electricsheepafrica/africa-south-sudan-acute-malnutrition

South Sudan : Acute Malnutrition

Publisher: HDX · Source: HDX · License: cc-by · Updated: 2026-02-05

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Abstract

South Sudan malnutrition rates from the IPC

Each row in this dataset represents time-series observations. Data was last updated on HDX on 2026-02-05. Geographic scope: SSD.

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

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Dataset Characteristics

Domain	Food security and nutrition
Unit of observation	Time-series observations
Rows (total)	12
Columns	8 (0 numeric, 8 categorical, 0 datetime)
Train split	9 rows
Test split	2 rows
Geographic scope	SSD
Publisher	HDX
HDX last updated	2026-02-05

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Variables

Temporal — number_of_children_6_59_months_in (SAM, 51,760, 43,177).

Identifier / Metadata — unnamed_0 (State, Central Equatoria, Eastern Equatoria), unnamed_1 (Children 6 - 59 months, 319,004, 229,157), unnamed_3 (MAM, 136,542, 124,710), unnamed_4 (GAM, 188,302, 167,887), unnamed_5 (Pregnant and Beastfeeding Women Cases, 80,863, 105,889) and 2 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-south-sudan-acute-malnutrition")
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
unnamed_0	object	0.0%	State, Central Equatoria, Eastern Equatoria
unnamed_1	object	0.0%	Children 6 - 59
months, 319,004, 229,157
number_of_children_6_59_months_in	object	0.0%	SAM, 51,760, 43,177
unnamed_3	object	0.0%	MAM, 136,542, 124,710
unnamed_4	object	0.0%	GAM, 188,302, 167,887
unnamed_5	object	0.0%	Pregnant and
Beastfeeding
Women Cases, 80,863, 105,889
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-06

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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. 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 HDX 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_south_sudan_acute_malnutrition,
  title     = {South Sudan : Acute Malnutrition},
  author    = {HDX},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/south-sudan-acute-malnutrition},
  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.