Datasets:

electricsheepafrica
/

africa-mauritius-data-budget-data-2016-2017-judiciary-2a4ede9a

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
  - judiciary
  - budget-data
  - budget-data-judiciary-2016-2017
  - estimates
  - recurrent-expenditure
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-00000-of-00001.parquet
pretty_name: Data Budget Data 2016 2017 Judiciary | Africa (MDPA)

Data Budget Data 2016 2017 Judiciary | Africa (MDPA)

264 rows - 1 Africa country/area - 2015-2018 - 3 indicators - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 264 rows from MDPA, covering Data Budget Data 2016 2017 Judiciary. 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.

This dataset covers Data Budget Data 2016 2017 Judiciary 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	264
Countries/areas	1
First period	2015
Last period	2018
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`	264	2015	2018	`Mauritius`

Indicators, Variables, Or Resource Contents

data-budget-data-2016-2017-judiciary-item-no-0a9a39c4 - Data_Budget Data 2016-2017 - Judiciary - item no(source_units_unspecified)
data-budget-data-2016-2017-judiciary-end-financial-year-51664213 - Data_Budget Data 2016-2017 - Judiciary - end financial year(source_units_unspecified)
data-budget-data-2016-2017-judiciary-amount-152d916a - Data_Budget Data 2016-2017 - Judiciary - amount(source_units_unspecified)

Schema

Column	Type	Description	Example
`indicator_id`	`string`	Stable source or Electric Sheep Africa indicator identifier.	`data-budget-data-2016-2017-judiciary-item-no-0a9a39c4`
`indicator_name`	`string`	Human-readable indicator name.	`Data_Budget Data 2016-2017 - Judiciary - item no`
`country_iso3`	`string`	ISO3 country or area code.	`MU`
`country_name`	`string`	Country or area name.	`Mauritius`
`year`	`int64`	Observation year.	`2015`
`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.	`THE JUDICIARY`
`dimension_sub_head`	`string`	Source dimension retained during long-form normalization.	`THE JUDICIARY`
`dimension_expense_type`	`string`	Source dimension retained during long-form normalization.	`Reccurrent Expenditure`
`dimension_category`	`string`	Source dimension retained during long-form normalization.	`Compensation of Employees`
`dimension_sub_category`	`string`	Source dimension retained during long-form normalization.	`Personal Emoluments`
`dimension_financial_status`	`string`	Source dimension retained during long-form normalization.	`Estimates`
`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.	`Data_Budget Data 2016-2017 - Judiciary`
`source_resource`	`dictionary<values=string, indices=int8, ordered=0>`	Source resource title, table name, or file name.	`Data-_Judiciary-20162017_0.csv`
`source_package_id`	`dictionary<values=string, indices=int8, ordered=0>`	Source package identifier.	`970bb7f7-8138-4293-8c0d-ccb888f4bf54`
`source_resource_id`	`dictionary<values=string, indices=int8, ordered=0>`	Source resource identifier.	`85939184-9e93-4e28-a8ef-34484f6bd3c0`
`source_url`	`dictionary<values=string, indices=int8, ordered=0>`	Original source URL or download URL.	`https://data.govmu.org/dataset/970bb7f7-8138-4293-8c0d-ccb888f4bf54/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-data-budget-data-2016-2017-judiciary-2a4ede9a")
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: Data-_Judiciary-20162017_0.csv
License: CC BY-SA 4.0
Retrieved/generated: 2026-08-08T16:46:07Z
Hugging Face repo: electricsheepafrica/africa-mauritius-data-budget-data-2016-2017-judiciary-2a4ede9a

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_data_budget_data_2016_2017_judiciary_2a4ede9a_2018,
  title        = {Data Budget Data 2016 2017 Judiciary | Africa (MDPA)},
  author       = {MDPA},
  year         = {2018},
  url          = {https://data.govmu.org/dataset/databudget-data-2016-2017-judiciary},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-data-budget-data-2016-2017-judiciary-2a4ede9a}}
}

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/databudget-data-2016-2017-judiciary