country_name stringclasses 1
value | country_iso3 stringclasses 1
value | year int64 1.96k 2.03k | indicator_name stringclasses 158
values | indicator_code stringclasses 158
values | value float64 0.01 253k | esa_source stringclasses 1
value | esa_processed stringdate 2026-04-12 00:00:00 2026-04-12 00:00:00 |
|---|---|---|---|---|---|---|---|
Mauritius | MUS | 1,972 | School enrollment, primary (gross), gender parity index (GPI) | SE.ENR.PRIM.FM.ZS | 0.99419 | HDX | 2026-04-12 |
Mauritius | MUS | 1,989 | School life expectancy, primary to tertiary, male (years) | SE.SCH.LIFE.MA | 10.40028 | HDX | 2026-04-12 |
Mauritius | MUS | 1,991 | Own-account workers, male (% of male employment) (modeled ILO estimate) | SL.EMP.OWAC.MA.ZS | 15.958 | HDX | 2026-04-12 |
Mauritius | MUS | 1,998 | School enrollment, secondary, male (% net) | SE.SEC.NENR.MA | 63.5868 | HDX | 2026-04-12 |
Mauritius | MUS | 2,014 | Age population, age 04, female | SP.POP.AG04.FE.IN | 7,341 | HDX | 2026-04-12 |
Mauritius | MUS | 1,987 | Prevalence of obesity, female (% of female population ages 18+) | SH.STA.OB18.FE.ZS | 6.7 | HDX | 2026-04-12 |
Mauritius | MUS | 1,994 | Labor force, female | SL.TLF.TOTL.FE.IN | 152,573 | HDX | 2026-04-12 |
Mauritius | MUS | 1,962 | Age population, age 02, male | SP.POP.AG02.MA.IN | 11,930 | HDX | 2026-04-12 |
Mauritius | MUS | 2,018 | Educational attainment, at least completed upper secondary, population 25+, male (%) (cumulative) | SE.SEC.CUAT.UP.MA.ZS | 52.982895 | HDX | 2026-04-12 |
Mauritius | MUS | 2,013 | Children out of school, primary, male | SE.PRM.UNER.MA | 3,825 | HDX | 2026-04-12 |
Mauritius | MUS | 2,014 | Employment to population ratio, 15+, male (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.MA.ZS | 70.665 | HDX | 2026-04-12 |
Mauritius | MUS | 2,000 | Persistence to grade 5, female (% of cohort) | SE.PRM.PRS5.FE.ZS | 98.436378 | HDX | 2026-04-12 |
Mauritius | MUS | 2,010 | Age population, age 01, female | SP.POP.AG01.FE.IN | 7,580.5 | HDX | 2026-04-12 |
Mauritius | MUS | 1,978 | Age population, age 00, male | SP.POP.AG00.MA.IN | 11,417 | HDX | 2026-04-12 |
Mauritius | MUS | 2,019 | Persistence to grade 5, female (% of cohort) | SE.PRM.PRS5.FE.ZS | 98.085426 | HDX | 2026-04-12 |
Mauritius | MUS | 1,971 | Age population, age 03, female | SP.POP.AG03.FE.IN | 10,833 | HDX | 2026-04-12 |
Mauritius | MUS | 1,979 | Prevalence of obesity, female (% of female population ages 18+) | SH.STA.OB18.FE.ZS | 5.3 | HDX | 2026-04-12 |
Mauritius | MUS | 1,971 | Age population, age 04, female | SP.POP.AG04.FE.IN | 11,211.5 | HDX | 2026-04-12 |
Mauritius | MUS | 1,981 | Age population, age 02, male | SP.POP.AG02.MA.IN | 11,837.5 | HDX | 2026-04-12 |
Mauritius | MUS | 1,980 | Age population, age 00, female | SP.POP.AG00.FE.IN | 11,290.5 | HDX | 2026-04-12 |
Mauritius | MUS | 2,021 | Age population, age 05, male | SP.POP.AG05.MA.IN | 6,138.5 | HDX | 2026-04-12 |
Mauritius | MUS | 1,963 | Age population, age 05, male | SP.POP.AG05.MA.IN | 11,846 | HDX | 2026-04-12 |
Mauritius | MUS | 2,001 | Employment in industry, female (% of female employment) (modeled ILO estimate) | SL.IND.EMPL.FE.ZS | 33.497581 | HDX | 2026-04-12 |
Mauritius | MUS | 2,005 | Labor force, female (% of total labor force) | SL.TLF.TOTL.FE.ZS | 34.570017 | HDX | 2026-04-12 |
Mauritius | MUS | 1,961 | Age population, age 02, male | SP.POP.AG02.MA.IN | 11,892.5 | HDX | 2026-04-12 |
