electricsheepafrica/africa-ethiopia-targeted-populaton-food-cluster

Ethiopia - Drought Induced Food Insecurity

Publisher: OCHA Ethiopia · Source: HDX · License: cc-by · Updated: 2025-08-31

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Abstract

The dataset contains the number of people targeted by the food cluster in relation to drought in Ethiopia.

Each row in this dataset represents subnational administrative unit observations. Data was last updated on HDX on 2025-08-31. Geographic scope: ETH.

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

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Dataset Characteristics

Domain	Food security and nutrition
Unit of observation	Subnational administrative unit observations
Rows (total)	391
Columns	9 (1 numeric, 8 categorical, 0 datetime)
Train split	312 rows
Test split	78 rows
Geographic scope	ETH
Publisher	OCHA Ethiopia
HDX last updated	2025-08-31

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Variables

Geographic — admin3pcode (ET010302, ET050592, ET050798), woreda (Erob, Kebridehar town, Lehel-Yucub), zone (East Hararge, West Hararge, Guji), admin2pcode (ET0410, ET0409, ET0414), region (Oromia, Somali, SNNP) and 1 others.

Identifier / Metadata — esa_source (HDX), esa_processed (2026-04-10).

Other — food_cluster_target (range 57.0–334621.0).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-ethiopia-targeted-populaton-food-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
admin3pcode	object	0.0%	ET010302, ET050592, ET050798
woreda	object	0.0%	Erob, Kebridehar town, Lehel-Yucub
zone	object	0.0%	East Hararge, West Hararge, Guji
admin2pcode	object	0.0%	ET0410, ET0409, ET0414
region	object	0.0%	Oromia, Somali, SNNP
admin1pcode	object	0.0%	ET04, ET05, ET07
food_cluster_target	float64	23.5%	57.0 – 334621.0 (mean 36657.2441)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-10

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Numeric Summary

Column	Min	Max	Mean	Median
food_cluster_target	57.0	334621.0	36657.2441	26188.0

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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. 1 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 Ethiopia 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: food_cluster_target.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_ethiopia_targeted_populaton_food_cluster,
  title     = {Ethiopia - Drought Induced Food Insecurity},
  author    = {OCHA Ethiopia},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/ethiopia-targeted-populaton-food-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.