electricsheepasia/asia-ilo-une-2une-sex-age-nb-unemployment-by-sex-and-age-ilo-modelled-estimates

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

🌏 16,236 observations · 49 Asia countries · 1991–2027 · Repackaged by Electric Sheep Asia

TL;DR

This dataset contains 16,236 observations of Unemployment data across 49 Asia countries, spanning 1991–2027, 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: Unemployment

Methodology

Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=UNE_2UNE_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:

Country	Rows	First year	Last year
AFG	333	1991	2027
ARE	333	1991	2027
ARM	333	1991	2027
AZE	333	1991	2027
BGD	333	1991	2027
BHR	333	1991	2027
BRN	333	1991	2027
BTN	333	1991	2027
CHN	333	1991	2027
CYP	333	1991	2027
GEO	333	1991	2027
IDN	333	1991	2027
IND	333	1991	2027
IRN	333	1991	2027
IRQ	333	1991	2027
...	34 more countries

Indicators (sample)

• UNE_2UNE_SEX_AGE_NB — Unemployment by sex and age -- ILO modelled estimates, Nov. 2025 (thousands)

Schema

Column	Type	Description	Example
ref_area	string	ISO 3166-1 alpha-3 country code	AFG
ref_area.label	string	Country name in English	Afghanistan
source	string	ILOSTAT source code (e.g. labour force survey)	XA:2198
source.label	string	Source name in English	ILO - Modelled Estimates
indicator	string	ILOSTAT indicator code	UNE_2UNE_SEX_AGE_NB
indicator.label	string	Indicator name in English	Unemployment by sex and age -- ILO mo…
sex	string	Disaggregation by sex (SEX_T = total, SEX_M = male, SEX_F = female)	SEX_T
sex.label	string	—	Total
classif1	string	First classification variable (age, education, status, etc.)	AGE_YTHADULT_YGE15
classif1.label	string	—	Age (Youth, adults): 15+
time	int64	Observation year	2027
obs_value	float64	Observed indicator value (unit varies — see indicator definition)	1308.51
obs_status	string	Observation status flag (e.g. provisional, unreliable)	A
obs_status.label	string	—	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

from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-ilo-une-2une-sex-age-nb-unemployment-by-sex-and-age-ilo-modelled-estimates")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

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

Time-series for a single indicator

sample = (df[df["indicator"] == "UNE_2UNE_SEX_AGE_NB"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="UNE_2UNE_SEX_AGE_NB")

Pivot to country × year matrix

matrix = (df[df["indicator"] == "UNE_2UNE_SEX_AGE_NB"]
          .pivot_table(index="time", columns="ref_area", values="obs_value"))
print(matrix.tail())

Citation

@misc{asia_ilo_une_2une_sex_age_nb_unemployment_by_sex_and_age_ilo_modelled_estimates_2027,
  title        = {Unemployment by sex and age -- ILO modelled estimates, Nov. 2025 (thousands) | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2027},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=UNE_2UNE_SEX_AGE_NB},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-une-2une-sex-age-nb-unemployment-by-sex-and-age-ilo-modelled-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

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Provenance: ingested 2026-05-28 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=UNE_2UNE_SEX_AGE_NB