# Unemployment: Guayama, PR Metropolitan Statistical Area (U)

Unemployment: Guayama, PR Metropolitan Statistical Area (U) was up 18.4% year on year in September 2026, compared with 27.6% in August 2026.
The level stood at 2,059.0 thousands.
Over the past ten years it has ranged from −35.6% (Aug 2018) to 65.9% (Jul 2021), averaging −2.3%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-25020.UNEMPLVL.M.NSA`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (439 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/unemployment-guayama-pr-metropolitan-statistical-area-u

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 2,059.0 thousands | 18.4 |
| August 2026 | 2,306.0 thousands | 27.6 |
| July 2026 | 2,275.0 thousands | 38.0 |
| June 2026 | 2,142.0 thousands | 27.0 |
| May 2026 | 1,780.0 thousands | 20.0 |
| April 2026 | 1,676.0 thousands | 6.6 |
| March 2026 | 1,678.0 thousands | 3.4 |
| February 2026 | 1,709.0 thousands | −1.1 |
| January 2026 | 1,790.0 thousands | 3.3 |
| December 2025 | 1,825.0 thousands | 4.1 |
| November 2025 | 1,726.0 thousands | 1.5 |
| October 2025 | 1,671.0 thousands | −5.1 |
| September 2025 | 1,739.0 thousands | −1.2 |
| August 2025 | 1,807.0 thousands | −10.5 |
| July 2025 | 1,648.0 thousands | −11.1 |
| June 2025 | 1,686.0 thousands | −8.7 |
| May 2025 | 1,483.0 thousands | −20.1 |
| April 2025 | 1,572.0 thousands | −13.7 |
| March 2025 | 1,623.0 thousands | −13.5 |
| February 2025 | 1,728.0 thousands | −10.5 |
| January 2025 | 1,733.0 thousands | −5.6 |
| December 2024 | 1,753.0 thousands | −1.4 |
| November 2024 | 1,700.0 thousands | −1.3 |
| October 2024 | 1,760.0 thousands | 8.2 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-25020.UNEMPLVL.M.NSA"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-25020.UNEMPLVL.M.NSA",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```