# All Employees: Total Nonfarm — Houston-Pasadena-The Woodlands, TX (NSA)

All Employees: Total Nonfarm — Houston-Pasadena-The Woodlands, TX (NSA) was up 1.0% year on year in September 2026, compared with 1.3% in August 2026.
The level stood at 3,489.4 thousands.
Over the past ten years it has ranged from −9.9% (Apr 2020) to 6.9% (Apr 2021), averaging 1.6%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-26420.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-houston-pasadena-the-woodlands-tx-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 3,489.4 thousands | 1.0 |
| August 2026 | 3,496.7 thousands | 1.3 |
| July 2026 | 3,494.4 thousands | 1.4 |
| June 2026 | 3,522.7 thousands | 1.2 |
| May 2026 | 3,507.1 thousands | 0.6 |
| April 2026 | 3,490.9 thousands | 0.2 |
| March 2026 | 3,485.0 thousands | 0.5 |
| February 2026 | 3,471.0 thousands | 0.2 |
| January 2026 | 3,457.9 thousands | 0.6 |
| December 2025 | 3,502.9 thousands | 0.5 |
| November 2025 | 3,495.2 thousands | 0.2 |
| October 2025 | 3,477.0 thousands | 0.2 |
| September 2025 | 3,455.8 thousands | 0.4 |
| August 2025 | 3,450.6 thousands | 0.6 |
| July 2025 | 3,447.4 thousands | 1.7 |
| June 2025 | 3,481.8 thousands | 1.0 |
| May 2025 | 3,486.4 thousands | 1.3 |
| April 2025 | 3,482.3 thousands | 1.5 |
| March 2025 | 3,468.5 thousands | 1.3 |
| February 2025 | 3,463.3 thousands | 1.6 |
| January 2025 | 3,437.6 thousands | 1.7 |
| December 2024 | 3,485.4 thousands | 1.8 |
| November 2024 | 3,487.3 thousands | 1.8 |
| October 2024 | 3,469.9 thousands | 1.8 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-26420.PAYEMS.M.NSA"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-26420.PAYEMS.M.NSA",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```