# United States All employees, thousands, legal services, seasonally adjusted

United States All employees, thousands, legal services, seasonally adjusted was up 1.9% year on year in October 2026, compared with 1.8% in September 2026.
The level stood at 1,251.2 thousands.
Over the past ten years it has ranged from −4.4% (Apr 2020) to 4.8% (Apr 2021), averaging 1.0%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US.EMP.M.SA.IND-60541100`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-10-01 (442 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-thousands-legal-services-seasonally-adjusted

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| October 2026 | 1,251.2 thousands | 1.9 |
| September 2026 | 1,248.8 thousands | 1.8 |
| August 2026 | 1,248.0 thousands | 1.9 |
| July 2026 | 1,246.1 thousands | 1.8 |
| June 2026 | 1,244.4 thousands | 1.9 |
| May 2026 | 1,238.3 thousands | 1.6 |
| April 2026 | 1,237.2 thousands | 1.7 |
| March 2026 | 1,234.1 thousands | 1.5 |
| February 2026 | 1,234.9 thousands | 1.9 |
| January 2026 | 1,233.9 thousands | 2.0 |
| December 2025 | 1,231.2 thousands | 2.0 |
| November 2025 | 1,229.9 thousands | 2.2 |
| October 2025 | 1,228.4 thousands | 2.2 |
| September 2025 | 1,226.2 thousands | 2.2 |
| August 2025 | 1,224.7 thousands | 2.2 |
| July 2025 | 1,223.5 thousands | 2.3 |
| June 2025 | 1,220.9 thousands | 2.1 |
| May 2025 | 1,218.2 thousands | 1.6 |
| April 2025 | 1,216.3 thousands | 1.6 |
| March 2025 | 1,215.7 thousands | 1.8 |
| February 2025 | 1,211.5 thousands | 0.9 |
| January 2025 | 1,209.8 thousands | 1.4 |
| December 2024 | 1,207.3 thousands | 0.6 |
| November 2024 | 1,204.0 thousands | 0.9 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US.EMP.M.SA.IND-60541100"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US.EMP.M.SA.IND-60541100",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```