Check the setup
- Python 3.10 or newer
- A notebook environment such as Jupyter or Google Colab
- An internet connection
Comparable labour-force, employment, and wage indicators for building country labour-market dashboards from ILO SDMX.
From source to product signal
ILOSTAT SDMX returns labour indicators such as unemployment rate by sex and age. Start with one country and one indicator. National definitions differ, modelled estimates are not survey microdata, and coverage gaps are common.
Install the packages, then run the notebook cell.
python -m pip install pandas requests
import pandas as pd
import requests
response = requests.get(
"https://sdmx.ilo.org/rest/data/ILO,DF_UNE_2EAP_SEX_AGE_RT/A.USA.SEX_T.AGE_YTHADULT_YGE15",
headers={"Accept": "application/vnd.sdmx.data+json;version=1.0.0"},
timeout=30,
)
response.raise_for_status()
observations = response.json()["data"]["dataSets"][0]["observations"]
unemployment = pd.DataFrame(
[{"position": key, "value": value[0]} for key, value in observations.items()]
)
unemployment["retrieved_at_utc"] = pd.Timestamp.now(tz="UTC")
print(unemployment.tail())Test a useful signal
Test whether one ILOSTAT series can power a bounded labour-market chart.
International Labour Organization is an intergovernmental source. Last verified 2026-08-18. Temporal coverage: country-specific labour series published by ILOSTAT.