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electricsheepasia/asia-ilo-eip-neet-sex-geo-rt-share-of-youth-not-in-employment-education-or-trai

Share of youth not in employment, education or training (NEET) by sex and rural / urban ar | Asia (ILOSTAT) 🌏 2,968 observations · 30 Asia countries · 1970–2025 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 2,968 observations of Other measures of labour underutilization data across 30 Asia countries, spanning 1970–2025, covering 1 distinct indicators. About the source ILOSTAT is the ILO's central statistics database, the… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-ilo-eip-neet-sex-geo-rt-share-of-youth-not-in-employment-education-or-trai.

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Dataset Card

Share of youth not in employment, education or training (NEET) by sex and rural / urban ar | Asia (ILOSTAT)

🌏 2,968 observations · 30 Asia countries · 1970–2025 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 2,968 observations of Other measures of labour underutilization data across 30 Asia countries, spanning 1970–2025, covering 1 distinct indicators.

About the source

ILOSTAT is the ILO's central statistics database, the leading global source for labour statistics. It compiles indicators across employment, unemployment, wages, working time, child labour, informal economy, social protection, occupational injuries, and SDG decent work targets — drawing on national labour force surveys, household income surveys, establishment surveys, and administrative records. Coverage spans 200+ economies, with the ILO's Department of Statistics responsible for harmonisation.

  • —Source: ILOSTAT
  • —Publisher: International Labour Organization (ILO)
  • —License: cc-by-4.0
  • —Topic: Other measures of labour underutilization

Methodology

Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=EIP_NEET_SEX_GEO_RT and filtered to Asia ISO3 country codes. ILOSTAT harmonises raw survey microdata using ICLS (International Conference of Labour Statisticians) definitions; sources are flagged in the source.label column for traceability.

Geographic coverage

30 Asia countries · top rows shown below, sorted by row count:

CountryRowsFirst yearLast year
PSE26420002022
IDN25219962023
CYP23419992024
KHM18019962023
MNG17120032024
ARM16220012023
VNM15620072024
PHL15620072023
PAK15320052025
THA12920072024
TUR12620002013
LKA12620102024
GEO11720122024
IND11719942025
BRN8120142024
...15 more countries

Indicators (sample)

  • —EIP_NEET_SEX_GEO_RT — Share of youth not in employment, education or training (NEET) by sex and rural / urban areas (%)

Schema

ColumnTypeDescriptionExample
ref_areastringISO 3166-1 alpha-3 country codeAFG
ref_area.labelstringCountry name in EnglishAfghanistan
sourcestringILOSTAT source code (e.g. labour force survey)BA:15715
source.labelstringSource name in EnglishLFS - Labour Force Survey
indicatorstringILOSTAT indicator codeEIP_NEET_SEX_GEO_RT
indicator.labelstringIndicator name in EnglishShare of youth not in employment, edu…
sexstringDisaggregation by sex (SEXT = total, SEXM = male, SEX_F = female)SEX_T
sex.labelstring—Total
classif1stringFirst classification variable (age, education, status, etc.)GEO_COV_NAT
classif1.labelstring—Area type: National
timeint64Observation year2021
obs_valuefloat64Observed indicator value (unit varies — see indicator definition)43.769
obs_statusstringObservation status flag (e.g. provisional, unreliable)B
obs_status.labelstring—Break in series
note_indicatorstring—I11:264
note_indicator.labelstring—Break in series: Methodology revised
note_sourcestring—R1:3513_S3:8
note_source.labelstring—Repository: ILO-STATISTICS - Micro da…

Disaggregation dimensions

The following columns provide disaggregation dimensions:

  • —`sex` (4 unique values): SEX_T, SEX_M, SEX_F, SEX_O

Data quality & caveats

  • —Data is annual frequency. Some indicators also publish monthly or quarterly series — those are not included here.
  • —When an indicator has multiple sources for the same country×year, the ILO-selected 'best source' is used.
  • —Disaggregation columns (sex, classif1, classif2) are non-null only when the indicator publishes that breakdown.

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-ilo-eip-neet-sex-geo-rt-share-of-youth-not-in-employment-education-or-trai")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python
indonesia = df[df["ref_area"] == "IDN"]

Time-series for a single indicator

python
sample = (df[df["indicator"] == "EIP_NEET_SEX_GEO_RT"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="EIP_NEET_SEX_GEO_RT")

Pivot to country × year matrix

python
matrix = (df[df["indicator"] == "EIP_NEET_SEX_GEO_RT"]
          .pivot_table(index="time", columns="ref_area", values="obs_value"))
print(matrix.tail())

Citation

bibtex
@misc{asia_ilo_eip_neet_sex_geo_rt_share_of_youth_not_in_employment_education_or_trai_2025,
  title        = {Share of youth not in employment, education or training (NEET) by sex and rural / urban ar | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2025},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=EIP_NEET_SEX_GEO_RT},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-eip-neet-sex-geo-rt-share-of-youth-not-in-employment-education-or-trai}}
}

License

Released under cc-by-4.0.

Original data © International Labour Organization (ILO). When using this dataset, please cite both the original source above and the Electric Sheep Asia repackaging.

About Electric Sheep

Electric Sheep Asia is part of the Electric Sheep mission: a unified, ML-ready data layer for Asia on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepasia


Provenance: ingested 2026-05-27 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=EIPNEETSEXGEORT