electricsheepafrica/africa-sudan-operational-presence

Sudan: Operational Presence

Publisher: OCHA Sudan · Source: HDX · License: cc-by · Updated: 2026-04-01

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Abstract

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working and what they are doing in order to identify gaps and plan for future humanitarian response. This dataset includes a list of humanitarian organizations by state and sector currently registered in Sudan. If you have updates for the 3W please contact OCHASudan@un.org.

Each row in this dataset represents first-level administrative unit observations. Temporal coverage is indicated by the reporting_month column(s). Geographic scope: SDN.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Humanitarian and development data
Unit of observation	First-level administrative unit observations
Rows (total)	2,669
Columns	9 (0 numeric, 8 categorical, 1 datetime)
Train split	2,135 rows
Test split	533 rows
Geographic scope	SDN
Publisher	OCHA Sudan
HDX last updated	2026-04-01

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Variables

Geographic — state (North Darfur, Khartoum, Gedaref), locality (Tawila, Wasat Al Gedaref, Madeinat Al Gedaref), org_acronym (SCI, UNICEF, RI), org_type (INGO, NNGO, UN Agency).

Temporal — reporting_month.

Identifier / Metadata — cluster_name (Protection, Health, Nutrition), org_name (Save the Children International, United Nations Children's Fund, Relief International), esa_source (HDX), esa_processed (2026-04-09).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-sudan-operational-presence")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
reporting_month	datetime64[ns]	0.0%
state	object	0.0%	North Darfur, Khartoum, Gedaref
locality	object	0.0%	Tawila, Wasat Al Gedaref, Madeinat Al Gedaref
cluster_name	object	0.0%	Protection, Health, Nutrition
org_name	object	0.0%	Save the Children International, United Nations Children's Fund, Relief International
org_acronym	object	0.0%	SCI, UNICEF, RI
org_type	object	0.0%	INGO, NNGO, UN Agency
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-09

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Numeric Summary

Column	Min	Max	Mean	Median
No numeric columns.

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Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. 1 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

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Limitations

• Data originates from OCHA Sudan and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_sudan_operational_presence,
  title     = {Sudan: Operational Presence},
  author    = {OCHA Sudan},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/sudan-operational-presence},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.