electricsheepasia/asia-refugees-people-in-need-idps-refugees-and-returne

People in Need, IDPs, Refugees and Returnees figures in 2020

Publisher: OCHA HQ · Source: HDX · License: cc-by-igo · Updated: 2026-04-27

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Abstract

This data contains the number of people in need, internally displaced persons (IDPs), returnees and refugees for 25 countries.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-04-27. Geographic scope: AFG, BFA, BDI, CMR, CAF, TCD, COL, COD, and 17 others.

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)	26
Columns	9 (4 numeric, 5 categorical, 0 datetime)
Train split	20 rows
Test split	5 rows
Geographic scope	AFG, BFA, BDI, CMR, CAF, TCD, COL, COD, and 17 others
Publisher	OCHA HQ
HDX last updated	2026-04-27

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Variables

Geographic — country (#country+name, Afghanistan, Burkina Faso), plan_type (Humanitarian response plan).

Identifier / Metadata — idps (range 10000.0–1900000.0), refugees (range 7000.0–1100000.0), esa_source (HDX), esa_processed (2026-05-05).

Other — humanitarian_response_plans (Afghanistan, Burkina Faso, Burundi), in_need (range 892784.0–24000000.0), returnees (range 30000.0–2850000.0).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-refugees-people-in-need-idps-refugees-and-returne")
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	0.0%	#country+name, Afghanistan, Burkina Faso
humanitarian_response_plans	object	3.8%	Afghanistan, Burkina Faso, Burundi
plan_type	object	3.8%	Humanitarian response plan
in_need	float64	3.8%	892784.0 – 24000000.0 (mean 6249360.92)
idps	float64	30.8%	10000.0 – 1900000.0 (mean 834005.5556)
refugees	float64	50.0%	7000.0 – 1100000.0 (mean 431000.0)
returnees	float64	38.5%	30000.0 – 2850000.0 (mean 588043.75)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-05-05

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Numeric Summary

Column	Min	Max	Mean	Median
in_need	892784.0	24000000.0	6249360.92	4800000.0
idps	10000.0	1900000.0	834005.5556	740500.0
refugees	7000.0	1100000.0	431000.0	468000.0
returnees	30000.0	2850000.0	588043.75	323500.0

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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 HQ 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: idps, refugees, returnees.
• This dataset spans 25 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_asia_refugees_people_in_need_idps_refugees_and_returne,
  title     = {People in Need, IDPs, Refugees and Returnees figures in 2020},
  author    = {OCHA HQ},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/people-in-need-idps-refugees-and-returnees-in-2020},
  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.