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
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_iso3where 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
- Source: MDPA
- Publisher: MDPA
- Portal: https://data.govmu.org
- Resource: Energy_Water_Yr22_060623_Source_File.xlsx
- License: CC BY-SA 4.0
- Retrieved/generated:
2026-08-08T16:30:12Z - Hugging Face repo: electricsheepafrica/africa-mauritius-water-sales-by-tariff-of-subscriber-685f5471
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_iso3as 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