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electricsheepeurope/europe-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 | Europe (ILOSTAT) 🇪🇺 7,424 observations · 32 Europe countries · 1990–2024 · Repackaged by Electric Sheep Europe TL;DR This dataset contains 7,424 observations of Occupational injuries data across 32 Europe countries, spanning 1990–2024, covering 1 distinct indicators. About the source ILOSTAT is the ILO's central statistics database, the leading global… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepeurope/europe-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 | Europe (ILOSTAT)

🇪🇺 7,424 observations · 32 Europe countries · 1990–2024 · Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)

rows countries years indicators license

TL;DR

This dataset contains 7,424 observations of Occupational injuries data across 32 Europe countries, spanning 1990–2024, 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 Europe 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

32 Europe countries · top rows shown below, sorted by row count:

CountryRowsFirst yearLast year
ESP53119932023
HUN49819942024
FRA43819902024
BEL42319932023
ROU42019962024
FIN40020052023
LUX35020092024
MLT33820012024
DNK32919912015
GRC32420112023
SVK30019962024
BGR29520032023
ITA27019942016
PRT25220092015
CHE25020092023
...17 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 codeAUT
ref_area.labelstringCountry name in EnglishAustria
sourcestringILOSTAT source code (e.g. labour force survey)FA:257
source.labelstringSource name in EnglishADM-IR - Database Records from all in…
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 year2016
obs_valuefloat64Observed indicator value (unit varies — see indicator definition)58320.0
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—S3:24_S9:66
note_source.labelstring—Data reference period: End of the yea…

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("electricsheepeurope/europe-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
germany = df[df["ref_area"] == "DEU"]

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{europe_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 | Europe (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 Europe},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-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 Europe repackaging.

About Electric Sheep

Electric Sheep Europe is part of the Electric Sheep mission: a unified, ML-ready data layer for Europe 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/electricsheepeurope


Provenance: ingested 2026-05-28 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=INJNFTLSEXINJMIGNB_