electricsheepafrica/africa-zimbabwe-gam-mam-and-sam-based-on-muac-measurements

Zimbabwe: GAM, MAM and SAM based on MUAC measurements

Publisher: OCHA Regional Office for Southern and Eastern Africa (ROSEA) · Source: HDX · License: cc-by · Updated: 2025-04-10

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Abstract

GAM,MAM and SAM for Zimbabwe based on MUAC measurements

Each row in this dataset represents geolocated point observations. Data was last updated on HDX on 2025-04-10. Geographic scope: ZWE.

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

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Dataset Characteristics

Domain	Demographics and population
Unit of observation	Geolocated point observations
Rows (total)	92
Columns	7 (3 numeric, 4 categorical, 0 datetime)
Train split	73 rows
Test split	18 rows
Geographic scope	ZWE
Publisher	OCHA Regional Office for Southern and Eastern Africa (ROSEA)
HDX last updated	2025-04-10

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Variables

Geographic — population_group (Children under 5 years).

Identifier / Metadata — esa_source (HDX), esa_processed (2026-04-19).

Other — adm_2 (Bulawayo, Zaka, Victoria Falls), sam (range 0.0–0.047), mam (range 0.0–0.105), gam (range 0.0–0.112).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-zimbabwe-gam-mam-and-sam-based-on-muac-measurements")
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
adm_2	object	0.0%	Bulawayo, Zaka, Victoria Falls
population_group	object	0.0%	Children under 5 years
sam	float64	0.0%	0.0 – 0.047 (mean 0.0155)
mam	float64	0.0%	0.0 – 0.105 (mean 0.0139)
gam	float64	0.0%	0.0 – 0.112 (mean 0.0294)
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
sam	0.0	0.047	0.0155	0.013
mam	0.0	0.105	0.0139	0.009
gam	0.0	0.112	0.0294	0.025

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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 OCHA Regional Office for Southern and Eastern Africa (ROSEA) 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_zimbabwe_gam_mam_and_sam_based_on_muac_measurements,
  title     = {Zimbabwe: GAM, MAM and SAM based on MUAC measurements},
  author    = {OCHA Regional Office for Southern and Eastern Africa (ROSEA)},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/zimbabwe-gam-mam-and-sam-based-on-muac-measurements},
  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.