Mauritius | MUS | 1,993 | Employers, male (% of male employment) (modeled ILO estimate) | SL.EMP.MPYR.MA.ZS | 0.716232 | HDX | 2026-04-12 |
Mauritius | MUS | 2,010 | Educational attainment, at least completed short-cycle tertiary, population 25+, female (%) (cumulative) | SE.TER.CUAT.ST.FE.ZS | 3.957236 | HDX | 2026-04-12 |
Mauritius | MUS | 2,021 | Mortality rate, adult, female (per 1,000 female adults) | SP.DYN.AMRT.FE | 113.512 | HDX | 2026-04-12 |
Mauritius | MUS | 2,001 | Repeaters, primary, female (% of female enrollment) | SE.PRM.REPT.FE.ZS | 3.6824 | HDX | 2026-04-12 |
Mauritius | MUS | 2,000 | Employers, female (% of female employment) (modeled ILO estimate) | SL.EMP.MPYR.FE.ZS | 0.674686 | HDX | 2026-04-12 |
Mauritius | MUS | 2,017 | Employment to population ratio, 15+, female (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.FE.ZS | 41.086 | HDX | 2026-04-12 |
Mauritius | MUS | 1,986 | Age population, age 02, female | SP.POP.AG02.FE.IN | 10,119 | HDX | 2026-04-12 |
Mauritius | MUS | 1,993 | Employment in services, male (% of male employment) (modeled ILO estimate) | SL.SRV.EMPL.MA.ZS | 48.906254 | HDX | 2026-04-12 |
Mauritius | MUS | 2,006 | Age population, age 03, female | SP.POP.AG03.FE.IN | 9,252 | HDX | 2026-04-12 |
Mauritius | MUS | 2,002 | School life expectancy, primary to tertiary, female (years) | SE.SCH.LIFE.FE | 12.5436 | HDX | 2026-04-12 |
Mauritius | MUS | 2,017 | Employers, male (% of male employment) (modeled ILO estimate) | SL.EMP.MPYR.MA.ZS | 2.450308 | HDX | 2026-04-12 |
Mauritius | MUS | 2,004 | School enrollment, primary, male (% gross) | SE.PRM.ENRR.MA | 102.635674 | HDX | 2026-04-12 |
Mauritius | MUS | 2,010 | Prevalence of obesity, male (% of male population ages 18+) | SH.STA.OB18.MA.ZS | 4.6 | HDX | 2026-04-12 |
Mauritius | MUS | 2,024 | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS | 7.466 | HDX | 2026-04-12 |
Mauritius | MUS | 2,002 | Age population, age 04, female | SP.POP.AG04.FE.IN | 9,498 | HDX | 2026-04-12 |
Mauritius | MUS | 2,025 | Employment in services, female (% of female employment) (modeled ILO estimate) | SL.SRV.EMPL.FE.ZS | 85.549155 | HDX | 2026-04-12 |
Mauritius | MUS | 2,007 | Repeaters, primary, male (% of male enrollment) | SE.PRM.REPT.MA.ZS | 4.38812 | HDX | 2026-04-12 |
Mauritius | MUS | 2,001 | Net intake rate in grade 1, male (% of official school-age population) | SE.PRM.NINT.MA.ZS | 60.47501 | HDX | 2026-04-12 |
Mauritius | MUS | 2,011 | Employers, female (% of female employment) (modeled ILO estimate) | SL.EMP.MPYR.FE.ZS | 1.478384 | HDX | 2026-04-12 |
Mauritius | MUS | 2,010 | Lifetime risk of maternal death (1 in: rate varies by country) | SH.MMR.RISK | 1,438 | HDX | 2026-04-12 |
Mauritius | MUS | 1,995 | Employment in agriculture, male (% of male employment) (modeled ILO estimate) | SL.AGR.EMPL.MA.ZS | 16.409721 | HDX | 2026-04-12 |
Mauritius | MUS | 1,976 | Secondary education, vocational pupils (% female) | SE.SEC.ENRL.VO.FE.ZS | 43.47319 | HDX | 2026-04-12 |
Mauritius | MUS | 2,016 | Primary education, teachers (% female) | SE.PRM.TCHR.FE.ZS | 76.463058 | HDX | 2026-04-12 |
Mauritius | MUS | 1,997 | Repeaters, primary, female (% of female enrollment) | SE.PRM.REPT.FE.ZS | 3.8678 | HDX | 2026-04-12 |
