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

Admissions for Treatment of Severe Acute Malnutrition (SAM) | Africa (Namibia 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 Namibia 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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-namibia-admissions-for-treatment-of-severe-acute-malnutrition-sam-81605917.

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Dataset Card

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

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

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from Namibia 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

Geographic coverage

1 Africa country:

CountryRowsFirst yearLast yearName
NAM1,55520202021Namibia

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

ColumnTypeDescriptionExample
indicator_idstringStable indicator identifier.admissions-for-treatment-of-severe-acute-malnutrition-sam-obs-value-535b
indicator_namestringHuman-readable indicator name.Admissions for Treatment of Severe Acute Malnutrition (SAM) - obs value
country_iso3stringISO3 country code.NAM
country_namestringCountry name.Namibia
yearInt64Observation year.2020
valuefloat64Numeric observation value.0.0
unitstringMeasurement unit, when available.source_units_unspecified
dimension_ref_areastringSource dimension.AFG
dimension_geographic_areastringSource dimension.Afghanistan
dimension_sitrep_indicatorstringSource dimension.CV-03-04
dimension_situation_report_indicatorstringSource dimension.Number of children 6-59 months admitted for TREATMENT OF SEVERE ACUTE MA
dimension_hac_pillarstringSource dimension.CV-03
dimension_humanitarian_action_for_children_pillarstringSource dimension.Continuity of health care for women and children
dimension_unit_measurestringSource dimension.PS
dimension_unit_of_measurestringSource dimension.Persons
dimension_data_sourcestringSource dimension.UNICEF Situation Report 2
dimension_obs_statusstringSource dimension.V
dimension_observation_statusstringSource dimension.Unvalidated value
source_period_start_yearInt64First year inferred from source resource metadata.``
source_period_end_yearInt64Last year inferred from source resource metadata.``
source_period_labelstringHuman-readable period inferred from source resource metadata.``
source_providercategoryPublishing organization.UNICEF Data and Analytics (HQ)
source_datasetcategorySource package title.Admissions for Treatment of Severe Acute Malnutrition (SAM)
source_resourcecategorySource resource title.DF_SITREP_COVID19.csv
source_package_idcategoryCKAN package UUID.32e7d10a-ce65-4b6b-aaae-cc124ca0049a
source_resource_idcategoryCKAN resource UUID.92827be4-f6b3-4453-80cc-4c5c2e5d3d5f
source_urlcategoryOriginal source resource URL.https://data.humdata.org/dataset/32e7d10a-ce65-4b6b-aaae-cc124ca0049a/re
license_idcategorySource license identifier.cc-by
retrieved_atcategoryUTC retrieval timestamp.2026-08-30T05:38:32Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-namibia-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"] == "NAM"]

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_namibia_admissions_for_treatment_of_severe_acute_malnutrition_sam_8160591_2021,
  title        = {Admissions for Treatment of Severe Acute Malnutrition (SAM) | Africa (Namibia 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-namibia-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