CoolFace
Datasetpublic

electricsheepasia/asia-ilo-emp-2fte-sex-jbf-nb-full-time-equivalent-employment-by-sex-ilo-modelle

Full-time equivalent employment by sex -- ILO modelled estimates, Nov. 2025 (thousands) | Asia (ILOSTAT) 🌏 6,708 observations · 49 Asia countries · 2005–2027 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 6,708 observations of Employment data across 49 Asia countries, spanning 2005–2027, covering 1 distinct indicators. About the source ILOSTAT is the ILO's central statistics database, the leading global source for labour… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-ilo-emp-2fte-sex-jbf-nb-full-time-equivalent-employment-by-sex-ilo-modelle.

sourceHugging Facecc-by-4.0updated 4mo agoView on Hugging Face
0likes12downloads
Dataset Card

Full-time equivalent employment by sex -- ILO modelled estimates, Nov. 2025 (thousands) | Asia (ILOSTAT)

🌏 6,708 observations · 49 Asia countries · 2005–2027 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 6,708 observations of Employment data across 49 Asia countries, spanning 2005–2027, 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: Employment

Methodology

Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=EMP_2FTE_SEX_JBF_NB 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

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

CountryRowsFirst yearLast year
AFG13820052027
ARE13820052027
ARM13820052027
AZE13820052027
BGD13820052027
BHR13820052027
BRN13820052027
BTN13820052027
CHN13820052027
CYP13820052027
GEO13820052027
IDN13820052027
IND13820052027
IRN13820052027
IRQ13820052027
...34 more countries

Indicators (sample)

  • —EMP_2FTE_SEX_JBF_NB — Full-time equivalent employment by sex -- ILO modelled estimates, Nov. 2025 (thousands)

Schema

ColumnTypeDescriptionExample
ref_areastringISO 3166-1 alpha-3 country codeAFG
ref_area.labelstringCountry name in EnglishAfghanistan
sourcestringILOSTAT source code (e.g. labour force survey)XA:2198
source.labelstringSource name in EnglishILO - Modelled Estimates
indicatorstringILOSTAT indicator codeEMP_2FTE_SEX_JBF_NB
indicator.labelstringIndicator name in EnglishFull-time equivalent employment by se…
sexstringDisaggregation by sex (SEXT = total, SEXM = male, SEX_F = female)SEX_T
sex.labelstring—Total
classif1stringFirst classification variable (age, education, status, etc.)JBF_FTE_FTE40
classif1.labelstring—Full-time equivalence: Based on 40 ho…
timeint64Observation year2027
obs_valuefloat64Observed indicator value (unit varies — see indicator definition)7752.571
obs_statusstringObservation status flag (e.g. provisional, unreliable)A
obs_status.labelstring—Adjusted

Disaggregation dimensions

The following columns provide disaggregation dimensions:

  • —`sex` (3 unique values): SEX_T, SEX_M, SEX_F

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-emp-2fte-sex-jbf-nb-full-time-equivalent-employment-by-sex-ilo-modelle")
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"] == "EMP_2FTE_SEX_JBF_NB"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="EMP_2FTE_SEX_JBF_NB")

Pivot to country × year matrix

python
matrix = (df[df["indicator"] == "EMP_2FTE_SEX_JBF_NB"]
          .pivot_table(index="time", columns="ref_area", values="obs_value"))
print(matrix.tail())

Citation

bibtex
@misc{asia_ilo_emp_2fte_sex_jbf_nb_full_time_equivalent_employment_by_sex_ilo_modelle_2027,
  title        = {Full-time equivalent employment by sex -- ILO modelled estimates, Nov. 2025 (thousands) | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2027},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=EMP_2FTE_SEX_JBF_NB},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-emp-2fte-sex-jbf-nb-full-time-equivalent-employment-by-sex-ilo-modelle}}
}

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 2026-05-28 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=EMP2FTESEXJBFNB