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electricsheepafrica
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africa-mauritius-budget-data-2016-2017-ministry-of-labour-industrial-relati-5c816a55

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Tabular Regression
Time Series Forecasting
Modalities:
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tabular
csv
africa
mauritius
official-statistics
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africa-mauritius-budget-data-2016-2017-ministry-of-labour-industrial-relati-5c816a55 / README.md
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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: >-
  Budget Data 2016- 2017 -Ministry of Labour, Industrial Relations, Employment
  and Training | Africa (Mauritius official open data)

Budget Data 2016- 2017 -Ministry of Labour, Industrial Relations, Employment and Training | Africa (Mauritius official open data)

720 rows - 1 Africa country - 2015-2018 - 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 720 2015 2018 Mauritius

Indicators or Resource Contents

  • budget-data-2016-2017-ministry-of-labour-industrial-relations-employment-f9757d8e - Budget Data 2016- 2017 -Ministry of Labour, Industrial Relations, Employment and Training - itemno
  • budget-data-2016-2017-ministry-of-labour-industrial-relations-employment-8e4c798d - Budget Data 2016- 2017 -Ministry of Labour, Industrial Relations, Employment and Training - endfinancialyear
  • budget-data-2016-2017-ministry-of-labour-industrial-relations-employment-0dd6febb - Budget Data 2016- 2017 -Ministry of Labour, Industrial Relations, Employment and Training - amount

Schema

Column Type Description Example
indicator_id object Stable indicator identifier. budget-data-2016-2017-ministry-of-labour-industrial-relations-employment
indicator_name object Human-readable indicator name. Budget Data 2016- 2017 -Ministry of Labour, Industrial Relations, Employ
country_iso3 object ISO3 country code. MUS
country_name object Country name. Mauritius
year Int64 Observation year. 2015
value float64 Numeric observation value. 21110.0
unit object Measurement unit, when available. source_units_unspecified
dimension_head string Source dimension. Ministry of Labour Industrial Relations Employment and Training
dimension_subhead string Source dimension. GENERAL
dimension_expensetype string Source dimension. Recurrent Expenditure
dimension_category string Source dimension. Compensation of Employees
dimension_subcategory string Source dimension. Personal Emoluments
dimension_financialstatus string Source dimension. Provisional Actual
source_provider object Publishing organization. MDPA
source_dataset object Source package title. Budget Data 2016- 2017 -Ministry of Labour, Industrial Relations, Employ
source_resource object Source resource title. Budget-MLIRET-2016_17_1.csv
source_package_id object CKAN package UUID. 89b530a8-a48b-4fd2-b5f2-f9c69918530e
source_resource_id object CKAN resource UUID. c14d4907-75d7-44e8-98a9-99b76376a83e
source_url object Original CSV URL. https://data.govmu.org/dataset/89b530a8-a48b-4fd2-b5f2-f9c69918530e/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-budget-data-2016-2017-ministry-of-labour-industrial-relati-5c816a55")
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_budget_data_2016_2017_ministry_of_labour_industrial_relati_5c81_2018,
  title        = {Budget Data 2016- 2017 -Ministry of Labour, Industrial Relations, Employment and Training | Africa (Mauritius official open data)},
  author       = {MDPA},
  year         = {2018},
  url          = {https://data.govmu.org/dataset/budget-data-2016-2017-ministry-labour-industrial-relations-employment-and-training},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-budget-data-2016-2017-ministry-of-labour-industrial-relati-5c816a55}}
}

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/89b530a8-a48b-4fd2-b5f2-f9c69918530e/resource/c14d4907-75d7-44e8-98a9-99b76376a83e/download/budget-mliret-2016_17_1.csv