electricsheepafrica/africa-health-facilities-tunisia

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: other
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- health-facilities
- hxl
- tun
pretty_name: "Tunisia Healthsites"
dataset_info:
splits:
- name: train
num_examples: 1132
- name: test
num_examples: 283
---

# Tunisia Healthsites

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

*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)** | 1,416 |
| **Columns** | 17 (6 numeric, 10 categorical, 0 datetime) |
| **Train split** | 1,132 rows |
| **Test split** | 283 rows |
| **Geographic scope** | TUN |
| **Publisher** | Global Healthsites Mapping Project |
| **HDX last updated** | 2025-10-15 |

---

## Variables

**Geographic** — `x` (range 8.1287–11.2181), `y` (range 32.8567–37.278), `osm_type` (node, way), `loc_amenity` (pharmacy, hospital, clinic), `addr_city` (صفاقس, تونس, قفصة).

**Temporal** — `changeset_timestamp`.

**Identifier / Metadata** — `osm_id` (range 27944768.0–13160906727.0), `loc_name` (صيدلية الليل, pharmacie de nuit, Pharmacie de nuit), `changeset_id` (range 3101828.0–173251412.0), `meta_id` (1cd96ef5dd3b46de8da71ea48cba1449, a28114cb09df429dbb1e97fa6b505aca, a1bc0329b3bb4a0facadddc6388267a2), `esa_source` (HDX) and 1 others.

**Other** — `completeness` (range 6.25–40.625), `meta_healthcare` (pharmacy, hospital, clinic), `meta_dispensing` (yes, no, صيدلية الزيتوني أيمن), `addr_street` (شارع الحبيب بورقيبة, شارع الجمهورية, شارع البيئة), `changeset_version` (range 1.0–22.0).

---

## Quick Start

```python
from datasets import load_dataset

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

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `x` | float64 | 21.7% | 8.1287 – 11.2181 (mean 10.3474) |
| `y` | float64 | 21.7% | 32.8567 – 37.278 (mean 35.8838) |
| `osm_id` | int64 | 0.0% | 27944768.0 – 13160906727.0 (mean 4758789791.5332) |
| `osm_type` | object | 0.0% | node, way |
| `completeness` | float64 | 0.0% | 6.25 – 40.625 (mean 14.8393) |
| `loc_amenity` | object | 2.8% | pharmacy, hospital, clinic |
| `meta_healthcare` | object | 33.7% | pharmacy, hospital, clinic |
| `loc_name` | object | 23.2% | صيدلية الليل, pharmacie de nuit, Pharmacie de nuit |
| `meta_dispensing` | object | 75.1% | yes, no, صيدلية الزيتوني أيمن |
| `addr_street` | object | 73.3% | شارع الحبيب بورقيبة, شارع الجمهورية, شارع البيئة |
| `addr_city` | object | 72.1% | صفاقس, تونس, قفصة |
| `changeset_id` | int64 | 0.0% | 3101828.0 – 173251412.0 (mean 104883194.9195) |
| `changeset_version` | int64 | 0.0% | 1.0 – 22.0 (mean 3.3496) |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | |
| `meta_id` | object | 0.0% | 1cd96ef5dd3b46de8da71ea48cba1449, a28114cb09df429dbb1e97fa6b505aca, a1bc0329b3bb4a0facadddc6388267a2 |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-21 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `x` | 8.1287 | 11.2181 | 10.3474 | 10.4497 |
| `y` | 32.8567 | 37.278 | 35.8838 | 36.3995 |
| `osm_id` | 27944768.0 | 13160906727.0 | 4758789791.5332 | 4546695789.5 |
| `completeness` | 6.25 | 40.625 | 14.8393 | 12.5 |
| `changeset_id` | 3101828.0 | 173251412.0 | 104883194.9195 | 104785595.0 |
| `changeset_version` | 1.0 | 22.0 | 3.3496 | 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`. 20 column(s) with >80% missing values were removed: `meta_operator`, `geo_bounds_url`, `meta_speciality`, `meta_operator_type`, `contact_phone`, `status_operational_status`.... 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`, `meta_healthcare`, `loc_name`, `meta_dispensing`, `addr_street`, `addr_city`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/tunisia-healthsites) for the publisher's own methodology notes and caveats.

---

## Citation

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