electricsheepafrica/africa-poverty-rate-gap-density-and-the-percentage-of-poor-housing-at-location-level-in-kenya-in

Poverty rate, gap, density and the percentage of poor housing at Location level in Kenya in 1999.

Publisher: World Resources Institute (inactive) · Source: HDX · License: other-pd-nr · Updated: 2025-08-26

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Abstract

This dataset shows the Poverty rate, poverty gap, poverty density and the percentage of poor housing at Location level in Kenya in 1999. This dataset was originally collected by Kenya National Bureau of Statistics

Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-08-26. Geographic scope: KEN.

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

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Dataset Characteristics

Domain	Poverty and economic vulnerability
Unit of observation	Tabular records
Rows (total)	2,432
Columns	12 (9 numeric, 3 categorical, 0 datetime)
Train split	1,945 rows
Test split	486 rows
Geographic scope	KEN
Publisher	World Resources Institute (inactive)
HDX last updated	2025-08-26

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Variables

Geographic — location (TOWNSHIP, BURA, ATHI).

Identifier / Metadata — locid (range 0.0–8080407.0), esa_source (HDX), esa_processed (2026-04-04).

Other — area_km2 (range 0.4996–10715.4624), rural (range 0.0–1.0), fgt1_all2 (range 0.0–0.5668), fgt0_all2 (range 0.0–0.9119), loc_pple_a (range 0.0–107636.0) and 3 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-poverty-rate-gap-density-and-the-percentage-of-poor-housing-at-location-level-in-kenya-in")
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
locid	int64	0.0%	0.0 – 8080407.0 (mean 5454250.2512)
area_km2	float64	0.0%	0.4996 – 10715.4624 (mean 239.8251)
rural	int64	0.0%	0.0 – 1.0 (mean 0.9671)
fgt1_all2	float64	0.0%	0.0 – 0.5668 (mean 0.1719)
fgt0_all2	float64	0.0%	0.0 – 0.9119 (mean 0.4649)
loc_pple_a	int64	0.0%	0.0 – 107636.0 (mean 10069.1961)
locpoor_al	int64	0.0%	0.0 – 54914.0 (mean 5248.4149)
location	object	0.2%	TOWNSHIP, BURA, ATHI
loc_poor_d	float64	0.0%	0.0 – 35220.93 (mean 278.827)
ave_h3per	float64	0.0%	-100.0 – 100.0 (mean 46.0904)
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
locid	0.0	8080407.0	5454250.2512	6050503.5
area_km2	0.4996	10715.4624	239.8251	56.806
rural	0.0	1.0	0.9671	1.0
fgt1_all2	0.0	0.5668	0.1719	0.1758
fgt0_all2	0.0	0.9119	0.4649	0.504
loc_pple_a	0.0	107636.0	10069.1961	7551.0
locpoor_al	0.0	54914.0	5248.4149	3899.5
loc_poor_d	0.0	35220.93	278.827	71.755
ave_h3per	-100.0	100.0	46.0904	45.23

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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 World Resources Institute (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_poverty_rate_gap_density_and_the_percentage_of_poor_housing_at_location_level_in_kenya_in,
  title     = {Poverty rate, gap, density and the percentage of poor housing at Location level in Kenya in 1999.},
  author    = {World Resources Institute (inactive)},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/poverty-rate-gap-density-and-the-percentage-of-poor-housing-at-location-level-in-kenya-in-1999},
  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.