Mauritius | MUS | 1,997 | Adolescent fertility rate (births per 1,000 women ages 15-19) | SP.ADO.TFRT | 36.77 | HDX | 2026-04-12 |
Mauritius | MUS | 1,994 | Women Business and the Law Index Score (scale 1-100) | SG.LAW.INDX | 60.625 | HDX | 2026-04-12 |
Mauritius | MUS | 2,016 | Life expectancy at age 60, male (years) | SP.DYN.LE60.MA.IN | 18.8389 | HDX | 2026-04-12 |
Mauritius | MUS | 2,014 | Labor force participation rate, male (% of male population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.MA.ZS | 74.693 | HDX | 2026-04-12 |
Mauritius | MUS | 2,015 | School enrollment, preprimary, male (% gross) | SE.PRE.ENRR.MA | 104.256943 | HDX | 2026-04-12 |
Mauritius | MUS | 1,976 | Adjusted net enrollment rate, primary, female (% of primary school age children) | SE.PRM.TENR.FE | 79.30351 | HDX | 2026-04-12 |
Mauritius | MUS | 2,010 | Prevalence of current tobacco use, females (% of female adults) | SH.PRV.SMOK.FE | 3.8 | HDX | 2026-04-12 |
Mauritius | MUS | 1,997 | Gross intake ratio in first grade of primary education, male (% of relevant age group) | SE.PRM.GINT.MA.ZS | 103.25142 | HDX | 2026-04-12 |
Mauritius | MUS | 2,004 | Women Business and the Law Index Score (scale 1-100) | SG.LAW.INDX | 69.375 | HDX | 2026-04-12 |
Mauritius | MUS | 2,004 | Progression to secondary school, male (%) | SE.SEC.PROG.MA.ZS | 78.38869 | HDX | 2026-04-12 |
Mauritius | MUS | 2,015 | Employers, male (% of male employment) (modeled ILO estimate) | SL.EMP.MPYR.MA.ZS | 1.987393 | HDX | 2026-04-12 |
Mauritius | MUS | 1,989 | School enrollment, primary (gross), gender parity index (GPI) | SE.ENR.PRIM.FM.ZS | 1.00598 | HDX | 2026-04-12 |
Mauritius | MUS | 2,023 | Educational attainment, Doctoral or equivalent, population 25+, total (%) (cumulative) | SE.TER.CUAT.DO.ZS | 0.302421 | HDX | 2026-04-12 |
Mauritius | MUS | 2,006 | Age population, age 04, male | SP.POP.AG04.MA.IN | 9,597.5 | HDX | 2026-04-12 |
Mauritius | MUS | 2,019 | School enrollment, primary (gross), gender parity index (GPI) | SE.ENR.PRIM.FM.ZS | 1.02579 | HDX | 2026-04-12 |
Mauritius | MUS | 1,970 | Mortality rate, adult, female (per 1,000 female adults) | SP.DYN.AMRT.FE | 185.381 | HDX | 2026-04-12 |
Mauritius | MUS | 2,014 | Age population, age 04, male | SP.POP.AG04.MA.IN | 7,430 | HDX | 2026-04-12 |
Mauritius | MUS | 2,013 | Mortality rate, adult, female (per 1,000 female adults) | SP.DYN.AMRT.FE | 95.58 | HDX | 2026-04-12 |
Mauritius | MUS | 1,982 | Age population, age 03, female | SP.POP.AG03.FE.IN | 11,267 | HDX | 2026-04-12 |
Mauritius | MUS | 2,009 | Net intake rate in grade 1, male (% of official school-age population) | SE.PRM.NINT.MA.ZS | 82.79805 | HDX | 2026-04-12 |
Mauritius | MUS | 1,992 | Survival to age 65, male (% of cohort) | SP.DYN.TO65.MA.ZS | 62.602867 | HDX | 2026-04-12 |
Mauritius | MUS | 2,011 | School life expectancy, primary to tertiary, male (years) | SE.SCH.LIFE.MA | 13.898 | HDX | 2026-04-12 |
Mauritius | MUS | 1,994 | Employment to population ratio, ages 15-24, male (%) (modeled ILO estimate) | SL.EMP.1524.SP.MA.ZS | 52.063 | HDX | 2026-04-12 |
Mauritius | MUS | 2,006 | Educational attainment, at least Bachelor's or equivalent, population 25+, male (%) (cumulative) | SE.TER.CUAT.BA.MA.ZS | 0.974228 | HDX | 2026-04-12 |
Mauritius | MUS | 2,014 | Gross intake ratio in first grade of primary education, male (% of relevant age group) | SE.PRM.GINT.MA.ZS | 101.53885 | HDX | 2026-04-12 |
