electricsheepafrica/africa-mali-flood-hazard-data-for-disaster-risk-assessment-selected-co-334c4a27

Flood: Hazard Data for Disaster Risk Assessment (selected countries) | Africa (Mali official open data)

8,883 rows - 1 Africa country - 2000-2018 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from Mali 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: Flood: Hazard Data for Disaster Risk Assessment (selected countries)
• Publisher: ETH Zürich - Weather and Climate Risks
• Resource: admin1-timeseries-summaries-flood.csv
• Format: CSV
• License: CC BY 4.0
• Packaging mode: indicator_long

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
MLI	8,883	2000	2018	Mali

Indicators or Resource Contents

• flood-hazard-data-for-disaster-risk-assessment-selected-countries-latitu-381551aa - Flood: Hazard Data for Disaster Risk Assessment (selected countries) - latitude
• flood-hazard-data-for-disaster-risk-assessment-selected-countries-longit-6b755a49 - Flood: Hazard Data for Disaster Risk Assessment (selected countries) - longitude
• flood-hazard-data-for-disaster-risk-assessment-selected-countries-value-f653f0aa - Flood: Hazard Data for Disaster Risk Assessment (selected countries) - value

Schema

Column	Type	Description	Example
indicator_id	string	Stable indicator identifier.	flood-hazard-data-for-disaster-risk-assessment-selected-countries-latitu
indicator_name	string	Human-readable indicator name.	Flood: Hazard Data for Disaster Risk Assessment (selected countries) - l
country_iso3	string	ISO3 country code.	MLI
country_name	string	Country name.	Mali
year	Int64	Observation year.	2013
value	float64	Numeric observation value.	34.6418
unit	string	Measurement unit, when available.	source_units_unspecified
dimension_country_name	string	Source dimension.	Afghanistan
dimension_admin1_name	string	Source dimension.	Kabul
dimension_admin2_name	string	Source dimension.	``
dimension_aggregation	string	Source dimension.	sum
dimension_indicator	string	Source dimension.	flood.date
source_period_start_year	Int64	First year inferred from source resource metadata.	2000
source_period_end_year	Int64	Last year inferred from source resource metadata.	2018
source_period_label	category	Human-readable period inferred from source resource metadata.	2000-2018
source_provider	category	Publishing organization.	ETH Zürich - Weather and Climate Risks
source_dataset	category	Source package title.	Flood: Hazard Data for Disaster Risk Assessment (selected countries)
source_resource	category	Source resource title.	admin1-timeseries-summaries-flood.csv
source_package_id	category	CKAN package UUID.	46c703fe-7ba1-484b-a38c-8c53f0cf00c4
source_resource_id	category	CKAN resource UUID.	5b49391f-4251-4e5b-977a-ee1ea49e2034
source_url	category	Original source resource URL.	https://data.humdata.org/dataset/46c703fe-7ba1-484b-a38c-8c53f0cf00c4/re
license_id	category	Source license identifier.	cc-by
retrieved_at	category	UTC retrieval timestamp.	2026-08-13T10:40:31Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mali-flood-hazard-data-for-disaster-risk-assessment-selected-co-334c4a27")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "MLI"]

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_mali_flood_hazard_data_for_disaster_risk_assessment_selected_co_334c4a27_2018,
  title        = {Flood: Hazard Data for Disaster Risk Assessment (selected countries) | Africa (Mali official open data)},
  author       = {ETH Zürich - Weather and Climate Risks},
  year         = {2018},
  url          = {https://data.humdata.org/dataset/climada-flood-dataset},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mali-flood-hazard-data-for-disaster-risk-assessment-selected-co-334c4a27}}
}

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 2026-08-13 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/46c703fe-7ba1-484b-a38c-8c53f0cf00c4/resource/5b49391f-4251-4e5b-977a-ee1ea49e2034/download/admin1-timeseries-summaries-flood.csv