electricsheepafrica/africa-kenya-rates-of-access-to-electricity-per-county

Kenya rates of Access to Electricity per county

Publisher: OCHA Regional Office for Southern and Eastern Africa (ROSEA) · Source: HDX · License: other-pd-nr · Updated: 2025-05-05

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Abstract

Kenya rates of access to electricity per county as reported by commission of revenue allocation in December 2011

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2025-05-05. Geographic scope: KEN.

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

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Dataset Characteristics

Domain	Humanitarian and development data
Unit of observation	Country-level aggregates
Rows (total)	49
Columns	5 (1 numeric, 4 categorical, 0 datetime)
Train split	39 rows
Test split	9 rows
Geographic scope	KEN
Publisher	OCHA Regional Office for Southern and Eastern Africa (ROSEA)
HDX last updated	2025-05-05

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Variables

Geographic — country (Kenya), access_to_electricity (range 0.5–72.4).

Outcome / Measurement — counties (National Average, Baringo, Meru).

Identifier / Metadata — esa_source (HDX), esa_processed (2026-04-05).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-kenya-rates-of-access-to-electricity-per-county")
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
country	object	2.0%	Kenya
counties	object	2.0%	National Average, Baringo, Meru
access_to_electricity	float64	2.0%	0.5 – 72.4 (mean 13.4229)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-05

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Numeric Summary

Column	Min	Max	Mean	Median
access_to_electricity	0.5	72.4	13.4229	7.75

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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_kenya_rates_of_access_to_electricity_per_county,
  title     = {Kenya rates of  Access to Electricity per county},
  author    = {OCHA Regional Office for Southern and Eastern Africa (ROSEA)},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/kenya-rates-of-access-to-electricity-per-county},
  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.