Datasets:

electricsheepafrica
/

africa-diabetes-comoros

sample_id stringlengths 15 15	population stringclasses 7 values	region stringclasses 5 values	is_SSA bool 2 classes	is_reference_panel bool 2 classes	sex stringclasses 2 values	age int64 18 85	hiv_status stringclasses 2 values	has_hiv bool 2 classes	on_art bool 2 classes	viral_suppressed bool 2 classes	viral_load_copies_ml float64 0 1.03M	diabetes_status stringclasses 2 values	has_diabetes bool 2 classes	hypertension_status stringclasses 2 values	has_hypertension bool 2 classes	tb_coinfection_status stringclasses 2 values
CO_SAMPLE_00001	SSA_West	West	true	false	Female	48	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00002	SSA_West	West	true	false	Female	30	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00003	SSA_West	West	true	false	Female	54	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00004	SSA_West	West	true	false	Female	56	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00005	SSA_West	West	true	false	Female	19	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00006	SSA_West	West	true	false	Male	27	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00007	SSA_West	West	true	false	Female	46	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00008	SSA_West	West	true	false	Female	40	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00009	SSA_West	West	true	false	Male	44	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00010	SSA_West	West	true	false	Female	33	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00011	SSA_West	West	true	false	Female	55	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00012	SSA_West	West	true	false	Male	54	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00013	SSA_West	West	true	false	Female	45	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00014	SSA_West	West	true	false	Female	59	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00015	SSA_West	West	true	false	Female	50	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00016	SSA_West	West	true	false	Male	33	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00017	SSA_West	West	true	false	Female	49	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00018	SSA_West	West	true	false	Female	32	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00019	SSA_West	West	true	false	Female	55	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00020	SSA_West	West	true	false	Female	43	Negative	false	false	false	0	Type2	true	No	false	No
CO_SAMPLE_00021	SSA_West	West	true	false	Male	42	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00022	SSA_West	West	true	false	Female	35	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00023	SSA_West	West	true	false	Male	60	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00024	SSA_West	West	true	false	Female	42	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00025	SSA_West	West	true	false	Female	38	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00026	SSA_West	West	true	false	Male	39	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00027	SSA_West	West	true	false	Female	51	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00028	SSA_West	West	true	false	Female	49	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00029	SSA_West	West	true	false	Male	49	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00030	SSA_West	West	true	false	Female	50	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00031	SSA_West	West	true	false	Female	72	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00032	SSA_West	West	true	false	Male	39	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00033	SSA_West	West	true	false	Female	37	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00034	SSA_West	West	true	false	Female	33	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00035	SSA_West	West	true	false	Female	52	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00036	SSA_West	West	true	false	Female	59	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00037	SSA_West	West	true	false	Female	43	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00038	SSA_West	West	true	false	Male	33	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00039	SSA_West	West	true	false	Female	33	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00040	SSA_West	West	true	false	Male	52	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00041	SSA_West	West	true	false	Female	54	Positive	true	true	false	19,236.455298	No	false	Yes	true	No
CO_SAMPLE_00042	SSA_West	West	true	false	Female	51	Negative	false	false	false	0	Type2	true	No	false	No
CO_SAMPLE_00043	SSA_West	West	true	false	Female	35	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00044	SSA_West	West	true	false	Male	47	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00045	SSA_West	West	true	false	Female	46	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00046	SSA_West	West	true	false	Female	47	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00047	SSA_West	West	true	false	Male	55	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00048	SSA_West	West	true	false	Male	47	Negative	false	false	false	0	Type2	true	No	false	No
CO_SAMPLE_00049	SSA_West	West	true	false	Female	53	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00050	SSA_West	West	true	false	Male	45	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00051	SSA_West	West	true	false	Female	48	Negative	false	false	false	0	Type2	true	No	false	No
CO_SAMPLE_00052	SSA_West	West	true	false	Female	52	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00053	SSA_West	West	true	false	Female	25	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00054	SSA_West	West	true	false	Female	40	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00055	SSA_West	West	true	false	Female	38	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00056	SSA_West	West	true	false	Male	36	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00057	SSA_West	West	true	false	Female	40	Negative	false	false	false	0	Type2	true	No	false	No
CO_SAMPLE_00058	SSA_West	West	true	false	Male	63	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00059	SSA_West	West	true	false	Male	33	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00060	SSA_West	West	true	false	Male	57	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00061	SSA_West	West	true	false	Male	22	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00062	SSA_West	West	true	false	Male	40	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00063	SSA_West	West	true	false	Male	46	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00064	SSA_West	West	true	false	Female	52	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00065	SSA_West	West	true	false	Female	53	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00066	SSA_West	West	true	false	Female	54	Positive	true	false	false	19,221.903026	No	false	No	false	No
CO_SAMPLE_00067	SSA_West	West	true	false	Female	39	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00068	SSA_West	West	true	false	Female	38	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00069	SSA_West	West	true	false	Male	55	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00070	SSA_West	West	true	false	Female	42	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00071	SSA_West	West	true	false	Male	27	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00072	SSA_West	West	true	false	Female	29	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00073	SSA_West	West	true	false	Female	32	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00074	SSA_West	West	true	false	Female	50	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00075	SSA_West	West	true	false	Female	46	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00076	SSA_West	West	true	false	Female	53	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00077	SSA_West	West	true	false	Female	38	Negative	false	false	false	0	Type2	true	No	false	No
CO_SAMPLE_00078	SSA_West	West	true	false	Female	46	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00079	SSA_West	West	true	false	Female	52	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00080	SSA_West	West	true	false	Female	40	Negative	false	false	false	0	Type2	true	Yes	true	No
CO_SAMPLE_00081	SSA_West	West	true	false	Female	50	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00082	SSA_West	West	true	false	Female	35	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00083	SSA_West	West	true	false	Female	39	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00084	SSA_West	West	true	false	Female	39	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00085	SSA_West	West	true	false	Female	28	Negative	false	false	false	0	Type2	true	No	false	No
CO_SAMPLE_00086	SSA_West	West	true	false	Female	50	Negative	false	false	false	0	Type2	true	Yes	true	No
CO_SAMPLE_00087	SSA_West	West	true	false	Male	38	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00088	SSA_West	West	true	false	Male	44	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00089	SSA_West	West	true	false	Male	50	Positive	true	true	true	464.417777	No	false	No	false	No
CO_SAMPLE_00090	SSA_West	West	true	false	Female	50	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00091	SSA_West	West	true	false	Female	53	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00092	SSA_West	West	true	false	Female	43	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00093	SSA_West	West	true	false	Male	38	Positive	true	true	false	5,763.721347	No	false	No	false	No
CO_SAMPLE_00094	SSA_West	West	true	false	Male	43	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00095	SSA_West	West	true	false	Male	22	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00096	SSA_West	West	true	false	Male	25	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00097	SSA_West	West	true	false	Female	27	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00098	SSA_West	West	true	false	Male	31	Negative	false	false	false	0	No	false	Yes	true	No
CO_SAMPLE_00099	SSA_West	West	true	false	Male	49	Negative	false	false	false	0	No	false	No	false	No
CO_SAMPLE_00100	SSA_West	West	true	false	Female	32	Negative	false	false	false	0	No	false	No	false	No