Mauritius | MUS | 2,006 | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS | 15.673 | HDX | 2026-04-12 |
Mauritius | MUS | 2,021 | Employment to population ratio, ages 15-24, female (%) (modeled ILO estimate) | SL.EMP.1524.SP.FE.ZS | 18.553 | HDX | 2026-04-12 |
Mauritius | MUS | 1,994 | Employment in agriculture, male (% of male employment) (modeled ILO estimate) | SL.AGR.EMPL.MA.ZS | 16.802087 | HDX | 2026-04-12 |
Mauritius | MUS | 1,975 | Age population, age 04, female | SP.POP.AG04.FE.IN | 9,705.5 | HDX | 2026-04-12 |
Mauritius | MUS | 2,000 | Employment in industry, male (% of male employment) (modeled ILO estimate) | SL.IND.EMPL.MA.ZS | 33.241338 | HDX | 2026-04-12 |
Mauritius | MUS | 1,977 | Secondary education, vocational pupils (% female) | SE.SEC.ENRL.VO.FE.ZS | 42.93746 | HDX | 2026-04-12 |
Mauritius | MUS | 1,982 | Age population, age 04, male | SP.POP.AG04.MA.IN | 11,670 | HDX | 2026-04-12 |
Mauritius | MUS | 2,020 | Proportion of seats held by women in national parliaments (%) | SG.GEN.PARL.ZS | 20 | HDX | 2026-04-12 |
Mauritius | MUS | 2,006 | Persistence to grade 5, female (% of cohort) | SE.PRM.PRS5.FE.ZS | 98.387917 | HDX | 2026-04-12 |
Mauritius | MUS | 2,012 | Self-employed, female (% of female employment) (modeled ILO estimate) | SL.EMP.SELF.FE.ZS | 20.775361 | HDX | 2026-04-12 |
Mauritius | MUS | 2,016 | Vulnerable employment, male (% of male employment) (modeled ILO estimate) | SL.EMP.VULN.MA.ZS | 17.624646 | HDX | 2026-04-12 |
Mauritius | MUS | 1,991 | Progression to secondary school, female (%) | SE.SEC.PROG.FE.ZS | 69.51928 | HDX | 2026-04-12 |
Mauritius | MUS | 2,004 | Employment in industry, male (% of male employment) (modeled ILO estimate) | SL.IND.EMPL.MA.ZS | 33.33869 | HDX | 2026-04-12 |
Mauritius | MUS | 2,001 | Lifetime risk of maternal death (1 in: rate varies by country) | SH.MMR.RISK | 1,320 | HDX | 2026-04-12 |
Mauritius | MUS | 2,018 | Life expectancy at birth, female (years) | SP.DYN.LE00.FE.IN | 77.72 | HDX | 2026-04-12 |
Mauritius | MUS | 2,018 | Primary education, teachers (% female) | SE.PRM.TCHR.FE.ZS | 78.948319 | HDX | 2026-04-12 |
Mauritius | MUS | 2,015 | Employment in industry, female (% of female employment) (modeled ILO estimate) | SL.IND.EMPL.FE.ZS | 17.531664 | HDX | 2026-04-12 |
Mauritius | MUS | 2,000 | Educational attainment, at least completed lower secondary, population 25+, male (%) (cumulative) | SE.SEC.CUAT.LO.MA.ZS | 44.950001 | HDX | 2026-04-12 |
Mauritius | MUS | 2,001 | Prevalence of obesity, male (% of male population ages 18+) | SH.STA.OB18.MA.ZS | 3.4 | HDX | 2026-04-12 |
Mauritius | MUS | 2,000 | Educational attainment, at least completed primary, population 25+ years, total (%) (cumulative) | SE.PRM.CUAT.ZS | 49.169998 | HDX | 2026-04-12 |
Mauritius | MUS | 2,008 | Employment in industry, male (% of male employment) (modeled ILO estimate) | SL.IND.EMPL.MA.ZS | 34.098545 | HDX | 2026-04-12 |
Mauritius | MUS | 1,976 | Age population, age 03, female | SP.POP.AG03.FE.IN | 9,551 | HDX | 2026-04-12 |
Mauritius | MUS | 2,003 | School enrollment, secondary, male (% gross) | SE.SEC.ENRR.MA | 85.770798 | HDX | 2026-04-12 |
Mauritius | MUS | 1,989 | School life expectancy, primary to tertiary, female (years) | SE.SCH.LIFE.FE | 10.31143 | HDX | 2026-04-12 |
