electricsheepafrica/africa-mauritius-number-of-incidents-related-to-flooding-and-hazardous-mate-95040182

Number of Incidents Related to Flooding and Hazardous Mate | Africa (MDPA)

9 rows - 1 Africa country/area - 2019-2021 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 9 rows from MDPA, covering Number of Incidents Related to Flooding and Hazardous Mate. 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: Dataset shows the Number of Incidents Related To Flooding and Hazardous Material Release Attended By Mauritius Fire and Rescue Service and Number of Persons Evacuated By Fire Station in Mauritius for the Year 2019 to 2021.

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	9
Countries/areas	1
First period	2019
Last period	2021
Indicators	0
Columns	27
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
MU	9	2019	2021	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.	8134df73-6933-4c86-9537-b920871377fe:table-75:0
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.	Table 75
rose_belle_1	string	Source column from the original resource.	Saint Aubin
napp	double	Source column from the original resource.	61.0
napp_2	double	Source column from the original resource.	0.0
d_4	double	Source column from the original resource.	26.0
d_0	double	Source column from the original resource.	0.0
d_103	double	Source column from the original resource.	64.0
d_3	double	Source column from the original resource.	5.0
napp_3	double	Source column from the original resource.	3.0
d_1	double	Source column from the original resource.	3.0
d_0_2	double	Source column from the original resource.	0.0
d_0_3	double	Source column from the original resource.	1.0
d_0_4	double	Source column from the original resource.	0.0
source_period_start_year	int64	Start year inferred from source metadata.	2019
source_period_end_year	int64	End year inferred from source metadata.	2021
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2019-2021
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.	Number of Incidents Related To Flooding and Hazardous Material Releas...
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Source-File_21.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	93c71613-05c0-437b-a167-d022667b8678
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	8134df73-6933-4c86-9537-b920871377fe
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/93c71613-05c0-437b-a167-d022667b8678/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-number-of-incidents-related-to-flooding-and-hazardous-mate-95040182")
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: Source-File_21.xlsx
• License: CC BY-SA 4.0
• Retrieved/generated: 2026-08-08T16:34:08Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-number-of-incidents-related-to-flooding-and-hazardous-mate-95040182

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_number_of_incidents_related_to_flooding_and_hazardous_mate_9504_2021,
  title        = {Number of Incidents Related to Flooding and Hazardous Mate | Africa (MDPA)},
  author       = {MDPA},
  year         = {2021},
  url          = {https://data.govmu.org/dataset/number-incidents-related-flooding-and-hazardous-material-release-attended-mauritius-fire-and},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-number-of-incidents-related-to-flooding-and-hazardous-mate-95040182}}
}

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/number-incidents-related-flooding-and-hazardous-material-release-attended-mauritius-fire-and