electricsheepafrica/africa-ethiopia-surface-area

Ethiopia Surface Area

Publisher: OCHA Regional Office for Southern and Eastern Africa (ROSEA) · Source: HDX · License: other-pd-nr · Updated: 2023-09-28

---

Abstract

Data sourced from official Government of Ethiopia publication. More information about the data is available on the metadata of the attached datasheet.

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2023-09-28. Geographic scope: ETH.

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

---

Dataset Characteristics

Domain	Conflict and security
Unit of observation	First-level administrative unit observations
Rows (total)	12
Columns	5 (1 numeric, 4 categorical, 0 datetime)
Train split	9 rows
Test split	2 rows
Geographic scope	ETH
Publisher	OCHA Regional Office for Southern and Eastern Africa (ROSEA)
HDX last updated	2023-09-28

---

Variables

Geographic — country (Ethiopia), region (National Average, Tigray, Afar).

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

Other — surface_area_km_square (range 334.0–1020404.0).

---

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-ethiopia-surface-area")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

---

Schema

Column	Type	Null %	Range / Sample Values
country	object	0.0%	Ethiopia
region	object	0.0%	National Average, Tigray, Afar
surface_area_km_square	int64	0.0%	334.0 – 1020404.0 (mean 170067.3333)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-04

---

Numeric Summary

Column	Min	Max	Mean	Median
surface_area_km_square	334.0	1020404.0	170067.3333	61376.0

---

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.

---

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.

---

Citation

@dataset{hdx_africa_ethiopia_surface_area,
  title     = {Ethiopia Surface Area},
  author    = {OCHA Regional Office for Southern and Eastern Africa (ROSEA)},
  year      = {2023},
  url       = {https://data.humdata.org/dataset/ethiopia-surface-area},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.