electricsheepafrica/africa-health-facilities-eritrea

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: other
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- health-facilities
- eri
pretty_name: "Eritrea Healthsites"
dataset_info:
splits:
- name: train
num_examples: 28
- name: test
num_examples: 7
---

# Eritrea Healthsites

**Publisher:** Global Healthsites Mapping Project · **Source:** [HDX](https://data.humdata.org/dataset/eritrea-healthsites) · **License:** `ODbL` · **Updated:** 2025-10-15

---

## Abstract

This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long

Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-10-15. Geographic scope: **ERI**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Public health |
| **Unit of observation** | Tabular records |
| **Rows (total)** | 36 |
| **Columns** | 15 (6 numeric, 8 categorical, 0 datetime) |
| **Train split** | 28 rows |
| **Test split** | 7 rows |
| **Geographic scope** | ERI |
| **Publisher** | Global Healthsites Mapping Project |
| **HDX last updated** | 2025-10-15 |

---

## Variables

**Geographic** — `x` (range 38.2353–38.9396), `y` (range 14.6368–17.1095), `osm_type` (way, node), `amenity` (hospital, pharmacy, clinic), `addr_city` (أسمرة, كرن, بارنتو).

**Temporal** — `changeset_timestamp`.

**Identifier / Metadata** — `osm_id` (range 144941432.0–12734115401.0), `name` (ፋርማሲ, Pharmacy No. 5 / صيدلية رقم 5, Halibet Referral Hospital), `changeset_id` (range 53411420.0–167274718.0), `uuid` (5cb0f41dc5fa404589f7285dbd57b9b6, b418bf6196614e30b148481078d70ee1, f5535e8d0ab04d17abf09379385b6d5a), `esa_source` (HDX) and 1 others.

**Other** — `completeness` (range 6.25–18.75), `healthcare` (hospital, pharmacy, clinic), `changeset_version` (range 1.0–8.0).

---

## Quick Start

```python
from datasets import load_dataset

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

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `x` | float64 | 61.1% | 38.2353 – 38.9396 (mean 38.8297) |
| `y` | float64 | 61.1% | 14.6368 – 17.1095 (mean 15.5132) |
| `osm_id` | int64 | 0.0% | 144941432.0 – 12734115401.0 (mean 3277352426.6111) |
| `osm_type` | object | 0.0% | way, node |
| `completeness` | float64 | 0.0% | 6.25 – 18.75 (mean 12.934) |
| `amenity` | object | 0.0% | hospital, pharmacy, clinic |
| `healthcare` | object | 30.6% | hospital, pharmacy, clinic |
| `name` | object | 8.3% | ፋርማሲ, Pharmacy No. 5 / صيدلية رقم 5, Halibet Referral Hospital |
| `addr_city` | object | 52.8% | أسمرة, كرن, بارنتو |
| `changeset_id` | int64 | 0.0% | 53411420.0 – 167274718.0 (mean 106521784.8056) |
| `changeset_version` | int64 | 0.0% | 1.0 – 8.0 (mean 2.8611) |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | |
| `uuid` | object | 0.0% | 5cb0f41dc5fa404589f7285dbd57b9b6, b418bf6196614e30b148481078d70ee1, f5535e8d0ab04d17abf09379385b6d5a |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-20 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `x` | 38.2353 | 38.9396 | 38.8297 | 38.9328 |
| `y` | 14.6368 | 17.1095 | 15.5132 | 15.3381 |
| `osm_id` | 144941432.0 | 12734115401.0 | 3277352426.6111 | 818425933.0 |
| `completeness` | 6.25 | 18.75 | 12.934 | 12.5 |
| `changeset_id` | 53411420.0 | 167274718.0 | 106521784.8056 | 85170511.5 |
| `changeset_version` | 1.0 | 8.0 | 2.8611 | 2.0 |

---

## 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`. 22 column(s) with >80% missing values were removed: `operator`, `source`, `speciality`, `operator_type`, `operational_status`, `opening_hours`.... 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.

---

## Limitations

- Data originates from Global Healthsites Mapping Project 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: `x`, `y`, `healthcare`, `addr_city`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/eritrea-healthsites) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_health_facilities_eritrea,
title = {Eritrea Healthsites},
author = {Global Healthsites Mapping Project},
year = {2025},
url = {https://data.humdata.org/dataset/eritrea-healthsites},
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.*