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africa-mauritius-employment-in-large-establishments-by-major-industrial-gro-7ddfaee7

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Tabular Regression
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africa
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metadata 
license: cc-by-sa-4.0
language:
  - en
task_categories:
  - tabular-regression
  - time-series-forecasting
multilinguality: monolingual
size_categories:
  - n<1K
tags:
  - tabular
  - csv
  - africa
  - mauritius
  - official-statistics
  - open-data
pretty_name: >-
  Employment in Large Establishments by Major Industrial Group and by Gender |
  Africa (Mauritius official open data)

Employment in Large Establishments by Major Industrial Group and by Gender | Africa (Mauritius official open data)

864 rows - 1 Africa country - 2007-2022 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from Mauritius as ML-ready Parquet. The CSV is the provenance boundary; all usable indicators or tabular columns from the source file stay together in this repo.

About the source

Geographic coverage

1 Africa country:

Country Rows First year Last year Name
MUS 864 2007 2022 Mauritius

Indicators or Resource Contents

  • employment-in-large-establishments-by-major-industrial-group-and-by-gend-33ae075e - Employment in Large Establishments by Major Industrial Group and by Gender - no of male
  • employment-in-large-establishments-by-major-industrial-group-and-by-gend-1a2bd720 - Employment in Large Establishments by Major Industrial Group and by Gender - no of female

Schema

Column Type Description Example
indicator_id object Stable indicator identifier. employment-in-large-establishments-by-major-industrial-group-and-by-gend
indicator_name object Human-readable indicator name. Employment in Large Establishments by Major Industrial Group and by Gend
country_iso3 object ISO3 country code. MUS
country_name object Country name. Mauritius
year Int64 Observation year. 2007
value float64 Numeric observation value. 17711.0
unit object Measurement unit, when available. source_units_unspecified
dimension_industrial_group string Source dimension. Agriculture and Forestry and Fishing
dimension_category string Source dimension. ``
source_provider object Publishing organization. MDPA
source_dataset object Source package title. Employment in Large Establishments by Major Industrial Group and by Gend
source_resource object Source resource title. Employment-in-Large-Establishments-by-Major-Industrial-Group-and-by-Gend
source_package_id object CKAN package UUID. 4e0520bb-551a-4bed-bfea-48ec05031eb9
source_resource_id object CKAN resource UUID. 1a563147-aeee-4a24-af92-cfaa5050ec6b
source_url object Original CSV URL. https://data.govmu.org/dataset/4e0520bb-551a-4bed-bfea-48ec05031eb9/reso
license_id object Source license identifier. CC-BY-SA-4.0
retrieved_at object UTC retrieval timestamp. 2026-07-16T19:23:24Z

Usage 

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-employment-in-large-establishments-by-major-industrial-gro-7ddfaee7")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country 

sample_country = df[df["country_iso3"] == "MUS"]

Work with indicators 

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation 

@misc{electric_sheep_africa_africa_mauritius_employment_in_large_establishments_by_major_industrial_gro_7ddf_2022,
  title        = {Employment in Large Establishments by Major Industrial Group and by Gender | Africa (Mauritius official open data)},
  author       = {MDPA},
  year         = {2022},
  url          = {https://data.govmu.org/dataset/employment-large-establishments-major-industrial-group-and-gender},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-employment-in-large-establishments-by-major-industrial-gro-7ddfaee7}}
}

License

Released under CC BY-SA 4.0.

Original data (c) MDPA. 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 Hugging Face. 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 2026-07-16 via the Electric Sheep pipeline. Source URL: https://data.govmu.org/dataset/4e0520bb-551a-4bed-bfea-48ec05031eb9/resource/1a563147-aeee-4a24-af92-cfaa5050ec6b/download/employment-in-large-establishments-by-major-industrial-group-and-by-gender.csv