electricsheepafrica/africa-mauritius-higher-school-certificate-hsc-grade-distribution-by-subjec-4ae5f3dc

Higher School Certificate Hsc Grade Distribution by Subjec | Africa (MDPA)

422 rows - 1 Africa country/area - 2016-2019 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 422 rows from MDPA, covering Higher School Certificate Hsc Grade Distribution by Subjec. 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 number of students who took part (who were examined) in Higher School Certificate Examinations and the number of passes by Subject from year 2016 to 2019 at Principal Level

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	422
Countries/areas	1
First period	2016
Last period	2019
Indicators	0
Columns	51
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
MU	422	2016	2019	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.	9d068140-d6a7-45d6-a464-c5eac105a42f:introduction: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.	Introduction
introduction	string	Source column from the original resource.	This issue of Education statistics presents data on education, compil...
source_period_start_year	int64	Start year inferred from source metadata.	2016
source_period_end_year	int64	End year inferred from source metadata.	2019
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2016-2019
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.	Higher School Certificate (HSC) Grade Distribution by Subjects at Pri...
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	source-file-hsc-grade-distribution-by-subjects-at-principal-level-201...
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	aba17443-7b43-4613-9e88-d27db2c5f92e
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	9d068140-d6a7-45d6-a464-c5eac105a42f
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/aba17443-7b43-4613-9e88-d27db2c5f92e/r...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-by
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_1	double	Source column from the original resource.	``
expenditure_on_education	string	Source column from the original resource.	``
educational_institutions_by_zone_2017	string	Source column from the original resource.	``
french_mauritius	string	Source column from the original resource.	``
d_71	double	Source column from the original resource.	``
d_265	double	Source column from the original resource.	``
d_527	double	Source column from the original resource.	``
d_699	double	Source column from the original resource.	``
d_605	double	Source column from the original resource.	``
d_280	double	Source column from the original resource.	``
d_34	double	Source column from the original resource.	``
d_4	double	Source column from the original resource.	``
d_27	double	Source column from the original resource.	``
d_45	double	Source column from the original resource.	``
d_2558	double	Source column from the original resource.	``
d_111	double	Source column from the original resource.	``
d_2447	double	Source column from the original resource.	``
d_2481	double	Source column from the original resource.	``
d_77	double	Source column from the original resource.	``
accounting	string	Source column from the original resource.	``
d_3583	double	Source column from the original resource.	``
d_2547	double	Source column from the original resource.	``
d_71_08568238905944	double	Source column from the original resource.	``
d_694	double	Source column from the original resource.	``
d_1853	double	Source column from the original resource.	``
d_3525	double	Source column from the original resource.	``
d_2571	double	Source column from the original resource.	``
d_72_93617021276596	double	Source column from the original resource.	``
d_717	double	Source column from the original resource.	``
d_1854	double	Source column from the original resource.	``
d_3261	double	Source column from the original resource.	``
d_2396	double	Source column from the original resource.	``
d_73_47439435755904	double	Source column from the original resource.	``
d_506	double	Source column from the original resource.	``
d_1890	double	Source column from the original resource.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-higher-school-certificate-hsc-grade-distribution-by-subjec-4ae5f3dc")
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-hsc-grade-distribution-by-subjects-at-principal-level-2016-2019.xlsx
• License: CC BY 4.0
• Retrieved/generated: 2026-08-08T16:54:07Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-higher-school-certificate-hsc-grade-distribution-by-subjec-4ae5f3dc

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_higher_school_certificate_hsc_grade_distribution_by_subjec_4ae5_2019,
  title        = {Higher School Certificate Hsc Grade Distribution by Subjec | Africa (MDPA)},
  author       = {MDPA},
  year         = {2019},
  url          = {https://data.govmu.org/dataset/higher-school-certificate-hsc-grade-distribution-by-subjects-at-principal-level-for-year-2016-2019},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-higher-school-certificate-hsc-grade-distribution-by-subjec-4ae5f3dc}}
}

License

Released under CC BY 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/higher-school-certificate-hsc-grade-distribution-by-subjects-at-principal-level-for-year-2016-2019