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electricsheepasia/asia-ilo-inj-nftl-sex-inj-mig-nb-cases-of-non-fatal-occupational-injury-by-sex-type

Cases of non-fatal occupational injury by sex, type of incapacity and migrant status | Asia (ILOSTAT) 🌏 1,432 observations · 22 Asia countries · 1971–2024 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 1,432 observations of Occupational injuries data across 22 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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-ilo-inj-nftl-sex-inj-mig-nb-cases-of-non-fatal-occupational-injury-by-sex-type.

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Cases of non-fatal occupational injury by sex, type of incapacity and migrant status | Asia (ILOSTAT)

🌏 1,432 observations · 22 Asia countries · 1971–2024 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 1,432 observations of Occupational injuries data across 22 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_INJ_MIG_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

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

CountryRowsFirst yearLast year
CYP19620092015
THA16419992024
LKA14019992024
TUR14020082024
UZB13620152024
MYS10819942022
IND8419712007
SGP8419992023
TWN5419882005
GEO4720192024
JOR4519902006
PAK4420182021
PHL4419902021
ISR3420092023
BHR2720202020
...7 more countries

Indicators (sample)

  • —INJ_NFTL_SEX_INJ_MIG_NB — Cases of non-fatal occupational injury by sex, type of incapacity 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)FF:172
source.labelstringSource name in EnglishADM-LIR - Records of Labour Inspectio…
indicatorstringILOSTAT indicator codeINJ_NFTL_SEX_INJ_MIG_NB
indicator.labelstringIndicator name in EnglishCases of non-fatal occupational injur…
sexstringDisaggregation by sex (SEXT = total, SEXM = male, SEX_F = female)SEX_T
sex.labelstring—Total
classif1stringFirst classification variable (age, education, status, etc.)INJ_INCAPACITY_TOTAL
classif1.labelstring—Type of incapacity: Total
classif2stringSecond classification variable where applicableMIG_STATUS_TOTAL
classif2.labelstring—Migrant status: Total
timeint64Observation year2010
obs_valuefloat64Observed indicator value (unit varies — see indicator definition)13.0
obs_statusstringObservation status flag (e.g. provisional, unreliable)—
obs_status.labelstring——
note_indicatorstring—T13:149_T14:153
note_indicator.labelstring—Coverage of occupational injuries: Re…
note_sourcestring—S9:66
note_source.labelstring—Reference group coverage: Employees

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-inj-mig-nb-cases-of-non-fatal-occupational-injury-by-sex-type")
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_INJ_MIG_NB"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="INJ_NFTL_SEX_INJ_MIG_NB")

Pivot to country × year matrix

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

Citation

bibtex
@misc{asia_ilo_inj_nftl_sex_inj_mig_nb_cases_of_non_fatal_occupational_injury_by_sex_type_2024,
  title        = {Cases of non-fatal occupational injury by sex, type of incapacity and migrant status | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2024},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=INJ_NFTL_SEX_INJ_MIG_NB},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-inj-nftl-sex-inj-mig-nb-cases-of-non-fatal-occupational-injury-by-sex-type}}
}

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=INJNFTLSEXINJMIGNB_