electricsheepafrica/africa-mauritius-foreign-workers-employed-in-large-establishments-by-indust-c5b549c0

Foreign Workers Employed in Large Establishments by Indust | Africa (MDPA)

24 rows - 1 Africa country/area - 2010 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 24 rows from MDPA, covering Foreign Workers Employed in Large Establishments by Indust. 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: Dataset shows the Foreign workers employed in large establishments by industrial group and sex 2010 - 2024

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	24
Countries/areas	1
First period	2010
Last period	2010
Indicators	0
Columns	62
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
MU	24	2010	2010	Mauritius

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.	8b35352b-e7dd-4986-9642-2f13efad777b:sheet1:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	MU
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	Mauritius
source_sheet	string	Source column from the original resource.	Sheet1
year	int64	Observation year.	2010
manufacturing	string	Source column from the original resource.	of which food (excluding sugar)
d_9880	double	Source column from the original resource.	299.0
d_8294	double	Source column from the original resource.	940.0
d_18174	double	Source column from the original resource.	1239.0
d_9791	double	Source column from the original resource.	446.0
d_9109	double	Source column from the original resource.	1071.0
d_18900	double	Source column from the original resource.	1517.0
d_10328	double	Source column from the original resource.	565.0
d_8746	double	Source column from the original resource.	1197.0
d_19074	double	Source column from the original resource.	1762.0
d_12663	double	Source column from the original resource.	641.0
d_9208	double	Source column from the original resource.	1234.0
d_21871	double	Source column from the original resource.	1875.0
d_14317	double	Source column from the original resource.	758.0
d_9210	double	Source column from the original resource.	1306.0
d_23527	double	Source column from the original resource.	2064.0
d_14999	double	Source column from the original resource.	812.0
d_9324	double	Source column from the original resource.	1357.0
d_24323	double	Source column from the original resource.	2169.0
d_15481	double	Source column from the original resource.	787.0
d_8569	double	Source column from the original resource.	1242.0
d_24050	double	Source column from the original resource.	2029.0
d_15610	double	Source column from the original resource.	827.0
d_8133	double	Source column from the original resource.	1311.0
d_23743	double	Source column from the original resource.	2138.0
d_16742	double	Source column from the original resource.	915.0
d_7501	double	Source column from the original resource.	1363.0
d_24243	double	Source column from the original resource.	2278.0
d_17293	double	Source column from the original resource.	994.0
d_5627	double	Source column from the original resource.	1343.0
d_22920	double	Source column from the original resource.	2337.0
d_16311	double	Source column from the original resource.	1105.0
d_5989	double	Source column from the original resource.	1392.0
d_22300	double	Source column from the original resource.	2497.0
d_14196	double	Source column from the original resource.	1019.0
d_5055	double	Source column from the original resource.	1323.0
d_19251	double	Source column from the original resource.	2342.0
d_12484	double	Source column from the original resource.	877.0
d_4433	double	Source column from the original resource.	1144.0
d_16917	double	Source column from the original resource.	2021.0
d_13039	double	Source column from the original resource.	1022.0
d_4589	double	Source column from the original resource.	1292.0
d_17628	double	Source column from the original resource.	2314.0
d_12392	double	Source column from the original resource.	1192.0
d_4062	double	Source column from the original resource.	1298.0
d_16454	double	Source column from the original resource.	2490.0
source_period_start_year	int64	Start year inferred from source metadata.	2010
source_period_end_year	int64	End year inferred from source metadata.	2010
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2010
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	MDPA
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Foreign workers employed in large establishments by industrial group ...
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Source file: foreign-workers-employed-in-large-establishments-by-indu...
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	8342686b-a136-45f8-8a64-e8a7c1792428
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	8b35352b-e7dd-4986-9642-2f13efad777b
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/8342686b-a136-45f8-8a64-e8a7c1792428/r...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	CC-BY-SA-4.0
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-08T16:26:20Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-foreign-workers-employed-in-large-establishments-by-indust-c5b549c0")
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"] == "MU"]

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: MDPA
• Publisher: MDPA
• Portal: https://data.govmu.org
• Resource: Source file: foreign-workers-employed-in-large-establishments-by-industrial-group-and-sex
• License: CC BY-SA 4.0
• Retrieved/generated: 2026-08-08T16:27:08Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-foreign-workers-employed-in-large-establishments-by-indust-c5b549c0

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_mauritius_foreign_workers_employed_in_large_establishments_by_indust_c5b5_2010,
  title        = {Foreign Workers Employed in Large Establishments by Indust | Africa (MDPA)},
  author       = {MDPA},
  year         = {2010},
  url          = {https://data.govmu.org/dataset/foreign-workers-employed-large-establishments-industrial-group-and-sex},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-foreign-workers-employed-in-large-establishments-by-indust-c5b549c0}}
}

License

Released under CC BY-SA 4.0.

Original data is published by MDPA. 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 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/foreign-workers-employed-large-establishments-industrial-group-and-sex