# All Employees: Leisure and Hospitality — San Juan-Bayamon-Caguas, PR (NSA)

All Employees: Leisure and Hospitality — San Juan-Bayamon-Caguas, PR (NSA) was up 3.1% year on year in September 2026, compared with 3.4% in August 2026.
The level stood at 73.50 thousands.
Over the past ten years it has ranged from −38.9% (Apr 2020) to 47.1% (Apr 2021), averaging 2.7%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-41980.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-san-juan-bayamon-caguas-pr-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 73.50 thousands | 3.1 |
| August 2026 | 73.50 thousands | 3.4 |
| July 2026 | 74.20 thousands | 5.1 |
| June 2026 | 74.40 thousands | 3.9 |
| May 2026 | 74.50 thousands | 5.4 |
| April 2026 | 74.60 thousands | 5.7 |
| March 2026 | 74.10 thousands | 4.7 |
| February 2026 | 74.10 thousands | 6.5 |
| January 2026 | 72.30 thousands | 4.0 |
| December 2025 | 73.00 thousands | 2.2 |
| November 2025 | 72.20 thousands | 4.0 |
| October 2025 | 72.20 thousands | 4.0 |
| September 2025 | 71.30 thousands | 1.4 |
| August 2025 | 71.10 thousands | 2.6 |
| July 2025 | 70.60 thousands | 2.3 |
| June 2025 | 71.60 thousands | 2.6 |
| May 2025 | 70.70 thousands | 3.1 |
| April 2025 | 70.60 thousands | 3.2 |
| March 2025 | 70.80 thousands | 2.6 |
| February 2025 | 69.60 thousands | 2.8 |
| January 2025 | 69.50 thousands | 3.4 |
| December 2024 | 71.40 thousands | 2.0 |
| November 2024 | 69.40 thousands | 2.5 |
| October 2024 | 69.40 thousands | 3.1 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-41980.PAYEMS.M.NSA.IND-70000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-41980.PAYEMS.M.NSA.IND-70000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```