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electricsheepafrica/africa-mauritius-budget-data-2017-2018-procurement-policy-office-aa4a2422

Budget Data 2017 2018 Procurement Policy Office | Africa (MDPA) 2,660 rows - 1 Africa country/area - 2016-2019 - 1 indicator - Engineered by Electric Sheep Africa TL;DR This dataset contains 2,660 rows from MDPA, covering Budget Data 2017 2018 Procurement Policy Office. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures Economic… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-budget-data-2017-2018-procurement-policy-office-aa4a2422.

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Budget Data 2017 2018 Procurement Policy Office | Africa (MDPA)

2,660 rows - 1 Africa country/area - 2016-2019 - 1 indicator - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 2,660 rows from MDPA, covering Budget Data 2017 2018 Procurement Policy Office. 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 - Procurement Policy Office

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

DimensionValue
Rows2,660
Countries/areas1
First period2016
Last period2019
Indicators1
Columns23
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
MU2,66020162019Mauritius

Indicators, Variables, Or Resource Contents

  • —budget-data-2017-2018-procurement-policy-office-aa4a2422 - Budget Data 2017-2018 - Procurement Policy Office(sourceunitsunspecified)

Schema

ColumnTypeDescriptionExample
indicator_idstringStable source or Electric Sheep Africa indicator identifier.budget-data-2017-2018-procurement-policy-office-aa4a2422
indicator_namestringHuman-readable indicator name.Budget Data 2017-2018 - Procurement Policy Office
country_iso3stringISO3 country or area code.MU
source_sheetstringSource column from the original resource.Sheet1
country_namestringCountry or area name.Mauritius
yearint64Observation year.2016
valuedoubleNumeric observation value.3746400000.0
unitstringMeasurement unit, when supplied by the source.source_units_unspecified
dimension_detailsstringSource dimension retained during long-form normalization.TOTAL EXPENDITURE
dimension_column_2stringSource dimension retained during long-form normalization.``
dimension_column_3stringSource dimension retained during long-form normalization.``
dimension_column_4stringSource dimension retained during long-form normalization.``
source_period_start_yearint64Start year inferred from source metadata.2017
source_period_end_yearint64End year inferred from source metadata.2017
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.2017
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.MDPA
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.Budget Data 2017-2018 - Procurement Policy Office
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.SOURCE_Budget_Data_PPO_2017_18.xlsx
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.479ccbf4-bd0b-48f0-b5f1-533d37a05c43
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.d0dfd80f-7c41-4425-a7b4-4f48ef7654c8
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.govmu.org/dataset/479ccbf4-bd0b-48f0-b5f1-533d37a05c43/r...
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.CC-BY-SA-4.0
retrieved_atdictionary<values=string, indices=int8, ordered=0>UTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-08-08T16:26:20Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-budget-data-2017-2018-procurement-policy-office-aa4a2422")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

python
print(df.info())
print(df.head())

Filter By Geography

python
if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "MU"]

Time-Series Pattern

python
if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

python
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

bibtex
@misc{electric_sheep_africa_africa_mauritius_budget_data_2017_2018_procurement_policy_office_aa4a2422_2019,
  title        = {Budget Data 2017 2018 Procurement Policy Office | Africa (MDPA)},
  author       = {MDPA},
  year         = {2019},
  url          = {https://data.govmu.org/dataset/budget-data-2017-2018-procurement-policy-office},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-budget-data-2017-2018-procurement-policy-office-aa4a2422}}
}

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-procurement-policy-office