electricsheepafrica/africa-mauritius-budget-data-2016-2017-ministry-of-education-and-human-reso-621649fe

Budget Data 2016 2017 Ministry of Education and Human Reso | Africa (MDPA)

2,680 rows - 1 Africa country/area - 2015-2018 - 3 indicators - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 2,680 rows from MDPA, covering Budget Data 2016 2017 Ministry of Education and Human Reso. 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.

This dataset covers Budget Data 2016 2017 Ministry of Education and Human Reso from MDPA. Use the source and schema sections below to confirm definitions, units, and collection methodology before sensitive analytical use.

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

Dimension	Value
Rows	2,680
Countries/areas	1
First period	2015
Last period	2018
Indicators	3
Columns	30
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
MU	2,680	2015	2018	Mauritius

Indicators, Variables, Or Resource Contents

• budget-data-2016-2017-ministry-of-education-and-human-resources-tertiary-621649fe - Budget Data 2016-2017 - Ministry of Education and Human Resources, Tertiary and Scientific Research(source_units_unspecified)
• budget-data-2016-2017-ministry-of-education-and-human-resources-tertiary-c0245dc8 - Budget Data 2016-2017 - Ministry of Education and Human Resources, Tertiary and Scientific Research - itemno(source_units_unspecified)
• budget-data-2016-2017-ministry-of-education-and-human-resources-tertiary-c0833146 - Budget Data 2016-2017 - Ministry of Education and Human Resources, Tertiary and Scientific Research - amount(source_units_unspecified)

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	budget-data-2016-2017-ministry-of-education-and-human-resources-terti...
indicator_name	string	Human-readable indicator name.	Budget Data 2016-2017 - Ministry of Education and Human Resources, Te...
country_iso3	string	ISO3 country or area code.	MU
source_sheet	string	Source column from the original resource.	Sheet1
country_name	string	Country or area name.	Mauritius
year	int64	Observation year.	2015
value	double	Numeric observation value.	14507743880.54888
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
dimension_details	string	Source dimension retained during long-form normalization.	VOTE 10-1 TOTAL EXPENDITURE
dimension_column_2	string	Source dimension retained during long-form normalization.	``
dimension_column_3	string	Source dimension retained during long-form normalization.	``
dimension_column_4	string	Source dimension retained during long-form normalization.	``
source_period_start_year	int64	Start year inferred from source metadata.	2016
source_period_end_year	int64	End year inferred from source metadata.	2017
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2016-2017
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.	Budget Data 2016-2017 - Ministry of Education and Human Resources, Te...
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Education-Finance-2016-2017.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	8be9e054-3665-4907-9a4d-f900aa538114
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	cef29272-3fd5-4a17-abbe-1aa6201b45ff
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/8be9e054-3665-4907-9a4d-f900aa538114/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
dimension_head	string	Source dimension retained during long-form normalization.	``
dimension_subhead	string	Source dimension retained during long-form normalization.	``
dimension_expense_type	string	Source dimension retained during long-form normalization.	``
dimension_category	string	Source dimension retained during long-form normalization.	``
dimension_subcategory	string	Source dimension retained during long-form normalization.	``
dimension_end_financial_year	string	Source dimension retained during long-form normalization.	``
dimension_final_status	string	Source dimension retained during long-form normalization.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-budget-data-2016-2017-ministry-of-education-and-human-reso-621649fe")
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: Education-Finance-2016-2017.xlsx
• License: CC BY-SA 4.0
• Retrieved/generated: 2026-08-08T16:28:19Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-budget-data-2016-2017-ministry-of-education-and-human-reso-621649fe

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_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_mauritius_budget_data_2016_2017_ministry_of_education_and_human_reso_6216_2018,
  title        = {Budget Data 2016 2017 Ministry of Education and Human Reso | Africa (MDPA)},
  author       = {MDPA},
  year         = {2018},
  url          = {https://data.govmu.org/dataset/budget-data-2016-2017-ministry-education-and-human-resources-tertiary-and-scientific},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-budget-data-2016-2017-ministry-of-education-and-human-reso-621649fe}}
}

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/budget-data-2016-2017-ministry-education-and-human-resources-tertiary-and-scientific