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metadata
license: cc-by-4.0
language:
  - en
task_categories:
  - tabular-classification
  - tabular-regression
  - time-series-forecasting
multilinguality: monolingual
size_categories:
  - 1K<n<10K
tags:
  - tabular
  - europe
  - ilostat
  - social-protection
  - ilo
  - labour
  - employment
pretty_name: >-
  SDG indicator 1.3.1 - Proportion of population covered by social protection
  floors/systems | Europe (ILOSTAT)

SDG indicator 1.3.1 - Proportion of population covered by social protection floors/systems | Europe (ILOSTAT)

🇪🇺 2,540 observations · 43 Europe countries · 2000–2023 · Repackaged by Electric Sheep Europe

rows countries years indicators license

TL;DR

This dataset contains 2,540 observations of Social protection data across 43 Europe countries, spanning 2000–2023, 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: Social protection

Methodology

Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=SDG_0131_SEX_SOC_RT 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

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

Country Rows First year Last year
FRA 96 2000 2022
BEL 95 2000 2022
DEU 94 2000 2022
FIN 94 2000 2022
DNK 84 2000 2023
LVA 80 2000 2022
SWE 79 2000 2022
AUT 78 2000 2022
NLD 77 2000 2022
LUX 76 2000 2022
CHE 75 2000 2021
EST 75 2000 2022
IRL 74 2000 2022
HUN 74 2000 2022
ESP 73 2000 2022
... 28 more countries

Indicators (sample)

  • SDG_0131_SEX_SOC_RT — SDG indicator 1.3.1 - Proportion of population covered by social protection floors/systems by sex and function (%)

Schema

Column Type Description Example
ref_area string ISO 3166-1 alpha-3 country code ALB
ref_area.label string Country name in English Albania
source string ILOSTAT source code (e.g. labour force survey) XA:6547
source.label string Source name in English ILO - Social Security Inquiry Database
indicator string ILOSTAT indicator code SDG_0131_SEX_SOC_RT
indicator.label string Indicator name in English SDG indicator 1.3.1 - Proportion of p…
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.) SOC_CONTIG_TOTAL
classif1.label string Function: Population covered by at le…
time int64 Observation year 2021
obs_value float64 Observed indicator value (unit varies — see indicator definition) 78.1
obs_status string Observation status flag (e.g. provisional, unreliable)
obs_status.label string
note_classif string C15:6326
note_classif.label string Social security coverage: Estimated b…

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("electricsheepeurope/europe-ilo-sdg-0131-sex-soc-rt-sdg-indicator-1-3-1-proportion-of-population-cover")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

germany = df[df["ref_area"] == "DEU"]

Time-series for a single indicator

sample = (df[df["indicator"] == "SDG_0131_SEX_SOC_RT"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="SDG_0131_SEX_SOC_RT")

Pivot to country × year matrix

matrix = (df[df["indicator"] == "SDG_0131_SEX_SOC_RT"]
          .pivot_table(index="time", columns="ref_area", values="obs_value"))
print(matrix.tail())

Citation

@misc{europe_ilo_sdg_0131_sex_soc_rt_sdg_indicator_1_3_1_proportion_of_population_cover_2023,
  title        = {SDG indicator 1.3.1 - Proportion of population covered by social protection floors/systems | Europe (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2023},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=SDG_0131_SEX_SOC_RT},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Europe},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-ilo-sdg-0131-sex-soc-rt-sdg-indicator-1-3-1-proportion-of-population-cover}}
}

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 2026-05-25 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=SDG_0131_SEX_SOC_RT