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electricsheepasia/asia-ilo-pop-2wap-sex-age-nb-working-age-population-by-sex-and-age-un-estimates

Working-age population by sex and age -- UN estimates and projections, July 2024 (thousand | Asia (ILOSTAT) 🌏 168,756 observations · 49 Asia countries · 1990–2030 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 168,756 observations of Population data across 49 Asia countries, spanning 1990–2030, covering 1 distinct indicators. About the source ILOSTAT is the ILO's central statistics database, the leading global source for… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-ilo-pop-2wap-sex-age-nb-working-age-population-by-sex-and-age-un-estimates.

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Dataset Card

Working-age population by sex and age -- UN estimates and projections, July 2024 (thousand | Asia (ILOSTAT)

🌏 168,756 observations · 49 Asia countries · 1990–2030 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 168,756 observations of Population data across 49 Asia countries, spanning 1990–2030, 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: Population

Methodology

Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=POP_2WAP_SEX_AGE_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
AFG3,44419902030
ARE3,44419902030
ARM3,44419902030
AZE3,44419902030
BGD3,44419902030
BHR3,44419902030
BRN3,44419902030
BTN3,44419902030
CHN3,44419902030
CYP3,44419902030
GEO3,44419902030
IDN3,44419902030
IND3,44419902030
IRN3,44419902030
IRQ3,44419902030
...34 more countries

Indicators (sample)

  • —POP_2WAP_SEX_AGE_NB — Working-age population by sex and age -- UN estimates and projections, July 2024 (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 codePOP_2WAP_SEX_AGE_NB
indicator.labelstringIndicator name in EnglishWorking-age population by sex and age…
sexstringDisaggregation by sex (SEXT = total, SEXM = male, SEX_F = female)SEX_T
sex.labelstring—Total
classif1stringFirst classification variable (age, education, status, etc.)AGE_YTHADULT_YGE15
classif1.labelstring—Age (Youth, adults): 15+
timeint64Observation year2030
obs_valuefloat64Observed indicator value (unit varies — see indicator definition)29680.974

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-pop-2wap-sex-age-nb-working-age-population-by-sex-and-age-un-estimates")
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"] == "POP_2WAP_SEX_AGE_NB"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="POP_2WAP_SEX_AGE_NB")

Pivot to country × year matrix

python
matrix = (df[df["indicator"] == "POP_2WAP_SEX_AGE_NB"]
          .pivot_table(index="time", columns="ref_area", values="obs_value"))
print(matrix.tail())

Citation

bibtex
@misc{asia_ilo_pop_2wap_sex_age_nb_working_age_population_by_sex_and_age_un_estimates_2030,
  title        = {Working-age population by sex and age -- UN estimates and projections, July 2024 (thousand | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2030},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=POP_2WAP_SEX_AGE_NB},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-pop-2wap-sex-age-nb-working-age-population-by-sex-and-age-un-estimates}}
}

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=POP2WAPSEXAGENB