electricsheepafrica/africa-mauritius-gross-tertiary-enrolment-rate-gter-in-tertiary-education-b-fa6715f1
Gross Tertiary Enrolment Rate Gter in Tertiary Education B | Africa (MDPA) 59 rows - 1 Africa country/area - 2000-2014 - 4 indicators - Engineered by Electric Sheep Africa TL;DR This dataset contains 59 rows from MDPA, covering Gross Tertiary Enrolment Rate Gter in Tertiary Education B. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-gross-tertiary-enrolment-rate-gter-in-tertiary-education-b-fa6715f1.
Gross Tertiary Enrolment Rate Gter in Tertiary Education B | Africa (MDPA)
59 rows - 1 Africa country/area - 2000-2014 - 4 indicators - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
TL;DR
This dataset contains 59 rows from MDPA, covering Gross Tertiary Enrolment Rate Gter in Tertiary Education B. 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: Gross Tertiary Enrolment Rate (GTER) in Tertiary Education by sex, 2000 - 2015
How To Read This Dataset
- One row means: one indicator observation for one geography, time period, and optional source dimensions.
- Primary geography column:
country_iso3. - Best time column:
year. - Time coverage basis: year.
- Recommended join keys:
country_iso3,year,indicator_id.
Coverage
Geographic Coverage
Top areas shown below, sorted by row count when available:
Indicators, Variables, Or Resource Contents
gross-tertiary-enrolment-rate-gter-in-tertiary-education-by-sex-2000-201-564d3069- Gross Tertiary Enrolment Rate (GTER) in Tertiary Education by sex, 2000 - 2015 - public funded institutions(sourceunitsunspecified)gross-tertiary-enrolment-rate-gter-in-tertiary-education-by-sex-2000-201-1f9bd21e- Gross Tertiary Enrolment Rate (GTER) in Tertiary Education by sex, 2000 - 2015 - private(sourceunitsunspecified)gross-tertiary-enrolment-rate-gter-in-tertiary-education-by-sex-2000-201-ea1bc9c7- Gross Tertiary Enrolment Rate (GTER) in Tertiary Education by sex, 2000 - 2015 - overseas(sourceunitsunspecified)gross-tertiary-enrolment-rate-gter-in-tertiary-education-by-sex-2000-201-dd2440a3- Gross Tertiary Enrolment Rate (GTER) in Tertiary Education by sex, 2000 - 2015 - total(sourceunitsunspecified)
Schema
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-mauritius-gross-tertiary-enrolment-rate-gter-in-tertiary-education-b-fa6715f1")
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: table1.xlsx
- License: CC BY-SA 4.0
- Retrieved/generated:
2026-08-08T16:30:05Z - Hugging Face repo: electricsheepafrica/africa-mauritius-gross-tertiary-enrolment-rate-gter-in-tertiary-education-b-fa6715f1
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
- Build time-series views and period-over-period comparisons
- Pivot to geography x period or indicator x period matrices
- Check missingness before modeling
- Use
country_iso3as the safest geography join key when present
Citation
@misc{electric_sheep_africa_africa_mauritius_gross_tertiary_enrolment_rate_gter_in_tertiary_education_b_fa67_2014,
title = {Gross Tertiary Enrolment Rate Gter in Tertiary Education B | Africa (MDPA)},
author = {MDPA},
year = {2014},
url = {https://data.govmu.org/dataset/gross-tertiary-enrolment-rate-gter-tertiary-education-sex-2000-2015},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-gross-tertiary-enrolment-rate-gter-in-tertiary-education-b-fa6715f1}}
}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.
Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/gross-tertiary-enrolment-rate-gter-tertiary-education-sex-2000-2015
