1 thousands | 0.9 |
| December 2025 | 1,003.6 thousands | 0.05 |
| November 2025 | 999.7 thousands | −0.3 |
| October 2025 | 995.6 thousands | −0.2 |
| September 2025 | 993.1 thousands | −0.2 |
| August 2025 | 998.0 thousands | −0.1 |
| July 2025 | 996.1 thousands | 0.0 |
| June 2025 | 998.2 thousands | −0.04 |
| May 2025 | 1,000.7 thousands | 0.8 |
| April 2025 | 999.0 thousands | 1.1 |
| March 2025 | 989.9 thousands | 0.9 |
| February 2025 | 991.0 thousands | 1.1 |
| January 2025 | 986.6 thousands | 1.1 |
| December 2024 | 1,003.1 thousands | 1.3 |
| November 2024 | 1,002.5 thousands | 1.1 |
| October 2024 | 997.9 thousands | 1.1 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-41700.PAYEMS.M.NSA.IND-05000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-41700.PAYEMS.M.NSA.IND-05000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```