electricsheepafrica/africa-madagascar-tropical-cyclone-hazard-data-for-disaster-risk-assessment-4cc1de55

Tropical cyclone: Hazard Data for Disaster Risk Assessment (selected countries) | Africa (Madagascar official open data)

9,034 rows - 1 Africa country - not-applicable - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from Madagascar as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.

About the source

• Source: Tropical cyclone: Hazard Data for Disaster Risk Assessment (selected countries)
• Publisher: ETH Zürich - Weather and Climate Risks
• Resource: central-african-republic-admin1-tropical-cyclone.csv
• Format: CSV
• License: CC BY 4.0
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
MDG	9,034	n/a	n/a	Madagascar

Indicators or Resource Contents

• This source file is packaged as a normalized tabular resource.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier for tabular resources.	324ed0bd-cdb6-4b93-8651-d570a73a7a97:0
country_iso3	category	ISO3 country code.	MDG
country_name	category	Country name.	Madagascar
country_name_2	string	Source column.	#country
admin1_name	string	Source column.	#adm1+name
latitude	float64	Source column.	``
longitude	float64	Source column.	``
aggregation	string	Source column.	``
indicator	string	Source column.	#indicator+name
value	float64	Numeric observation value.	``
source_period_start_year	Int64	First year inferred from source resource metadata.	``
source_period_end_year	Int64	Last year inferred from source resource metadata.	``
source_period_label	string	Human-readable period inferred from source resource metadata.	``
source_provider	category	Publishing organization.	ETH Zürich - Weather and Climate Risks
source_dataset	category	Source package title.	Tropical cyclone: Hazard Data for Disaster Risk Assessment (selected cou
source_resource	category	Source resource title.	central-african-republic-admin1-tropical-cyclone.csv
source_package_id	category	CKAN package UUID.	f02bb601-9314-4162-9ebd-e1d18cdc2739
source_resource_id	category	CKAN resource UUID.	324ed0bd-cdb6-4b93-8651-d570a73a7a97
source_url	category	Original source resource URL.	https://data.humdata.org/dataset/f02bb601-9314-4162-9ebd-e1d18cdc2739/re
license_id	category	Source license identifier.	cc-by
retrieved_at	category	UTC retrieval timestamp.	2026-08-30T05:38:32Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-madagascar-tropical-cyclone-hazard-data-for-disaster-risk-assessment-4cc1de55")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "MDG"]

Work with indicators

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation

@misc{electric_sheep_africa_africa_madagascar_tropical_cyclone_hazard_data_for_disaster_risk_assessment_4cc1_2026,
  title        = {Tropical cyclone: Hazard Data for Disaster Risk Assessment (selected countries) | Africa (Madagascar official open data)},
  author       = {ETH Zürich - Weather and Climate Risks},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/climada-tropical-cyclone-dataset},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-madagascar-tropical-cyclone-hazard-data-for-disaster-risk-assessment-4cc1de55}}
}

License

Released under CC BY 4.0.

Original data (c) ETH Zürich - Weather and Climate Risks. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

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Provenance: ingested 2026-08-30 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/f02bb601-9314-4162-9ebd-e1d18cdc2739/resource/324ed0bd-cdb6-4b93-8651-d570a73a7a97/download/central-african-republic-admin1-tropical-cyclone.csv