electricsheepasia/asia-ilo-ear-ehra-sex-age-cur-nb-average-hourly-earnings-of-employees-by-sex-and-ag
Average hourly earnings of employees by sex and age and currency | Asia (ILOSTAT) 🌏 14,982 observations · 25 Asia countries · 1996–2025 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 14,982 observations of Earnings data across 25 Asia countries, spanning 1996–2025, covering 1 distinct indicators. About the source ILOSTAT is the ILO's central statistics database, the leading global source for labour statistics. It compiles… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-ilo-ear-ehra-sex-age-cur-nb-average-hourly-earnings-of-employees-by-sex-and-ag.
Average hourly earnings of employees by sex and age and currency | Asia (ILOSTAT)
🌏 14,982 observations · 25 Asia countries · 1996–2025 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)
TL;DR
This dataset contains 14,982 observations of Earnings data across 25 Asia countries, spanning 1996–2025, 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.
Methodology
Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=EAR_EHRA_SEX_AGE_CUR_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
25 Asia countries · top rows shown below, sorted by row count:
Indicators (sample)
EAR_EHRA_SEX_AGE_CUR_NB— Average hourly earnings of employees by sex and age and currency
Schema
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-ear-ehra-sex-age-cur-nb-average-hourly-earnings-of-employees-by-sex-and-ag")
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"] == "EAR_EHRA_SEX_AGE_CUR_NB"]
.sort_values("time"))
sample.plot(x="time", y="obs_value", title="EAR_EHRA_SEX_AGE_CUR_NB")Pivot to country × year matrix
matrix = (df[df["indicator"] == "EAR_EHRA_SEX_AGE_CUR_NB"]
.pivot_table(index="time", columns="ref_area", values="obs_value"))
print(matrix.tail())Citation
@misc{asia_ilo_ear_ehra_sex_age_cur_nb_average_hourly_earnings_of_employees_by_sex_and_ag_2025,
title = {Average hourly earnings of employees by sex and age and currency | Asia (ILOSTAT)},
author = {International Labour Organization (ILO)},
year = {2025},
url = {https://www.ilo.org/shinyapps/bulkexplorer/?id=EAR_EHRA_SEX_AGE_CUR_NB},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-ear-ehra-sex-age-cur-nb-average-hourly-earnings-of-employees-by-sex-and-ag}}
}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 2026-05-27 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=EAREHRASEXAGECURNB_