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.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Source
- Eurostat
- Lignes
- 1 764
- Colonnes
- 6
- Cadence de la source
- Annuelle
- Dernière actualisation
- 26 sept. 2026
- Thème
- education
| Colonne | 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) |
- Actuelle
20260926T051518Z-1e54c1edfd66 · sha256 1e54c1edfd66…
1 764 lignes · premier instantané
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (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)Point d’accès API : https://datazimuts.com/v1/datasets/eurostat/eurostat_neet_rate_by_sex_annual
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.
D’où viennent ces données et ce qui en a été fait. Le travail des autres apparaît sous forme de décomptes ; seuls les projets partagés sont nommés.
Citer cet instantané
Épinglé à l’instantané 20260926T051518Z-1e54c1edfd66 et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
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/fr/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/fr/datasets/eurostat/eurostat_neet_rate_by_sex_annual?snapshot=20260926T051518Z-1e54c1edfd66}},
note = {Snapshot 20260926T051518Z-1e54c1edfd66, sha256 1e54c1edfd66518761b9160bee81b4ed3b7b17c5b94783c2e8ad92366be4f941; accessed 2026-09-26}
}Intégrer un tableau ou un graphique
Collez ce code dans n’importe quelle page. L’intégration est épinglée au même instantané, suit le thème clair ou sombre du lecteur et affiche toujours la source, la licence et un lien de retour.
<iframe src="https://datazimuts.com/embed/chart?dataset=eurostat%2Feurostat_neet_rate_by_sex_annual&lang=fr&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>
Posez une question sur ce jeu de données. Les réponses viennent uniquement de sa fiche, de son profil mesuré et de son historique, et citent les faits utilisés.