electricsheepafrica/africa-bed-nets-and-illness-by-county-kenya

Kenya - Bed Nets, Malaria and Fever occurrence and Health spending per County

Publisher: Kenya Open Data Initiative (inactive) · Source: HDX · License: other-pd-nr · Updated: 2023-03-03

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Abstract

Dataset that shows the percentage of people sleeping under a bed-net, percentage of people who had malaria or fever and the health spending per county in kenya

Each row in this dataset represents tabular records. Data was last updated on HDX on 2023-03-03. Geographic scope: KEN.

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

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Dataset Characteristics

Domain	Public health
Unit of observation	Tabular records
Rows (total)	47
Columns	7 (4 numeric, 3 categorical, 0 datetime)
Train split	37 rows
Test split	9 rows
Geographic scope	KEN
Publisher	Kenya Open Data Initiative (inactive)
HDX last updated	2023-03-03

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Variables

Geographic — name_of_county (BARINGO, NYERI, MIGORI).

Demographic — percentagethat_slept_under_a_be (range 1.7–62.4), percentage_that_had_a_fever_or (range 0.0–63.3), heath_spending_per_person (range 7.0–50.0).

Identifier / Metadata — objectid (range 1.0–47.0), esa_source (HDX), esa_processed (2026-04-04).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-bed-nets-and-illness-by-county-kenya")
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
objectid	int64	0.0%	1.0 – 47.0 (mean 24.0)
name_of_county	object	0.0%	BARINGO, NYERI, MIGORI
percentagethat_slept_under_a_be	float64	0.0%	1.7 – 62.4 (mean 26.7298)
percentage_that_had_a_fever_or	float64	0.0%	0.0 – 63.3 (mean 40.1809)
heath_spending_per_person	int64	0.0%	7.0 – 50.0 (mean 24.0426)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-04

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Numeric Summary

Column	Min	Max	Mean	Median
objectid	1.0	47.0	24.0	24.0
percentagethat_slept_under_a_be	1.7	62.4	26.7298	27.8
percentage_that_had_a_fever_or	0.0	63.3	40.1809	42.6
heath_spending_per_person	7.0	50.0	24.0426	22.0

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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 Kenya Open Data Initiative (inactive) 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_bed_nets_and_illness_by_county_kenya,
  title     = {Kenya - Bed Nets, Malaria and Fever occurrence and Health spending per County},
  author    = {Kenya Open Data Initiative (inactive)},
  year      = {2023},
  url       = {https://data.humdata.org/dataset/bed-nets-and-illness-by-county-kenya},
  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.