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electricsheepasia/asia-ilo-inj-nftl-sex-mig-rt-non-fatal-occupational-injuries-per-100-000-worker

Non-fatal occupational injuries per 100'000 workers by sex and migrant status | Asia (ILOSTAT) 🌏 985 observations · 26 Asia countries · 1971–2024 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 985 observations of Occupational injuries data across 26 Asia countries, spanning 1971–2024, covering 1 distinct indicators. About the source ILOSTAT is the ILO's central statistics database, the leading global source for labour… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-ilo-inj-nftl-sex-mig-rt-non-fatal-occupational-injuries-per-100-000-worker.

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Dataset Card

Non-fatal occupational injuries per 100'000 workers by sex and migrant status | Asia (ILOSTAT)

🌏 985 observations · 26 Asia countries · 1971–2024 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 985 observations of Occupational injuries data across 26 Asia countries, spanning 1971–2024, 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: Occupational injuries

Methodology

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

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

CountryRowsFirst yearLast year
TUR17319982024
UZB7920092024
MMR5919932019
KAZ5419852017
AZE5419922023
ISR5219822023
CYP5119772020
LKA5019812024
MYS3919852022
BHR3919792020
KGZ3619832015
SGP3519762015
QAT3520092022
IND3119712007
JOR3019752006
...11 more countries

Indicators (sample)

  • —INJ_NFTL_SEX_MIG_RT — Non-fatal occupational injuries per 100'000 workers by sex and migrant status

Schema

ColumnTypeDescriptionExample
ref_areastringISO 3166-1 alpha-3 country codeARM
ref_area.labelstringCountry name in EnglishArmenia
sourcestringILOSTAT source code (e.g. labour force survey)EB:176
source.labelstringSource name in EnglishOther - Statistical Report on Occupat…
indicatorstringILOSTAT indicator codeINJ_NFTL_SEX_MIG_RT
indicator.labelstringIndicator name in EnglishNon-fatal occupational injuries per 1…
sexstringDisaggregation by sex (SEXT = total, SEXM = male, SEX_F = female)SEX_T
sex.labelstring—Total
classif1stringFirst classification variable (age, education, status, etc.)MIG_STATUS_TOTAL
classif1.labelstring—Migrant status: Total
timeint64Observation year2020
obs_valuefloat64Observed indicator value (unit varies — see indicator definition)29.4
note_indicatorstring—I20:4077_T13:149_T14:156
note_indicator.labelstring—Employment definition: Excluding own-…
note_sourcestring—S8:1619_S9:66_S10:73
note_source.labelstring—Economic activity coverage: Excluding…

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-inj-nftl-sex-mig-rt-non-fatal-occupational-injuries-per-100-000-worker")
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"] == "INJ_NFTL_SEX_MIG_RT"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="INJ_NFTL_SEX_MIG_RT")

Pivot to country × year matrix

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

Citation

bibtex
@misc{asia_ilo_inj_nftl_sex_mig_rt_non_fatal_occupational_injuries_per_100_000_worker_2024,
  title        = {Non-fatal occupational injuries per 100'000 workers by sex and migrant status | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2024},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=INJ_NFTL_SEX_MIG_RT},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-inj-nftl-sex-mig-rt-non-fatal-occupational-injuries-per-100-000-worker}}
}

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=INJNFTLSEXMIGRT