---
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
- hxl
- dji
pretty_name: "Djibouti Healthsites"
dataset_info:
  splits:
    - name: train
      num_examples: 38
    - name: test
      num_examples: 9
---

# Djibouti Healthsites

**Publisher:** Global Healthsites Mapping Project · **Source:** [HDX](https://data.humdata.org/dataset/djibouti-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: **DJI**.

*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)** | 48 |
| **Columns** | 16 (6 numeric, 9 categorical, 0 datetime) |
| **Train split** | 38 rows |
| **Test split** | 9 rows |
| **Geographic scope** | DJI |
| **Publisher** | Global Healthsites Mapping Project |
| **HDX last updated** | 2025-10-15 |

---

## Variables

**Geographic** — `x` (range 43.0808–43.1525), `y` (range 11.5427–11.5964), `osm_type` (node, way), `amenity` (hospital, pharmacy, clinic), `addr_city` (جيبوتي, Ali Sabieh علي صبيح, بلبالا).

**Temporal** — `changeset_timestamp`.

**Identifier / Metadata** — `osm_id` (range 228050145.0–9371609717.0), `name` (Laboratoire d'analyses médicales Abdan, Service de Santé des Armées خدمة الصحة العسكرية, Pharmacie BSH صيدلية بي إس أيتش), `changeset_id` (range 37442253.0–172509033.0), `uuid` (fd8a4954019143ac8f7a404b73ad2845, 12967dd31dc348828ce7f356252aa4b4, 7efbe13bc2df4074bdafd8035a91dfd5), `esa_source` (HDX) and 1 others.

**Other** — `completeness` (range 6.25–25.0), `healthcare` (hospital, pharmacy, clinic), `operator` (Ministère de la Santé, Dr Guillard, Dr Dell'Aquila, Nicolas Gorgalis), `changeset_version` (range 1.0–8.0).

---

## Quick Start

```python
from datasets import load_dataset

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

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `x` | float64 | 45.8% | 43.0808 – 43.1525 (mean 43.1366) |
| `y` | float64 | 45.8% | 11.5427 – 11.5964 (mean 11.5778) |
| `osm_id` | int64 | 0.0% | 228050145.0 – 9371609717.0 (mean 3015709806.1458) |
| `osm_type` | object | 0.0% | node, way |
| `completeness` | float64 | 0.0% | 6.25 – 25.0 (mean 15.7552) |
| `amenity` | object | 6.2% | hospital, pharmacy, clinic |
| `healthcare` | object | 4.2% | hospital, pharmacy, clinic |
| `name` | object | 10.4% | Laboratoire d'analyses médicales Abdan, Service de Santé des Armées خدمة الصحة العسكرية, Pharmacie BSH صيدلية بي إس أيتش |
| `operator` | object | 72.9% | Ministère de la Santé, Dr Guillard, Dr Dell'Aquila, Nicolas Gorgalis |
| `addr_city` | object | 47.9% | جيبوتي, Ali Sabieh علي صبيح, بلبالا |
| `changeset_id` | int64 | 0.0% | 37442253.0 – 172509033.0 (mean 100585750.0208) |
| `changeset_version` | int64 | 0.0% | 1.0 – 8.0 (mean 3.4792) |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% |  |
| `uuid` | object | 0.0% | fd8a4954019143ac8f7a404b73ad2845, 12967dd31dc348828ce7f356252aa4b4, 7efbe13bc2df4074bdafd8035a91dfd5 |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-20 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `x` | 43.0808 | 43.1525 | 43.1366 | 43.146 |
| `y` | 11.5427 | 11.5964 | 11.5778 | 11.59 |
| `osm_id` | 228050145.0 | 9371609717.0 | 3015709806.1458 | 3691941118.5 |
| `completeness` | 6.25 | 25.0 | 15.7552 | 15.625 |
| `changeset_id` | 37442253.0 | 172509033.0 | 100585750.0208 | 83020145.5 |
| `changeset_version` | 1.0 | 8.0 | 3.4792 | 3.0 |

---

## 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`. 21 column(s) with >80% missing values were removed: `source`, `speciality`, `operator_type`, `operational_status`, `opening_hours`, `beds`.... 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`, `operator`, `addr_city`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/djibouti-healthsites) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_health_facilities_djibouti,
  title     = {Djibouti Healthsites},
  author    = {Global Healthsites Mapping Project},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/djibouti-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.*