electricsheepafrica/africa-number-of-refugees-from-kenya

Number of Refugees from Kenya

Publisher: UNHCR - The UN Refugee Agency · Source: HDX · License: other-pd-nr · Updated: 2022-09-23

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Abstract

The UNHCR Refugee Population statistics are compiled and curated at headquarters-level and released yearly at the same time of the UNHCR Statistical Yearbooks. This is a subset of the data only with refugees from Kenya. The full dataset is available here.

This dataset contains refugee population statistics from 1975 until 2012.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2022-09-23. Geographic scope: KEN.

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

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Dataset Characteristics

Domain	Demographics and population
Unit of observation	Country-level aggregates
Rows (total)	526
Columns	9 (5 numeric, 4 categorical, 0 datetime)
Train split	420 rows
Test split	105 rows
Geographic scope	KEN
Publisher	UNHCR - The UN Refugee Agency
HDX last updated	2022-09-23

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Variables

Geographic — year (range 1975.0–2012.0), country_or_territory_of_asylum_or_residence (GBR, DEN, SWE), country_or_territory_of_origin (KEN), refugees_assisted_by_unhcr (range 0.0–4783.0), total_refugees_and_people_in_refugee_like_situations_assisted_by_unhcr (range 0.0–133.0).

Outcome / Measurement — total_refugees_and_people_in_refugee_like_situations (range 0.0–8680.0).

Identifier / Metadata — refugees (range 0.0–8680.0), esa_source (HDX), esa_processed (2026-04-17).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-number-of-refugees-from-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
year	int64	0.0%	1975.0 – 2012.0 (mean 2003.9487)
country_or_territory_of_asylum_or_residence	object	0.0%	GBR, DEN, SWE
country_or_territory_of_origin	object	0.0%	KEN
refugees	float64	5.3%	0.0 – 8680.0 (mean 257.755)
refugees_assisted_by_unhcr	float64	63.7%	0.0 – 4783.0 (mean 151.7016)
total_refugees_and_people_in_refugee_like_situations	float64	5.3%	0.0 – 8680.0 (mean 257.755)
total_refugees_and_people_in_refugee_like_situations_assisted_by_unhcr	float64	63.3%	0.0 – 133.0 (mean 4.9067)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-17

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Numeric Summary

Column	Min	Max	Mean	Median
year	1975.0	2012.0	2003.9487	2005.0
refugees	0.0	8680.0	257.755	8.0
refugees_assisted_by_unhcr	0.0	4783.0	151.7016	1.0
total_refugees_and_people_in_refugee_like_situations	0.0	8680.0	257.755	8.0
total_refugees_and_people_in_refugee_like_situations_assisted_by_unhcr	0.0	133.0	4.9067	0.0

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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 UNHCR - The UN Refugee Agency and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• The following columns have >20% missing values and should be treated with caution in modelling: refugees_assisted_by_unhcr, total_refugees_and_people_in_refugee_like_situations_assisted_by_unhcr.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_number_of_refugees_from_kenya,
  title     = {Number of Refugees from Kenya},
  author    = {UNHCR - The UN Refugee Agency},
  year      = {2022},
  url       = {https://data.humdata.org/dataset/number-of-refugees-from-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.