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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
  - africa
  - ilostat
  - other-measures-of-labour-underutilization
  - ilo
  - labour
  - employment
pretty_name: >-
  Combined rate of time-related underemployment and unemployment (LU2) by sex
  and rural / ur | Africa (ILOSTAT)

Combined rate of time-related underemployment and unemployment (LU2) by sex and rural / ur | Africa (ILOSTAT)

🌍 1,131 observations · 32 Africa countries · 1996–2025 · Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset contains 1,131 observations of Other measures of labour underutilization data across 32 Africa countries, spanning 1996–2025, 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: Other measures of labour underutilization

Methodology

Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=LUU_XLU2_SEX_GEO_RT and filtered to Africa 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 Africa countries · top rows shown below, sorted by row count:

Country Rows First year Last year
ZAF 156 2008 2024
RWA 90 2014 2025
ZMB 72 2017 2024
AGO 66 2019 2025
SEN 63 2011 2024
GHA 63 2006 2024
ZWE 63 2011 2024
UGA 63 2010 2021
MLI 45 2018 2024
EGY 45 2016 2024
NGA 36 2019 2024
SLE 27 2003 2018
GMB 27 2012 2025
KEN 27 2019 2022
CIV 27 2016 2019
... 17 more countries

Indicators (sample)

  • LUU_XLU2_SEX_GEO_RT — Combined rate of time-related underemployment and unemployment (LU2) by sex and rural / urban areas (%)

Schema

Column Type Description Example
ref_area string ISO 3166-1 alpha-3 country code AGO
ref_area.label string Country name in English Angola
source string ILOSTAT source code (e.g. labour force survey) BA:13951
source.label string Source name in English LFS - Employment Survey
indicator string ILOSTAT indicator code LUU_XLU2_SEX_GEO_RT
indicator.label string Indicator name in English Combined rate of time-related underem…
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.) GEO_COV_NAT
classif1.label string Area type: National
time int64 Observation year 2025
obs_value float64 Observed indicator value (unit varies — see indicator definition) 11.141
obs_status string Observation status flag (e.g. provisional, unreliable) U
obs_status.label string Unreliable
note_indicator string I11:264
note_indicator.label string Break in series: Methodology revised
note_source string R1:3513
note_source.label string Repository: ILO-STATISTICS - Micro da…

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("electricsheepafrica/africa-ilo-luu-xlu2-sex-geo-rt-combined-rate-of-time-related-underemployment-and")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

kenya = df[df["ref_area"] == "KEN"]

Time-series for a single indicator

sample = (df[df["indicator"] == "LUU_XLU2_SEX_GEO_RT"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="LUU_XLU2_SEX_GEO_RT")

Pivot to country × year matrix

matrix = (df[df["indicator"] == "LUU_XLU2_SEX_GEO_RT"]
          .pivot_table(index="time", columns="ref_area", values="obs_value"))
print(matrix.tail())

Citation

@misc{africa_ilo_luu_xlu2_sex_geo_rt_combined_rate_of_time_related_underemployment_and_2025,
  title        = {Combined rate of time-related underemployment and unemployment (LU2) by sex and rural / ur | Africa (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2025},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=LUU_XLU2_SEX_GEO_RT},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-ilo-luu-xlu2-sex-geo-rt-combined-rate-of-time-related-underemployment-and}}
}

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 Africa repackaging.

About Electric Sheep

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


Provenance: ingested 2026-05-26 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=LUU_XLU2_SEX_GEO_RT