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electricsheepeurope/europe-ilo-inj-nftl-eco-nb-cases-of-non-fatal-occupational-injury-by-economic

Cases of non-fatal occupational injury by economic activity | Europe (ILOSTAT) 🇪🇺 24,128 observations · 37 Europe countries · 1970–2024 · Repackaged by Electric Sheep Europe TL;DR This dataset contains 24,128 observations of Occupational injuries data across 37 Europe countries, spanning 1970–2024, 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/electricsheepeurope/europe-ilo-inj-nftl-eco-nb-cases-of-non-fatal-occupational-injury-by-economic.

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Dataset Card

Cases of non-fatal occupational injury by economic activity | Europe (ILOSTAT)

🇪🇺 24,128 observations · 37 Europe countries · 1970–2024 · Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)

rows countries years indicators license

TL;DR

This dataset contains 24,128 observations of Occupational injuries data across 37 Europe countries, spanning 1970–2024, 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_ECO_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

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

CountryRowsFirst yearLast year
CHE1,06019762023
SVK95919852023
ITA95519792023
FIN92819782023
SWE91719782023
ESP91319802023
DEU86319902023
DNK85419782023
PRT85119792023
HUN84819752023
CZE83019912023
ROU81319852023
HRV80719832023
SVN80419832023
NOR80319902023
...22 more countries

Indicators (sample)

  • —INJ_NFTL_ECO_NB — Cases of non-fatal occupational injury by economic activity

Schema

ColumnTypeDescriptionExample
ref_areastringISO 3166-1 alpha-3 country codeAND
ref_area.labelstringCountry name in EnglishAndorra
sourcestringILOSTAT source code (e.g. labour force survey)EA:98
source.labelstringSource name in EnglishOE - Department of Statistics Estimat…
indicatorstringILOSTAT indicator codeINJ_NFTL_ECO_NB
indicator.labelstringIndicator name in EnglishCases of non-fatal occupational injur…
classif1stringFirst classification variable (age, education, status, etc.)ECO_AGGREGATE_TOTAL
classif1.labelstring—Economic activity (Aggregate): Total
timeint64Observation year2015
obs_valuefloat64Observed indicator value (unit varies — see indicator definition)3.0
obs_statusstringObservation status flag (e.g. provisional, unreliable)U
obs_status.labelstring—Unreliable
note_classifstring——
note_classif.labelstring——
note_indicatorstring—T13:150_T14:153_I2:1653
note_indicator.labelstring—Coverage of occupational injuries: Co…
note_sourcestring—S3:24_S9:66
note_source.labelstring—Data reference period: End of the yea…

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-eco-nb-cases-of-non-fatal-occupational-injury-by-economic")
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_ECO_NB"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="INJ_NFTL_ECO_NB")

Pivot to country × year matrix

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

Citation

bibtex
@misc{europe_ilo_inj_nftl_eco_nb_cases_of_non_fatal_occupational_injury_by_economic_2024,
  title        = {Cases of non-fatal occupational injury by economic activity | Europe (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2024},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=INJ_NFTL_ECO_NB},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Europe},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-ilo-inj-nftl-eco-nb-cases-of-non-fatal-occupational-injury-by-economic}}
}

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=INJNFTLECONB_