Datasetpublic

electricsheepafrica/africa-eswatini-admissions-for-treatment-of-severe-acute-malnutrition-sam-81605917

Admissions for Treatment of Severe Acute Malnutrition (SAM) | Africa (Eswatini official open data) 1,555 rows - 1 Africa country - 2020-2021 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official CSV resource from Eswatini as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo. About the source Source: Admissions for… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-eswatini-admissions-for-treatment-of-severe-acute-malnutrition-sam-81605917.

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Dataset Card

Admissions for Treatment of Severe Acute Malnutrition (SAM) | Africa (Eswatini official open data)

1,555 rows - 1 Africa country - 2020-2021 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from Eswatini as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.

About the source

—Source: Admissions for Treatment of Severe Acute Malnutrition (SAM)
—Publisher: UNICEF Data and Analytics (HQ)
—Resource: DF_SITREP_COVID19.csv
—Format: CSV
—License: CC BY 4.0
—Packaging mode: indicator_long

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
`SWZ`	1,555	2020	2021	`Eswatini`

Indicators or Resource Contents

—admissions-for-treatment-of-severe-acute-malnutrition-sam-obs-value-535b4f36 - Admissions for Treatment of Severe Acute Malnutrition (SAM) - obs value
—admissions-for-treatment-of-severe-acute-malnutrition-sam-target-f801b1d9 - Admissions for Treatment of Severe Acute Malnutrition (SAM) - target

Schema

Column	Type	Description	Example
`indicator_id`	`string`	Stable indicator identifier.	`admissions-for-treatment-of-severe-acute-malnutrition-sam-obs-value-535b`
`indicator_name`	`string`	Human-readable indicator name.	`Admissions for Treatment of Severe Acute Malnutrition (SAM) - obs value`
`country_iso3`	`string`	ISO3 country code.	`SWZ`
`country_name`	`string`	Country name.	`Eswatini`
`year`	`Int64`	Observation year.	`2020`
`value`	`float64`	Numeric observation value.	`0.0`
`unit`	`string`	Measurement unit, when available.	`source_units_unspecified`
`dimension_ref_area`	`string`	Source dimension.	`AFG`
`dimension_geographic_area`	`string`	Source dimension.	`Afghanistan`
`dimension_sitrep_indicator`	`string`	Source dimension.	`CV-03-04`
`dimension_situation_report_indicator`	`string`	Source dimension.	`Number of children 6-59 months admitted for TREATMENT OF SEVERE ACUTE MA`
`dimension_hac_pillar`	`string`	Source dimension.	`CV-03`
`dimension_humanitarian_action_for_children_pillar`	`string`	Source dimension.	`Continuity of health care for women and children`
`dimension_unit_measure`	`string`	Source dimension.	`PS`
`dimension_unit_of_measure`	`string`	Source dimension.	`Persons`
`dimension_data_source`	`string`	Source dimension.	`UNICEF Situation Report 2`
`dimension_obs_status`	`string`	Source dimension.	`V`
`dimension_observation_status`	`string`	Source dimension.	`Unvalidated value`
`source_period_start_year`	`Int64`	First year inferred from source resource metadata.	``
`source_period_end_year`	`Int64`	Last year inferred from source resource metadata.	``
`source_period_label`	`string`	Human-readable period inferred from source resource metadata.	``
`source_provider`	`category`	Publishing organization.	`UNICEF Data and Analytics (HQ)`
`source_dataset`	`category`	Source package title.	`Admissions for Treatment of Severe Acute Malnutrition (SAM)`
`source_resource`	`category`	Source resource title.	`DF_SITREP_COVID19.csv`
`source_package_id`	`category`	CKAN package UUID.	`32e7d10a-ce65-4b6b-aaae-cc124ca0049a`
`source_resource_id`	`category`	CKAN resource UUID.	`92827be4-f6b3-4453-80cc-4c5c2e5d3d5f`
`source_url`	`category`	Original source resource URL.	`https://data.humdata.org/dataset/32e7d10a-ce65-4b6b-aaae-cc124ca0049a/re`
`license_id`	`category`	Source license identifier.	`cc-by`
`retrieved_at`	`category`	UTC retrieval timestamp.	`2026-08-30T05:35:43Z`

Usage

python

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-eswatini-admissions-for-treatment-of-severe-acute-malnutrition-sam-81605917")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python

sample_country = df[df["country_iso3"] == "SWZ"]

Work with indicators

python

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation

bibtex

@misc{electric_sheep_africa_africa_eswatini_admissions_for_treatment_of_severe_acute_malnutrition_sam_816059_2021,
  title        = {Admissions for Treatment of Severe Acute Malnutrition (SAM) | Africa (Eswatini official open data)},
  author       = {UNICEF Data and Analytics (HQ)},
  year         = {2021},
  url          = {https://data.humdata.org/dataset/number-of-admissions-for-treatment-of-severe-acute-malnutrition-sam},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-eswatini-admissions-for-treatment-of-severe-acute-malnutrition-sam-81605917}}
}

License

Released under CC BY 4.0.

Original data (c) UNICEF Data and Analytics (HQ). When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

Provenance: ingested 2026-08-30 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/32e7d10a-ce65-4b6b-aaae-cc124ca0049a/resource/92827be4-f6b3-4453-80cc-4c5c2e5d3d5f/download/dfsitrepcovid19.csv