electricsheepafrica/africa-cameroon-fao-eve-global-flood-monitoring-system-b97dc8b0

FAO EVE Global Flood Monitoring System | Africa (Cameroon official open data)

28,608 rows - 1 Africa country - 2024-2026 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from Cameroon 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: FAO EVE Global Flood Monitoring System
• Publisher: Food and Agriculture Organization (FAO) of the United Nations
• Resource: ssd-flood-events-fao-eve.csv
• Format: CSV
• License: CC BY 4.0
• Packaging mode: indicator_long

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
CMR	28,608	2024	2026	Cameroon

Indicators or Resource Contents

• fao-eve-global-flood-monitoring-system-period-number-101a153b - FAO EVE Global Flood Monitoring System - period number
• fao-eve-global-flood-monitoring-system-cropland-flooded-sq-km-1c65e3a2 - FAO EVE Global Flood Monitoring System - cropland flooded sq km
• fao-eve-global-flood-monitoring-system-cropland-flooded-ha-cc7b89fe - FAO EVE Global Flood Monitoring System - cropland flooded ha
• fao-eve-global-flood-monitoring-system-total-area-flooded-sq-km-f8425f4d - FAO EVE Global Flood Monitoring System - total area flooded sq km
• fao-eve-global-flood-monitoring-system-total-area-flooded-ha-7ef632a8 - FAO EVE Global Flood Monitoring System - total area flooded ha
• fao-eve-global-flood-monitoring-system-perc-cropland-flooded-891978c2 - FAO EVE Global Flood Monitoring System - perc cropland flooded
• fao-eve-global-flood-monitoring-system-perc-total-area-flooded-8b15d74f - FAO EVE Global Flood Monitoring System - perc total area flooded
• fao-eve-global-flood-monitoring-system-pop-exposed-23adc67b - FAO EVE Global Flood Monitoring System - pop exposed

Schema

Column	Type	Description	Example
indicator_id	string	Stable indicator identifier.	fao-eve-global-flood-monitoring-system-period-number-101a153b
indicator_name	string	Human-readable indicator name.	FAO EVE Global Flood Monitoring System - period number
country_iso3	string	ISO3 country code.	CMR
country_name	string	Country name.	Cameroon
year	Int64	Observation year.	2026
value	float64	Numeric observation value.	61.0
unit	string	Measurement unit, when available.	source_units_unspecified
dimension_adm0_iso3	string	Source dimension.	SSD
dimension_adm0_name	string	Source dimension.	South Sudan
dimension_admin_level	string	Source dimension.	admin2
dimension_adm1_pcode	string	Source dimension.	SS04
dimension_adm1_name	string	Source dimension.	Lakes
dimension_adm2_pcode	string	Source dimension.	SS0403
dimension_adm2_name	string	Source dimension.	Rumbek Centre
dimension_end_date	string	Source dimension.	2026-07-15
source_period_start_year	Int64	First year inferred from source resource metadata.	2024
source_period_end_year	Int64	Last year inferred from source resource metadata.	2024
source_period_label	category	Human-readable period inferred from source resource metadata.	2024
source_provider	category	Publishing organization.	Food and Agriculture Organization (FAO) of the United Nations
source_dataset	category	Source package title.	FAO EVE Global Flood Monitoring System
source_resource	category	Source resource title.	ssd-flood-events-fao-eve.csv
source_package_id	category	CKAN package UUID.	1fa3b0d1-4b0b-415b-a978-8b4dbf50d1ca
source_resource_id	category	CKAN resource UUID.	82ca2db7-440f-4bad-bb0e-490823239591
source_url	category	Original source resource URL.	https://data.humdata.org/dataset/1fa3b0d1-4b0b-415b-a978-8b4dbf50d1ca/re
license_id	category	Source license identifier.	cc-by
retrieved_at	category	UTC retrieval timestamp.	2026-08-24T22:56:18Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-cameroon-fao-eve-global-flood-monitoring-system-b97dc8b0")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "CMR"]

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_cameroon_fao_eve_global_flood_monitoring_system_b97dc8b0_2026,
  title        = {FAO EVE Global Flood Monitoring System | Africa (Cameroon official open data)},
  author       = {Food and Agriculture Organization (FAO) of the United Nations},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/fao-eve-global-flood-monitoring-system},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-cameroon-fao-eve-global-flood-monitoring-system-b97dc8b0}}
}

License

Released under CC BY 4.0.

Original data (c) Food and Agriculture Organization (FAO) of the United Nations. 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 2026-08-25 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/1fa3b0d1-4b0b-415b-a978-8b4dbf50d1ca/resource/82ca2db7-440f-4bad-bb0e-490823239591/download/ssd-flood-events-fao-eve.csv