electricsheepafrica/africa-who-is-doing-what-and-where-in-sudan-november-2020

Who is doing What and Where in Sudan, November 2020

Publisher: OCHA Sudan · Source: HDX · License: cc-by · Updated: 2025-04-10

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Abstract

The data shows Who is doing What and Where by locality in Sudan

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2025-04-10. 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)	2,730
Columns	7 (0 numeric, 7 categorical, 0 datetime)
Train split	2,184 rows
Test split	546 rows
Geographic scope	SDN
Publisher	OCHA Sudan
HDX last updated	2025-04-10

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Variables

Geographic — state (South Darfur, South Kordofan, Kassala), locality (Beliel, Ag Geneina, Abyei), implementing_organization_type (UN, INGO, NGO).

Identifier / Metadata — implementing_organization_name (UNICEF, UNHCR, SRCS), esa_source (HDX), esa_processed (2026-04-19).

Other — sector_intervention (Protection, FSL, WASH).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-who-is-doing-what-and-where-in-sudan-november-2020")
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
state	object	0.0%	South Darfur, South Kordofan, Kassala
locality	object	0.0%	Beliel, Ag Geneina, Abyei
sector_intervention	object	0.0%	Protection, FSL, WASH
implementing_organization_name	object	0.0%	UNICEF, UNHCR, SRCS
implementing_organization_type	object	0.0%	UN, INGO, NGO
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-19

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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. 135 exact duplicate rows were removed. 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_who_is_doing_what_and_where_in_sudan_november_2020,
  title     = {Who is doing What and Where in Sudan, November 2020},
  author    = {OCHA Sudan},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/who-is-doing-what-and-where-in-sudan-november-2020},
  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.