electricsheepafrica/africa-mauritius-enrolment-by-school-course-level-faculty-gender-and-by-yea-e922edd0

Enrolment by School Course Level Faculty Gender and by Yea | Africa (MDPA)

104 rows - 1 Africa country/area - 2019-2022 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 104 rows from MDPA, covering Enrolment by School Course Level Faculty Gender and by Yea. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Education datasets help analysts study access, participation, learning systems, infrastructure, and outcomes across places and periods.

Source-provided context: Dataset Shows the Number of Participant Enrolled by Schools, Course Level, Faculty, Gender and by Year for University of Technology for the Year 2019 to 2022

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: not detected.
• Time coverage basis: source metadata.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	104
Countries/areas	1
First period	2019
Last period	2022
Indicators	0
Columns	61
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
MU	104	2019	2022	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.	22eb8523-bb79-4e48-9ab1-681609ffbf6d:2019-2020:0
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.	2019-2020
degree	string	Source column from the original resource.	Diploma
d_202	double	Source column from the original resource.	1.0
d_307	double	Source column from the original resource.	0.0
d_509	double	Source column from the original resource.	1.0
d_75	double	Source column from the original resource.	0.0
d_117	double	Source column from the original resource.	0.0
d_192	double	Source column from the original resource.	0.0
d_93	double	Source column from the original resource.	7.0
d_149	double	Source column from the original resource.	29.0
d_242	double	Source column from the original resource.	36.0
d_30	double	Source column from the original resource.	0.0
d_38	double	Source column from the original resource.	0.0
d_68	double	Source column from the original resource.	0.0
d_400	double	Source column from the original resource.	8.0
d_611	double	Source column from the original resource.	29.0
d_1011	double	Source column from the original resource.	37.0
source_period_start_year	int64	Start year inferred from source metadata.	2019
source_period_end_year	int64	End year inferred from source metadata.	2022
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2019-2022
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.	Enrolment by School, Course Level, Faculty, Gender and by Year for Un...
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Source-File_41.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	c52217d2-3b21-4d74-a288-01c907ac4854
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	22eb8523-bb79-4e48-9ab1-681609ffbf6d
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/c52217d2-3b21-4d74-a288-01c907ac4854/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
d_162	double	Source column from the original resource.	``
d_382	double	Source column from the original resource.	``
d_544	double	Source column from the original resource.	``
d_186	double	Source column from the original resource.	``
d_265	double	Source column from the original resource.	``
d_451	double	Source column from the original resource.	``
d_89	double	Source column from the original resource.	``
d_165	double	Source column from the original resource.	``
d_254	double	Source column from the original resource.	``
d_6	double	Source column from the original resource.	``
d_8	double	Source column from the original resource.	``
d_14	double	Source column from the original resource.	``
d_443	double	Source column from the original resource.	``
d_820	double	Source column from the original resource.	``
d_1263	double	Source column from the original resource.	``
d_200	double	Source column from the original resource.	``
d_361	double	Source column from the original resource.	``
d_561	double	Source column from the original resource.	``
d_150	double	Source column from the original resource.	``
d_351	double	Source column from the original resource.	``
d_501	double	Source column from the original resource.	``
d_158	double	Source column from the original resource.	``
d_255	double	Source column from the original resource.	``
d_413	double	Source column from the original resource.	``
d_0	double	Source column from the original resource.	``
d_0_2	double	Source column from the original resource.	``
d_0_3	double	Source column from the original resource.	``
d_508	double	Source column from the original resource.	``
d_967	double	Source column from the original resource.	``
d_1475	double	Source column from the original resource.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-enrolment-by-school-course-level-faculty-gender-and-by-yea-e922edd0")
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

• No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
• 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_41.xlsx
• License: CC BY-SA 4.0
• Retrieved/generated: 2026-08-08T16:37:19Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-enrolment-by-school-course-level-faculty-gender-and-by-yea-e922edd0

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

• Compare education indicators by geography
• Track participation or completion trends
• Join with population and poverty indicators
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_mauritius_enrolment_by_school_course_level_faculty_gender_and_by_yea_e922_2022,
  title        = {Enrolment by School Course Level Faculty Gender and by Yea | Africa (MDPA)},
  author       = {MDPA},
  year         = {2022},
  url          = {https://data.govmu.org/dataset/enrolment-school-course-level-faculty-gender-and-year-university-technology},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-enrolment-by-school-course-level-faculty-gender-and-by-yea-e922edd0}}
}

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/enrolment-school-course-level-faculty-gender-and-year-university-technology