electricsheepasia/asia-ilo-une-tune-sex-age-nb-unemployment-by-sex-and-age-thousands

Unemployment by sex and age (thousands) | Asia (ILOSTAT)

🌏 68,156 observations · 48 Asia countries · 1952–2025 · Repackaged by Electric Sheep Asia

TL;DR

This dataset contains 68,156 observations of Unemployment data across 48 Asia countries, spanning 1952–2025, 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: Unemployment

Methodology

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

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

Country	Rows	First year	Last year
JPN	5,052	1953	2025
SGP	3,554	1970	2024
TWN	3,445	1978	2020
IDN	3,152	1973	2023
CYP	2,904	1974	2025
THA	2,884	1971	2024
ISR	2,855	1969	2024
PAK	2,638	1969	2025
PHL	2,570	1969	2023
TUR	2,440	1982	2025
MYS	2,410	1970	2022
KOR	2,317	1969	2025
GEO	2,275	1991	2024
VNM	2,148	1996	2024
PSE	2,018	2000	2025
...	33 more countries

Indicators (sample)

• UNE_TUNE_SEX_AGE_NB — Unemployment by sex and age (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)	BA:15715
source.label	string	Source name in English	LFS - Labour Force Survey
indicator	string	ILOSTAT indicator code	UNE_TUNE_SEX_AGE_NB
indicator.label	string	Indicator name in English	Unemployment by sex and age (thousands)
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	2021
obs_value	float64	Observed indicator value (unit varies — see indicator definition)	462.411
obs_status	string	Observation status flag (e.g. provisional, unreliable)	U
obs_status.label	string	—	Unreliable
note_classif	string	—	C6:2300_C6:1058
note_classif.label	string	—	Nonstandard age group: Including ages…
note_indicator	string	—	I11:264
note_indicator.label	string	—	Break in series: Methodology revised
note_source	string	—	R1:3513_S3:8
note_source.label	string	—	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

from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-ilo-une-tune-sex-age-nb-unemployment-by-sex-and-age-thousands")
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_TUNE_SEX_AGE_NB"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="UNE_TUNE_SEX_AGE_NB")

Pivot to country × year matrix

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

Citation

@misc{asia_ilo_une_tune_sex_age_nb_unemployment_by_sex_and_age_thousands_2025,
  title        = {Unemployment by sex and age (thousands) | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2025},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=UNE_TUNE_SEX_AGE_NB},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-une-tune-sex-age-nb-unemployment-by-sex-and-age-thousands}}
}

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 2026-05-26 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=UNE_TUNE_SEX_AGE_NB