electricsheepafrica/africa-south-sudan-fao-eve-global-flood-monitoring-system-9a74a50a

Fao Eve Global Flood Monitoring System | Africa (Food and Agriculture Organization (FAO) of the United Nations)

16,600 rows - 1 Africa country/area - 2024-2026 - 8 indicators - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 16,600 rows from Food and Agriculture Organization (FAO) of the United Nations, covering Fao Eve Global Flood Monitoring System. 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: Biweekly insights on flood events - their impacts on population and various land cover types - for Niger from 1 July 2024 (when available) to date.

How To Read This Dataset

• One row means: one indicator observation for one geography, time period, and optional source dimensions.
• Primary geography column: country_iso3.
• Best time column: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3, year, indicator_id.

Coverage

Dimension	Value
Rows	16,600
Countries/areas	1
First period	2024
Last period	2026
Indicators	8
Columns	26
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
SSD	16,600	2024	2026	South Sudan

Indicators, Variables, Or Resource Contents

• fao-eve-global-flood-monitoring-system-period-number-5530d86b - FAO EVE Global Flood Monitoring System - period number(source_units_unspecified)
• fao-eve-global-flood-monitoring-system-cropland-flooded-sq-km-d86213f9 - FAO EVE Global Flood Monitoring System - cropland flooded sq km(source_units_unspecified)
• fao-eve-global-flood-monitoring-system-cropland-flooded-ha-e010af1a - FAO EVE Global Flood Monitoring System - cropland flooded ha(source_units_unspecified)
• fao-eve-global-flood-monitoring-system-total-area-flooded-sq-km-0c767bef - FAO EVE Global Flood Monitoring System - total area flooded sq km(source_units_unspecified)
• fao-eve-global-flood-monitoring-system-total-area-flooded-ha-2db1b50f - FAO EVE Global Flood Monitoring System - total area flooded ha(source_units_unspecified)
• fao-eve-global-flood-monitoring-system-perc-cropland-flooded-e6acdec6 - FAO EVE Global Flood Monitoring System - perc cropland flooded(source_units_unspecified)
• fao-eve-global-flood-monitoring-system-perc-total-area-flooded-e3e87ed1 - FAO EVE Global Flood Monitoring System - perc total area flooded(source_units_unspecified)
• fao-eve-global-flood-monitoring-system-pop-exposed-698460ad - FAO EVE Global Flood Monitoring System - pop exposed(source_units_unspecified)

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	fao-eve-global-flood-monitoring-system-period-number-5530d86b
indicator_name	string	Human-readable indicator name.	FAO EVE Global Flood Monitoring System - period number
country_iso3	string	ISO3 country or area code.	SSD
country_name	string	Country or area name.	South Sudan
year	int64	Observation year.	2026
value	double	Numeric observation value.	61.0
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
dimension_adm0_iso3	string	Source dimension retained during long-form normalization.	NER
dimension_adm0_name	string	Source dimension retained during long-form normalization.	Niger
dimension_admin_level	string	Source dimension retained during long-form normalization.	admin2
dimension_adm1_pcode	string	Source dimension retained during long-form normalization.	NE007
dimension_adm1_name	string	Source dimension retained during long-form normalization.	Zinder
dimension_adm2_pcode	string	Source dimension retained during long-form normalization.	NE007007
dimension_adm2_name	string	Source dimension retained during long-form normalization.	Takiéta
dimension_end_date	string	Source dimension retained during long-form normalization.	2026-07-15
source_period_start_year	int64	Start year inferred from source metadata.	2024
source_period_end_year	int64	End year inferred from source metadata.	2024
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2024
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	Food and Agriculture Organization (FAO) of the United Nations
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	FAO EVE Global Flood Monitoring System
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	ner-flood-events-fao-eve.csv
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	1fa3b0d1-4b0b-415b-a978-8b4dbf50d1ca
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	3d8ee86c-8b42-45ae-860a-e4f7dc74648d
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.humdata.org/dataset/1fa3b0d1-4b0b-415b-a978-8b4dbf50d1ca...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-by
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-10T18:18:23Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-fao-eve-global-flood-monitoring-system-9a74a50a")
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"] == "SSD"]

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

• Canonical time field: 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: Food and Agriculture Organization (FAO) of the United Nations
• Publisher: Food and Agriculture Organization (FAO) of the United Nations
• Portal: https://data.humdata.org
• Resource: ner-flood-events-fao-eve.csv
• License: CC BY 4.0
• Retrieved/generated: 2026-08-10T18:33:14Z
• Hugging Face repo: electricsheepafrica/africa-south-sudan-fao-eve-global-flood-monitoring-system-9a74a50a

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
• Pivot to geography x period or indicator x period matrices
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_south_sudan_fao_eve_global_flood_monitoring_system_9a74a50a_2026,
  title        = {Fao Eve Global Flood Monitoring System | Africa (Food and Agriculture Organization (FAO) of the United Nations)},
  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    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-fao-eve-global-flood-monitoring-system-9a74a50a}}
}

License

Released under CC BY 4.0.

Original data is published by Food and Agriculture Organization (FAO) of the United Nations. 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 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/fao-eve-global-flood-monitoring-system