electricsheepafrica/africa-kenya-pin-targeted-reached-by-location-and-cluster

Kenya Drought Related - People Affected, Targeted & Reached by Location

Publisher: OCHA Regional Office for Southern and Eastern Africa (ROSEA) · Source: HDX · License: cc-by · Updated: 2025-10-28

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Abstract

Drought affected areas and population in Kenya

Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-10-28. Geographic scope: KEN.

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

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Dataset Characteristics

Domain	Natural hazards and disaster risk
Unit of observation	Tabular records
Rows (total)	25
Columns	8 (4 numeric, 4 categorical, 0 datetime)
Train split	20 rows
Test split	5 rows
Geographic scope	KEN
Publisher	OCHA Regional Office for Southern and Eastern Africa (ROSEA)
HDX last updated	2025-10-28

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Variables

Geographic — location (County, Mandera, Wajir), operational_priority (range 1.0–2.0).

Outcome / Measurement — overall_affected (range 0.0–1012168.0).

Identifier / Metadata — unnamed_1 (admin1Pcode, KE009, KE008), unnamed_4 (range 0.0–843624.0), unnamed_5 (range 2463.0–515967.0), esa_source (HDX), esa_processed (2026-04-09).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-kenya-pin-targeted-reached-by-location-and-cluster")
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
location	object	0.0%	County, Mandera, Wajir
unnamed_1	object	0.0%	admin1Pcode, KE009, KE008
operational_priority	float64	8.0%	1.0 – 2.0 (mean 1.6522)
overall_affected	float64	8.0%	0.0 – 1012168.0 (mean 276812.1739)
unnamed_4	float64	8.0%	0.0 – 843624.0 (mean 185279.8261)
unnamed_5	float64	8.0%	2463.0 – 515967.0 (mean 76666.5652)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-09

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Numeric Summary

Column	Min	Max	Mean	Median
operational_priority	1.0	2.0	1.6522	2.0
overall_affected	0.0	1012168.0	276812.1739	170680.0
unnamed_4	0.0	843624.0	185279.8261	106116.0
unnamed_5	2463.0	515967.0	76666.5652	23478.0

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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. 4 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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_pin_targeted_reached_by_location_and_cluster,
  title     = {Kenya Drought Related - People Affected, Targeted & Reached by Location},
  author    = {OCHA Regional Office for Southern and Eastern Africa (ROSEA)},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/kenya-pin-targeted-reached-by-location-and-cluster},
  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.