Mauritius | MUS | 2,006 | Prevalence of obesity, female (% of female population ages 18+) | SH.STA.OB18.FE.ZS | 11.9 | HDX | 2026-04-12 |
Mauritius | MUS | 2,021 | Prevalence of current tobacco use, males (% of male adults) | SH.PRV.SMOK.MA | 39.1 | HDX | 2026-04-12 |
Mauritius - Gender | Africa (original)
Size category: 1K<n<10K - Formats: parquet - Sector: economics_finance - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
Dataset context from the existing Hugging Face card: Mauritius - Gender Publisher: World Bank Group · Source: HDX · License: cc-by · Updated: 2026-03-27 Abstract Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Gender equality is a core development objective in its own right. It is also smart development policy and sound business practice. It is integral to economic growth, business growth and good development outcomes. Gender equality can boost productivity, enhance… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-world-bank-gender-indicators-for-mauritius.
Dataset Profile
| Field | Value |
|---|---|
| Hugging Face repo | electricsheepafrica/africa-world-bank-gender-indicators-for-mauritius |
| Sector | economics_finance |
| Topic tags | humanitarian, hdx, electric-sheep-africa, gender, indicators, mus |
| Modalities | tabular, text |
| Formats | parquet |
| Size category | 1K<n<10K |
| Countries | Mauritius |
| ISO3 coverage | MUS |
| Last modified on HF | 2026-04-12 03:37:49+00:00 |
| Inventory snapshot | 2026-07-16T16:00:34Z |
How To Read This Dataset
- Start from the repository files and the dataset viewer when available.
- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
- Preserve missing values until you have a defensible imputation rule.
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-world-bank-gender-indicators-for-mauritius")
print(ds)
split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])
Convert To Pandas When Tabular
from datasets import Dataset
first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
df = first_split.to_pandas()
print(df.head())
Data Quality Notes
- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
- Exact schema, row counts, and source files should be inspected in the repository data files.
- Metadata gaps from the inventory: upstream_publisher.
- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
Source And Provenance
- Source context: original
- Publisher/source attribution: original
- License: CC BY 4.0
- Hugging Face URL: https://huggingface.co/datasets/electricsheepafrica/africa-world-bank-gender-indicators-for-mauritius
- Inventory retrieved at:
2026-07-16T16:00:34Z
Suggested Analyses
- Inspect schema and missingness before modeling.
- Profile variables by geography, time, and subgroup columns where present.
- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
Citation
@misc{electric_sheep_africa_africa_world_bank_gender_indicators_for_mauritius_2026,
title = {Mauritius - Gender | Africa (original)},
author = {original},
year = {2026},
url = {https://huggingface.co/datasets/electricsheepafrica/africa-world-bank-gender-indicators-for-mauritius},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-world-bank-gender-indicators-for-mauritius}}
}
License
Released under CC BY 4.0.
Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
About Electric Sheep Africa
Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.
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