NEET rate by sex, 15-29 (annual, Europe)
Annual share of 15-29 year olds neither in employment nor in education or training (the NEET rate), broken down by sex, for EU member states, EFTA countries, EU candidate countries and EU/euro-area aggregates. Eurostat dataset edat_lfse_20 ('Young persons neither in employment nor in education and training by labour status (NEET rates)'), filtered to sex=M ('Males') / F ('Females'), age=Y15-29 ('From 15 to 29 years'), training=NO_FE_NO_NFE ('Neither formal nor non-formal education or training'), wstatus=NEMP ('Not employed persons') and unit=PC ('Percentage'). It extends the headline dataset 'neet-rate-annual' (the sex=T slice of the same table). Each row is one (year, country, sex). Method: EU Labour Force Survey microdata compiled by Eurostat; a young person counts as NEET only when both conditions hold (not employed AND not in education or training). Units: percent of the 15-29 population in the sex group. Caveats: female rates run above male rates in the large majority of published country-years (e.g. EU27_2020 2025: 12.1% F vs 10.0% M; DEU 2025: 10.6% F vs 8.5% M); national LFS redesigns cause breaks in some series; the EU27_2020 and EA aggregates are included as published; the UK and other non-EU/EFTA/non-candidate countries are dropped by the connector's commercial-use geo rule. Coverage: ~40 geographic units after the geo rule, 2000 to the present, annual. Provenance: Eurostat keyless JSON-stat API, free reuse with attribution (Commission Decision 2011/833/EU) - please cite Eurostat. Primary key: (year, country_code, sex). Join keys: country_code (ISO 3166-1 alpha-3), year. Cadence: refreshed yearly; Eurostat publishes the series each spring. Sample use: filter country_code='DEU' to compare male and female youth disengagement in Germany.
- Source
- Eurostat
- Rows
- 1,764
- Columns
- 6
- Source cadence
- Yearly
- Last refreshed
- Sep 26, 2026
- Theme
- education
| Column | Type | Description |
|---|---|---|
| year | string | Reference year of the observation (stored as January 1), from the 'time' dimension. |
| country_code | string | Reporting country: ISO 3166-1 alpha-3 (mapped from Eurostat's alpha-2 codes). Also carries the provider aggregates (e.g. 'EU27_2020', 'EA20') verbatim. |
| country_name | string | Canonical English country name (hub.normalize), or the Eurostat-published label for the EU/EA aggregates. |
| sex | string | Sex from the 'sex' dimension: M ('Males') and F ('Females'). Age slice age=Y15-29 ('From 15 to 29 years'); training slice training=NO_FE_NO_NFE ('Neither formal nor non-formal education or training'); labour-status slice wstatus=NEMP ('Not employed persons'). |
| sex_label | string | Eurostat-published group label, verbatim from the API. |
| neet_rate_pct | float | Share of the sex group's 15-29 population neither in employment nor in education or training, from the 'unit' indicator PC ('Percentage') (dataset edat_lfse_20, 'Young persons neither in employment nor in education and training by labour status (NEET rates)', compiled from the EU Labour Force Survey microdata). Female rates run above male rates in the large majority of published country-years. (unit: percent) |
- Current
20260926T051518Z-1e54c1edfd66 · sha256 1e54c1edfd66…
1,764 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/eurostat/eurostat_neet_rate_by_sex_annual" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/eurostat/eurostat_neet_rate_by_sex_annual").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/eurostat/eurostat_neet_rate_by_sex_annual
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20260926T051518Z-1e54c1edfd66 and its content hash, so readers get exactly the data you used.
Eurostat. (2026). NEET rate by sex, 15-29 (annual, Europe) [Data set, snapshot 20260926T051518Z-1e54c1edfd66, sha256 1e54c1edfd66]. Datazimuts. Retrieved 2026-09-26, from https://datazimuts.com/en/datasets/eurostat/eurostat_neet_rate_by_sex_annual?snapshot=20260926T051518Z-1e54c1edfd66
@misc{dz_eurostat_eurostat_neet_rate_by_sex_annua_1e54c1ed,
title = {{NEET rate by sex, 15-29 (annual, Europe)}},
author = {{Eurostat}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/eurostat/eurostat_neet_rate_by_sex_annual?snapshot=20260926T051518Z-1e54c1edfd66}},
note = {Snapshot 20260926T051518Z-1e54c1edfd66, sha256 1e54c1edfd66518761b9160bee81b4ed3b7b17c5b94783c2e8ad92366be4f941; accessed 2026-09-26}
}Embed a table or a chart
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<iframe src="https://datazimuts.com/embed/chart?dataset=eurostat%2Feurostat_neet_rate_by_sex_annual&lang=en&theme=auto&snapshot=20260926T051518Z-1e54c1edfd66&x=year&y=neet_rate_pct&agg=avg" title="NEET rate by sex, 15-29 (annual, Europe)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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