electricsheepafrica/africa-ethiopian-health-facilities

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- tabular-classification
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- facilities-infrastructure
- geodata
- health-facilities
- eth
pretty_name: "Ethiopia - Health Facilities"
dataset_info:
splits:
- name: train
num_examples: 32420
- name: test
num_examples: 8105
---

# Ethiopia - Health Facilities

**Publisher:** 3iS · **Source:** [HDX](https://data.humdata.org/dataset/ethiopian-health-facilities) · **License:** `cc-by` · **Updated:** 2025-03-19

---

## Abstract

This dataset includes the spatial locations of health facilities across Ethiopia, along with their associated attribute information.

Each row in this dataset represents subnational administrative unit observations. Data was last updated on HDX on 2025-03-19. Geographic scope: **ETH**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Public health |
| **Unit of observation** | Subnational administrative unit observations |
| **Rows (total)** | 40,525 |
| **Columns** | 18 (4 numeric, 14 categorical, 0 datetime) |
| **Train split** | 32,420 rows |
| **Test split** | 8,105 rows |
| **Geographic scope** | ETH |
| **Publisher** | 3iS |
| **HDX last updated** | 2025-03-19 |

---

## Variables

**Geographic** — `latitude` (range 3.5317–14.7229), `longitude` (range 33.2315–47.1221), `type` (Health Post, Clinic, Pharmacy), `admin3name` (Kolfe Keraniyo, Mekelle, Adama town), `admin3pcod` (ET140103, ET010701, ET040714) and 5 others.

**Identifier / Metadata** — `id` (range 1000861.0–1092681.0), `name` (Selam Primary Clinic, Rohobot Primary Clinic, Abenezer Primary Clinic), `esa_source`, `esa_processed`.

**Other** — `altitude` (range -1815.7–4180700304.0), `ownership` (Public/Government, Private for profit, Private Not for profit), `kebele`, `status`.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-ethiopian-health-facilities")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `id` | int64 | 0.0% | 1000861.0 – 1092681.0 (mean 1052325.5114) |
| `name` | object | 0.0% | Selam Primary Clinic, Rohobot Primary Clinic, Abenezer Primary Clinic |
| `latitude` | float64 | 0.0% | 3.5317 – 14.7229 (mean 8.9813) |
| `longitude` | float64 | 0.0% | 33.2315 – 47.1221 (mean 38.516) |
| `altitude` | float64 | 5.3% | -1815.7 – 4180700304.0 (mean 110732.8086) |
| `ownership` | object | 0.0% | Public/Government, Private for profit, Private Not for profit |
| `type` | object | 0.1% | Health Post, Clinic, Pharmacy |
| `admin3name` | object | 0.0% | Kolfe Keraniyo, Mekelle, Adama town |
| `admin3pcod` | object | 0.0% | ET140103, ET010701, ET040714 |
| `admin2name` | object | 0.0% | Region 14, South Wello, East Shewa |
| `admin2pcod` | object | 0.0% | ET1401, ET0304, ET0407 |
| `admin1name` | object | 0.0% | Oromia, Amhara, SNNP |
| `admin1pcod` | object | 0.0% | ET04, ET03, ET07 |
| `city` | object | 34.6% | Addis Ababa, Adama, Hawassa |
| `kebele` | object | 11.9% | |
| `status` | object | 0.0% | |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `id` | 1000861.0 | 1092681.0 | 1052325.5114 | 1055482.0 |
| `latitude` | 3.5317 | 14.7229 | 8.9813 | 8.9511 |
| `longitude` | 33.2315 | 47.1221 | 38.516 | 38.4829 |
| `altitude` | -1815.7 | 4180700304.0 | 110732.8086 | 1925.95 |

---

## 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 3iS 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: `city`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/ethiopian-health-facilities) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_ethiopian_health_facilities,
title = {Ethiopia - Health Facilities},
author = {3iS},
year = {2025},
url = {https://data.humdata.org/dataset/ethiopian-health-facilities},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
```

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*