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metadata
license: cc-by-sa-4.0
language:
  - en
task_categories:
  - tabular-regression
  - time-series-forecasting
multilinguality: multilingual
size_categories:
  - n<1K
tags:
  - tabular
  - africa
  - open-data
  - official-statistics
  - mauritius
  - mdpa
  - economics
  - finance-and-trade
  - budget-data-2017-2018-ministry-of-arts-and-culture
  - arts
  - arts-and-culture
  - culture
  - ministry-of-arts-and-culture
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-00000-of-00001.parquet
pretty_name: Budget Data 2017 2018 Ministry of Arts and Culture | Africa (MDPA)

Budget Data 2017 2018 Ministry of Arts and Culture | Africa (MDPA)

672 rows - 1 Africa country/area - 2016-2019 - 3 indicators - Engineered by Electric Sheep Africa

rows countries period indicators license

TL;DR

This dataset contains 672 rows from MDPA, covering Budget Data 2017 2018 Ministry of Arts and Culture. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Economic datasets help analysts examine production, prices, public finance, trade flows, market conditions, and macroeconomic change.

Source-provided context: Budget data 2017-2018 - Ministry of Arts and Culture

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 672
Countries/areas 1
First period 2016
Last period 2019
Indicators 3
Columns 24
Source format CSV

Geographic Coverage

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

Area Rows First year Last year Name
MU 672 2016 2019 Mauritius

Indicators, Variables, Or Resource Contents

  • budget-data-2017-2018-ministry-of-arts-and-culture-itemno-e1177c5b - Budget Data 2017-2018 - Ministry of Arts and Culture - itemno(source_units_unspecified)
  • budget-data-2017-2018-ministry-of-arts-and-culture-endfinancialyear-07f7d068 - Budget Data 2017-2018 - Ministry of Arts and Culture - endfinancialyear(source_units_unspecified)
  • budget-data-2017-2018-ministry-of-arts-and-culture-amount-830bd44b - Budget Data 2017-2018 - Ministry of Arts and Culture - amount(source_units_unspecified)

Schema

Column Type Description Example
indicator_id string Stable source or Electric Sheep Africa indicator identifier. budget-data-2017-2018-ministry-of-arts-and-culture-itemno-e1177c5b
indicator_name string Human-readable indicator name. Budget Data 2017-2018 - Ministry of Arts and Culture - itemno
country_iso3 string ISO3 country or area code. MU
country_name string Country or area name. Mauritius
year int64 Observation year. 2016
value double Numeric observation value. 21110.0
unit string Measurement unit, when supplied by the source. source_units_unspecified
dimension_head string Source dimension retained during long-form normalization. M of Arts and Culture
dimension_subhead string Source dimension retained during long-form normalization. General
dimension_expensetype string Source dimension retained during long-form normalization. Recurrent
dimension_category string Source dimension retained during long-form normalization. Compensation of Employees
dimension_subcategory string Source dimension retained during long-form normalization. Personal Emoluments
dimension_expensestatus string Source dimension retained during long-form normalization. Estimates
source_period_start_year int64 Start year inferred from source metadata. 2017
source_period_end_year int64 End year inferred from source metadata. 2018
source_period_label dictionary<values=string, indices=int8, ordered=0> Source column from the original resource. 2017-2018
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 2017-2018 - Ministry of Arts and Culture
source_resource dictionary<values=string, indices=int8, ordered=0> Source resource title, table name, or file name. DATA-Budget-data-2017-18-Ministry-of-Arts-%26-Culture_0.csv
source_package_id dictionary<values=string, indices=int8, ordered=0> Source package identifier. 46b7c6d0-f7e2-4af0-8919-2d59a0ea5aab
source_resource_id dictionary<values=string, indices=int8, ordered=0> Source resource identifier. be32782e-06bb-42b2-940f-d7ae2c6c1490
source_url dictionary<values=string, indices=int8, ordered=0> Original source URL or download URL. https://data.govmu.org/dataset/46b7c6d0-f7e2-4af0-8919-2d59a0ea5aab/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-budget-data-2017-2018-ministry-of-arts-and-culture-18ca6944")
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

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

  • Build time-series dashboards
  • Compare economic indicators
  • Join with population or sector data
  • 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_2017_2018_ministry_of_arts_and_culture_18ca6944_2019,
  title        = {Budget Data 2017 2018 Ministry of Arts and Culture | Africa (MDPA)},
  author       = {MDPA},
  year         = {2019},
  url          = {https://data.govmu.org/dataset/budget-data-2017-2018-ministry-arts-and-culture},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-budget-data-2017-2018-ministry-of-arts-and-culture-18ca6944}}
}

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/budget-data-2017-2018-ministry-arts-and-culture