electricsheepasia/asia-ilo-ear-shra-sex-cur-nb-average-hourly-earnings-of-stem-employees-by-sex-a

Average hourly earnings of STEM employees by sex and currency | Asia (ILOSTAT)

🌏 1,110 observations · 21 Asia countries · 2007–2025 · Repackaged by Electric Sheep Asia

TL;DR

This dataset contains 1,110 observations of Workers in STEM occupations data across 21 Asia countries, spanning 2007–2025, 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: Workers in STEM occupations

Methodology

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

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

Country	Rows	First year	Last year
VNM	135	2009	2024
KHM	126	2007	2023
TUR	117	2012	2024
LKA	105	2013	2024
THA	99	2014	2024
PHL	63	2017	2023
PAK	60	2013	2025
JOR	54	2017	2023
MNG	54	2019	2024
BTN	45	2018	2022
MMR	45	2015	2020
TLS	36	2010	2021
BGD	36	2017	2024
IND	33	2022	2025
PSE	30	2015	2025
...	6 more countries

Indicators (sample)

• EAR_SHRA_SEX_CUR_NB — Average hourly earnings of STEM employees by sex and currency

Schema

Column	Type	Description	Example
ref_area	string	ISO 3166-1 alpha-3 country code	BGD
ref_area.label	string	Country name in English	Bangladesh
source	string	ILOSTAT source code (e.g. labour force survey)	BA:673
source.label	string	Source name in English	LFS - Labour Force Survey
indicator	string	ILOSTAT indicator code	EAR_SHRA_SEX_CUR_NB
indicator.label	string	Indicator name in English	Average hourly earnings of STEM emplo…
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.)	CUR_TYPE_LCU
classif1.label	string	—	Currency: Local currency
time	int64	Observation year	2024
obs_value	float64	Observed indicator value (unit varies — see indicator definition)	126.37
obs_status	string	Observation status flag (e.g. provisional, unreliable)	B
obs_status.label	string	—	Break in series
note_indicator	string	—	T30:114
note_indicator.label	string	—	Currency: BGD - Taka (BDT)
note_source	string	—	R1:3513
note_source.label	string	—	Repository: ILO-STATISTICS - Micro da…

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-ear-shra-sex-cur-nb-average-hourly-earnings-of-stem-employees-by-sex-a")
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_SHRA_SEX_CUR_NB"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="EAR_SHRA_SEX_CUR_NB")

Pivot to country × year matrix

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

Citation

@misc{asia_ilo_ear_shra_sex_cur_nb_average_hourly_earnings_of_stem_employees_by_sex_a_2025,
  title        = {Average hourly earnings of STEM employees by sex and currency | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2025},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=EAR_SHRA_SEX_CUR_NB},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-ear-shra-sex-cur-nb-average-hourly-earnings-of-stem-employees-by-sex-a}}
}

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=EAR_SHRA_SEX_CUR_NB