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metadata
license: cc-by-sa-4.0
language:
  - en
task_categories:
  - tabular-classification
  - tabular-regression
multilinguality: multilingual
size_categories:
  - n<1K
tags:
  - tabular
  - africa
  - open-data
  - official-statistics
  - mauritius
  - mdpa
  - climate
  - environment-and-natural-resources
  - commercial
  - domestic
  - industrial
  - religious
  - water
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-00000-of-00001.parquet
pretty_name: Water Sales by Tariff of Subscriber | Africa (MDPA)

Water Sales by Tariff of Subscriber | Africa (MDPA)

28 rows - 1 Africa country/area - 2016-2022 - source table - Engineered by Electric Sheep Africa

rows countries period indicators license

TL;DR

This dataset contains 28 rows from MDPA, covering Water Sales by Tariff of Subscriber. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Climate and environment datasets help analysts study exposure, resource conditions, environmental pressure, and climate-related trends.

Source-provided context: The data shows the water sales by tariff of subscribers for island of Mauritius for the year 2016 to 2022

How To Read This Dataset

  • One row means: one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
  • Primary geography column: country_iso3.
  • Best time column: not detected.
  • Time coverage basis: source metadata.
  • Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension Value
Rows 28
Countries/areas 1
First period 2016
Last period 2022
Indicators 0
Columns 55
Source format XLSX

Geographic Coverage

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

Area Rows First year Last year Name
MU 28 2016 2022 Mauritius

Indicators, Variables, Or Resource Contents

  • This repo preserves one source tabular resource with its usable columns kept together.

Schema

Column Type Description Example
source_record_id string Stable row identifier assigned during Electric Sheep Africa engineering. ff1be866-1f8f-4c16-af99-f14cd51ddfb5:tab16:0
country_iso3 dictionary<values=string, indices=int8, ordered=0> ISO3 country or area code. MU
country_name dictionary<values=string, indices=int8, ordered=0> Country or area name. Mauritius
source_sheet string Source column from the original resource. TAB16
column_1 string Source column from the original resource. ``
domestic string Source column from the original resource. Public Sector Agency
d_365971 double Source column from the original resource. 2587.0
d_92_92495588253963 double Source column from the original resource. 0.6568740716289817
d_85053_399 double Source column from the original resource. 4096.654
d_69_77075636118678 double Source column from the original resource. 3.360555268697507
d_832555_79997 double Source column from the original resource. 98681.707
d_55_00829401135688 double Source column from the original resource. 6.52005829806744
d_232_40475064964164 double Source column from the original resource. 1583.5539234634712
d_9_788624672953988 double Source column from the original resource. 24.088367482340463
d_372734 double Source column from the original resource. 2603.0
d_92_94069244099789 double Source column from the original resource. 0.649054345522323
d_87497_492 double Source column from the original resource. 4338.04
d_68_68942650464635 double Source column from the original resource. 3.40555452439958
d_870695_6203399999 double Source column from the original resource. 104306.187
d_53_14584534898735 double Source column from the original resource. 6.366680104672956
d_234_74513191713126 double Source column from the original resource. 1666.5539761813293
d_9_951092316337478 double Source column from the original resource. 24.04454246618289
source_period_start_year int64 Start year inferred from source metadata. 2016
source_period_end_year int64 End year inferred from source metadata. 2022
source_period_label dictionary<values=string, indices=int8, ordered=0> Source column from the original resource. 2016-2022
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. Water sales by tariff of subscriber
source_resource dictionary<values=string, indices=int8, ordered=0> Source resource title, table name, or file name. Energy_Water_Yr22_060623_Source_File.xlsx
source_package_id dictionary<values=string, indices=int8, ordered=0> Source package identifier. 9584b934-20df-4dd5-98e7-e3ff15f7aa8e
source_resource_id dictionary<values=string, indices=int8, ordered=0> Source resource identifier. ff1be866-1f8f-4c16-af99-f14cd51ddfb5
source_url dictionary<values=string, indices=int8, ordered=0> Original source URL or download URL. https://data.govmu.org/dataset/9584b934-20df-4dd5-98e7-e3ff15f7aa8e/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
type_of_tariff string Source column from the original resource. ``
column_2 string Source column from the original resource. ``
no_of_consumers double Source column from the original resource. ``
volume_sold_thousand_m3 double Source column from the original resource. ``
amount_collectible_rs_000 double Source column from the original resource. ``
average_sales_price_per_m3 double Source column from the original resource. ``
no_of_consumers_2 double Source column from the original resource. ``
volume_sold_thousand_m3_2 double Source column from the original resource. ``
amount_collectible_rs_000_2 double Source column from the original resource. ``
average_sales_price_per_m3_2 double Source column from the original resource. ``
no_of_consumers_3 double Source column from the original resource. ``
volume_sold_thousand_m3_3 double Source column from the original resource. ``
amount_collectible_rs_000_3 double Source column from the original resource. ``
average_sales_price_per_m3_3 double Source column from the original resource. ``
no_of_consumers_4 double Source column from the original resource. ``
volume_sold_thousand_m3_4 double Source column from the original resource. ``
amount_collectible_rs_000_4 double Source column from the original resource. ``
average_sales_price_per_m3_4 double Source column from the original resource. ``
no_of_consumers_5 double Source column from the original resource. ``
volume_sold_thousand_m3_5 double Source column from the original resource. ``
amount_collectible_rs_000_5 double Source column from the original resource. ``
average_sales_price_per_m3_5 double Source column from the original resource. ``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-water-sales-by-tariff-of-subscriber-685f5471")
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

  • No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
  • 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

  • Analyze seasonal or annual patterns
  • Join with agriculture or health data
  • Map geographic exposure
  • Check missingness before modeling
  • Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_mauritius_water_sales_by_tariff_of_subscriber_685f5471_2022,
  title        = {Water Sales by Tariff of Subscriber | Africa (MDPA)},
  author       = {MDPA},
  year         = {2022},
  url          = {https://data.govmu.org/dataset/water-sales-tariff-subscriber},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-water-sales-by-tariff-of-subscriber-685f5471}}
}

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/water-sales-tariff-subscriber