CoolFace
Datasetpublic

electricsheepasia/asia-ilo-emp-2emp-sex-ocu-nb-employment-by-sex-and-occupation-ilo-modelled-esti

Employment by sex and occupation -- ILO modelled estimates, Nov. 2025 (thousands) | Asia (ILOSTAT) 🌏 46,170 observations · 49 Asia countries · 1991–2025 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 46,170 observations of Employment data across 49 Asia countries, spanning 1991–2025, 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-2emp-sex-ocu-nb-employment-by-sex-and-occupation-ilo-modelled-esti.

sourceHugging Facecc-by-4.0updated 4mo agoView on Hugging Face
0likes46downloads
Dataset Card

Employment by sex and occupation -- ILO modelled estimates, Nov. 2025 (thousands) | Asia (ILOSTAT)

🌏 46,170 observations · 49 Asia countries · 1991–2025 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 46,170 observations of Employment data across 49 Asia countries, spanning 1991–2025, 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: Employment

Methodology

Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=EMP_2EMP_SEX_OCU_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
AFG94519912025
ARE94519912025
ARM94519912025
AZE94519912025
BGD94519912025
BHR94519912025
BRN94519912025
BTN94519912025
CHN94519912025
CYP94519912025
GEO94519912025
IDN94519912025
IND94519912025
IRN94519912025
IRQ94519912025
...34 more countries

Indicators (sample)

  • —EMP_2EMP_SEX_OCU_NB — Employment by sex and occupation -- 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_2EMP_SEX_OCU_NB
indicator.labelstringIndicator name in EnglishEmployment by sex and occupation -- I…
sexstringDisaggregation by sex (SEXT = total, SEXM = male, SEX_F = female)SEX_T
sex.labelstring—Total
classif1stringFirst classification variable (age, education, status, etc.)OCU_ISCO08_TOTAL
classif1.labelstring—Occupation (ISCO-08): Total
timeint64Observation year2025
obs_valuefloat64Observed indicator value (unit varies — see indicator definition)8173.748
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-2emp-sex-ocu-nb-employment-by-sex-and-occupation-ilo-modelled-esti")
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_2EMP_SEX_OCU_NB"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="EMP_2EMP_SEX_OCU_NB")

Pivot to country × year matrix

python
matrix = (df[df["indicator"] == "EMP_2EMP_SEX_OCU_NB"]
          .pivot_table(index="time", columns="ref_area", values="obs_value"))
print(matrix.tail())

Citation

bibtex
@misc{asia_ilo_emp_2emp_sex_ocu_nb_employment_by_sex_and_occupation_ilo_modelled_esti_2025,
  title        = {Employment by sex and occupation -- ILO modelled estimates, Nov. 2025 (thousands) | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2025},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=EMP_2EMP_SEX_OCU_NB},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-emp-2emp-sex-ocu-nb-employment-by-sex-and-occupation-ilo-modelled-esti}}
}

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=EMP2EMPSEXOCUNB