# All Employees: Leisure and Hospitality — Dallas-Fort Worth-Arlington, TX (NSA)

All Employees: Leisure and Hospitality — Dallas-Fort Worth-Arlington, TX (NSA) was up 1.2% year on year in September 2026, compared with 1.9% in August 2026.
The level stood at 433.7 thousands.
Over the past ten years it has ranged from −40.1% (Apr 2020) to 49.9% (Apr 2021), averaging 2.5%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-19100.PAYEMS.M.NSA.IND-70000000`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-leisure-and-hospitality-dallas-fort-worth-arlington-tx-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 433.7 thousands | 1.2 |
| August 2026 | 442.0 thousands | 1.9 |
| July 2026 | 447.9 thousands | 2.6 |
| June 2026 | 450.9 thousands | 2.3 |
| May 2026 | 443.7 thousands | 0.6 |
| April 2026 | 435.5 thousands | 0.2 |
| March 2026 | 431.4 thousands | 1.0 |
| February 2026 | 425.2 thousands | 1.2 |
| January 2026 | 424.0 thousands | 1.5 |
| December 2025 | 427.1 thousands | −0.4 |
| November 2025 | 428.6 thousands | 0.2 |
| October 2025 | 431.2 thousands | 0.3 |
| September 2025 | 428.5 thousands | 0.1 |
| August 2025 | 433.8 thousands | −0.02 |
| July 2025 | 436.4 thousands | 0.3 |
| June 2025 | 440.8 thousands | 0.2 |
| May 2025 | 441.0 thousands | 1.4 |
| April 2025 | 434.5 thousands | 1.4 |
| March 2025 | 427.1 thousands | 1.1 |
| February 2025 | 420.2 thousands | 1.1 |
| January 2025 | 417.8 thousands | 1.2 |
| December 2024 | 428.7 thousands | 1.7 |
| November 2024 | 427.9 thousands | 1.7 |
| October 2024 | 429.8 thousands | 1.8 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-19100.PAYEMS.M.NSA.IND-70000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-19100.PAYEMS.M.NSA.IND-70000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```