electricsheepafrica/africa-rwanda-labour-force-indicators-by-sex-e4cc6c46

Labour Force Indicators by Sex | Africa (Rwanda Data Sharing Platform - NISR)

56 rows - 1 Africa country/area - 2019-2025 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 56 rows from Rwanda Data Sharing Platform - NISR, covering Labour Force Indicators by Sex. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Labour and workforce datasets help analysts study employment, participation, skills, sectoral structure, and the movement of people through work and livelihoods.

Source-provided context: Summary: This table is part of the Rwanda Labour Force Survey (LFS) 2025 aggregated schema, which compiles quarterly labour market data from 2019 to 2025 to provide a continuous and longitudinal view of workforce dynamics. It presents key labour force indicators disaggregated by sex, showing how labour market outcomes differ between males and females over time. Geographic Coverage: National coverage across Rwanda. Time Period: Quarterly data from 2019 Q1 to 2025 Q4. Frequency: Quarterly Population/Units: Individuals aged 16 years and above in the labour force. Key Variables: Sex (male/female), labour force participation rate, employment rate, unemployment rate, labour underutilization indicators, and other core labour market metrics. Purpose: To support analysis of gender disparities in labour market outcomes and inform policies on gender equality, employment, and inclusive economic development.

How To Read This Dataset

• One row means: one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
• Primary geography column: country_iso3.
• Best time column: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	56
Countries/areas	1
First period	2019
Last period	2025
Indicators	0
Columns	31
Source format	CSV

Geographic Coverage

Top areas shown below, sorted by row count when available:

Area	Rows	First year	Last year	Name
RWA	56	2019	2025	Rwanda

Indicators, Variables, Or Resource Contents

• This repo preserves one source tabular resource with its usable columns kept together.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa engineering.	9fe40738-0ac6-4ac0-983f-0f76ba831580:0
country_iso3	string	ISO3 country or area code.	RWA
country_name	string	Country or area name.	Rwanda
sex	string	Sex category: "Male" or "Female"	Female
year	int64	Survey year (2019 to 2025)	2019
quarter	string	Survey quarter (Q1, Q2, Q3, Q4)	Q1
employed	double	Source column from the original resource.	1407387.8726897305
employment_to_population_ratio	double	Source column from the original resource.	37.377275851658496
labour_force	double	Source column from the original resource.	1663376.5062483926
labour_force_participation_rate	double	Source column from the original resource.	44.175798104891584
lu1_unemployment_rate	double	Source column from the original resource.	15.389698760145947
lu2_combined_rate_of_unemployment_and_time_related_under	double	Source column from the original resource.	43.80442137631591
lu3_combined_rate_of_unemployment_and_potential_labour_f	double	Source column from the original resource.	46.75156182477982
lu4_composite_measure_of_labour_underutilization	double	Source column from the original resource.	64.63401323225062
median_monthly_earnings_at_main_job	double	Source column from the original resource.	18200.0
neet_rate_youth_not_in_employment_nor_currently_in_educa	double	Source column from the original resource.	42.03589152868624
out_of_labour_force	double	Source column from the original resource.	2101980.4937515864
out_of_labour_force_inactivity_rate	double	Source column from the original resource.	55.824201895108416
potential_labour_force	double	Source column from the original resource.	979682.9353422734
time_related_underemployed	double	Source column from the original resource.	472643.8203130225
time_related_underemployment_rate	double	Source column from the original resource.	33.58305336323014
unemployed	double	Source column from the original resource.	255988.6335586697
working_age_population16_years	double	Source column from the original resource.	3765357.000000027
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset or package title.	Labour Force Indicators by Sex
source_resource	string	Source resource title, table name, or file name.	labour_force_by_sex
source_package_id	string	Source package identifier.	9fe40738-0ac6-4ac0-983f-0f76ba831580
source_resource_id	string	Source resource identifier.	9fe40738-0ac6-4ac0-983f-0f76ba831580
source_url	string	Original source URL or download URL.	https://api.data.gov.rw/api/v1/datasets/public/9fe40738-0ac6-4ac0-983...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-18T11:48:51Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-labour-force-indicators-by-sex-e4cc6c46")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

print(df.info())
print(df.head())

Filter By Geography

if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "RWA"]

Time-Series Pattern

if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())

Data Quality Notes

• Canonical time field: year.
• Missing values are preserved rather than silently imputed.
• Column names are standardized for machine use; source meanings are preserved where known.
• Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

Source And Provenance

• Source: Rwanda Data Sharing Platform - NISR
• Publisher: NISR
• Portal: https://data.gov.rw/
• Resource: labour_force_by_sex
• License: CC BY 4.0
• Retrieved/generated: 2026-07-18T13:10:40Z
• Hugging Face repo: electricsheepafrica/africa-rwanda-labour-force-indicators-by-sex-e4cc6c46

Transformations Applied

• Converted the source table to Parquet for efficient analytics and ML workflows.
• Added or preserved source provenance columns where available.
• Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
• Preserved source-reported values without analytical imputation.

Suggested Analyses

• Track workforce composition over time
• Compare employment patterns across groups
• Join with education, population, and sector data
• Build time-series views and period-over-period comparisons
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_rwanda_labour_force_indicators_by_sex_e4cc6c46_2025,
  title        = {Labour Force Indicators by Sex | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2025},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/9fe40738-0ac6-4ac0-983f-0f76ba831580},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-labour-force-indicators-by-sex-e4cc6c46}}
}

License

Released under CC BY 4.0.

Original data is published by NISR. Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.

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Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://api.data.gov.rw/api/v1/datasets/public/9fe40738-0ac6-4ac0-983f-0f76ba831580