# United States All employees, thousands, credit unions, not seasonally adjusted

United States All employees, thousands, credit unions, not seasonally adjusted was up 1.6% year on year in September 2026, compared with 2.2% in August 2026.
The level stood at 325.6 thousands.
That is the lowest reading since April 2025.
Over the past ten years it has ranged from −1.6% (Mar 2021) to 5.8% (Dec 2022), averaging 2.4%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US.EMP.M.NSA.IND-55522130`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-thousands-credit-unions-not-seasonally-adjusted

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 325.6 thousands | 1.6 |
| August 2026 | 327.2 thousands | 2.2 |
| July 2026 | 327.0 thousands | 2.2 |
| June 2026 | 327.0 thousands | 2.8 |
| May 2026 | 325.3 thousands | 3.0 |
| April 2026 | 325.0 thousands | 3.7 |
| March 2026 | 324.1 thousands | 3.6 |
| February 2026 | 323.9 thousands | 3.5 |
| January 2026 | 324.7 thousands | 4.2 |
| December 2025 | 325.4 thousands | 4.4 |
| November 2025 | 323.4 thousands | 3.9 |
| October 2025 | 321.5 thousands | 3.5 |
| September 2025 | 320.6 thousands | 3.6 |
| August 2025 | 320.1 thousands | 3.6 |
| July 2025 | 319.9 thousands | 3.5 |
| June 2025 | 318.1 thousands | 2.7 |
| May 2025 | 315.8 thousands | 2.4 |
| April 2025 | 313.3 thousands | 1.4 |
| March 2025 | 312.7 thousands | 1.2 |
| February 2025 | 312.9 thousands | 1.4 |
| January 2025 | 311.5 thousands | 1.0 |
| December 2024 | 311.6 thousands | 1.1 |
| November 2024 | 311.3 thousands | 1.3 |
| October 2024 | 310.7 thousands | 0.9 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US.EMP.M.NSA.IND-55522130"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US.EMP.M.NSA.IND-55522130",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```