electricsheepafrica/africa-south-sudan-nutrition-gam-rates

South Sudan: Nutrition GAM rates

Publisher: UNICEF South Sudan · Source: HDX · License: cc-by · Updated: 2025-05-05

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Abstract

South Sudan nutrition GAM rates from the Nutrition Cluster as of December 2022.

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2025-05-05. Geographic scope: SSD.

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)	78
Columns	7 (1 numeric, 6 categorical, 0 datetime)
Train split	62 rows
Test split	15 rows
Geographic scope	SSD
Publisher	UNICEF South Sudan
HDX last updated	2025-05-05

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Variables

Geographic — adm1_state (Upper Nile, Jonglei, Western Equatoria), adm2_county (Juba, Longochuk, Panyikang), proxy_gam_2022 (range 0.043–0.271).

Identifier / Metadata — adm1_pcode (SS07, SS03, SS10), adm2_pcode (SS0101, SS0703, SS0710), esa_source (HDX), esa_processed (2026-04-17).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-south-sudan-nutrition-gam-rates")
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
adm1_state	object	0.0%	Upper Nile, Jonglei, Western Equatoria
adm1_pcode	object	0.0%	SS07, SS03, SS10
adm2_county	object	0.0%	Juba, Longochuk, Panyikang
adm2_pcode	object	0.0%	SS0101, SS0703, SS0710
proxy_gam_2022	float64	0.0%	0.043 – 0.271 (mean 0.1532)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-17

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Numeric Summary

Column	Min	Max	Mean	Median
proxy_gam_2022	0.043	0.271	0.1532	0.157

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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 UNICEF South 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_south_sudan_nutrition_gam_rates,
  title     = {South Sudan: Nutrition GAM rates},
  author    = {UNICEF South Sudan},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/south-sudan-nutrition-gam-rates},
  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.