electricsheepafrica/africa-mauritius-dangerous-bathing-beach-areas-cb257e15

Dangerous Bathing Beach Areas | Africa (MDPA)

63 rows - 1 Africa country/area - detected - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 63 rows from MDPA, covering Dangerous Bathing Beach Areas. 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: list of all dangerous bathing beach areas around the island

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: source_period_start_year.
• Time coverage basis: source_period_start_year.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	63
Countries/areas	1
First period	detected
Last period	detected
Indicators	0
Columns	19
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
MU	63	detected	detected	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.	28e96afd-7955-477c-9b18-51d1be6d59b6:0
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
fid	string	Source column from the original resource.	dangerous_bathing.1
beach	string	Source column from the original resource.	Le Goulet Dangerous Bathing
district	string	Source column from the original resource.	Pamplemousses
longitude	double	Source column from the original resource.	57.5172515
latitude	double	Source column from the original resource.	-20.1040249
source_period_start_year	int64	Start year inferred from source metadata.	``
source_period_end_year	int64	End year inferred from source metadata.	``
source_period_label	string	Source column from the original resource.	``
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.	dangerous bathing beach areas
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	dangerous_bathingf.csv
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	ec540fa4-8c61-4cbc-880c-202e8056c926
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	28e96afd-7955-477c-9b18-51d1be6d59b6
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/ec540fa4-8c61-4cbc-880c-202e8056c926/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-dangerous-bathing-beach-areas-cb257e15")
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 "source_period_start_year" in df.columns:
    trend = df.sort_values("source_period_start_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: source_period_start_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: dangerous_bathingf.csv
• License: CC BY-SA 4.0
• Retrieved/generated: 2026-08-08T16:38:06Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-dangerous-bathing-beach-areas-cb257e15

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
• Build time-series views and period-over-period comparisons
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_mauritius_dangerous_bathing_beach_areas_cb257e15_2026,
  title        = {Dangerous Bathing Beach Areas | Africa (MDPA)},
  author       = {MDPA},
  year         = {2026},
  url          = {https://data.govmu.org/dataset/dangerous-bathing-beach-areas},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-dangerous-bathing-beach-areas-cb257e15}}
}

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.

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Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/dangerous-bathing-beach-areas