End of preview. Expand in Data Studio

SSA Comorbidities Dataset (Adults, Multi-ancestry) | Africa (Electric Sheep Africa metadata inventory)

Size category: 10K<n<100K - Formats: parquet - Sector: health - Engineered by Electric Sheep Africa

TL;DR

This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.

What This Dataset Covers

Health datasets help researchers examine disease burden, service delivery, risk factors, outcomes, and public-health program performance.

Dataset context from the existing Hugging Face card: SSA Comorbidities Dataset (Adults, Multi-ancestry, Synthetic) Dataset summary This dataset provides a synthetic adult cohort (18–85 years) with key infectious and chronic comorbidities relevant to cancer and NCD risk in sub-Saharan Africa (SSA) and reference populations. Included conditions: HIV prevalence with ART status and viral load distributions. Diabetes prevalence (Type 2 diabetes). Hypertension prevalence. Tuberculosis (TB) co-infection rates among people living… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-diabetes-comoros.

Dataset Profile

Field	Value
Hugging Face repo	`electricsheepafrica/africa-diabetes-comoros`
Sector	health
Topic tags	hiv, viral-load, diabetes, hypertension, tuberculosis, comorbidities, sub-saharan-africa
Modalities	`tabular`, `text`
Formats	`parquet`
Size category	`10K<n<100K`
Countries	Comoros
ISO3 coverage	`COM`
Last modified on HF	`2025-11-24 14:23:30+00:00`
Inventory snapshot	`2026-07-16T16:00:34Z`

How To Read This Dataset

Start from the repository files and the dataset viewer when available.
Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
Preserve missing values until you have a defensible imputation rule.

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-diabetes-comoros")
print(ds)

split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])

Convert To Pandas When Tabular

from datasets import Dataset

first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
    df = first_split.to_pandas()
    print(df.head())

Data Quality Notes

This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
Exact schema, row counts, and source files should be inspected in the repository data files.
Metadata gaps from the inventory: upstream_publisher.
Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.

Source And Provenance

Source context: Electric Sheep Africa metadata inventory
Publisher/source attribution: Public dataset metadata
License: cc-by-nc-4.0
Hugging Face URL: https://huggingface.co/datasets/electricsheepafrica/africa-diabetes-comoros
Inventory retrieved at: 2026-07-16T16:00:34Z

Suggested Analyses

Inspect schema and missingness before modeling.
Profile variables by geography, time, and subgroup columns where present.
Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.

Citation

@misc{electric_sheep_africa_africa_diabetes_comoros_2026,
  title        = {SSA Comorbidities Dataset (Adults, Multi-ancestry) | Africa (Electric Sheep Africa metadata inventory)},
  author       = {Public dataset metadata},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-diabetes-comoros},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-diabetes-comoros}}
}

License

Released under cc-by-nc-4.0.

Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.

Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.

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Collection including electricsheepafrica/africa-diabetes-comoros

Comoros · Country Data Coverage

Collection

89 official ML-ready Comoros open-data resources, plus related Electric Sheep Africa datasets. • 147 items • Updated Aug 30