electricsheepafrica/africa-health-facilities-libya

---
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
- lby
pretty_name: "Libya Healthsites"
dataset_info:
splits:
- name: train
num_examples: 2356
- name: test
num_examples: 589
---

# Libya Healthsites

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

*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)** | 2,945 |
| **Columns** | 14 (6 numeric, 7 categorical, 0 datetime) |
| **Train split** | 2,356 rows |
| **Test split** | 589 rows |
| **Geographic scope** | LBY |
| **Publisher** | Global Healthsites Mapping Project |
| **HDX last updated** | 2025-10-15 |

---

## Variables

**Geographic** — `x` (range 9.4886–25.0499), `y` (range 24.1942–32.9511), `osm_type` (node, way), `loc_amenity` (pharmacy, hospital, clinic).

**Temporal** — `changeset_timestamp`.

**Identifier / Metadata** — `osm_id` (range 95248345.0–13203310815.0), `loc_name` (صيدلية, صيدلية العافية, مستوصف), `changeset_id` (range 7383079.0–173017752.0), `meta_id` (be789d1f90674d6b8d766dd22c0600bf, a7da5963d8f048888777b246f2834637, 2195df6cb88e4cb3a4d3870800036914), `esa_source` (HDX) and 1 others.

**Other** — `completeness` (range 6.25–40.625), `meta_healthcare` (hospital, pharmacy, clinic), `changeset_version` (range 1.0–28.0).

---

## Quick Start

```python
from datasets import load_dataset

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

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `x` | float64 | 26.7% | 9.4886 – 25.0499 (mean 15.0269) |
| `y` | float64 | 26.7% | 24.1942 – 32.9511 (mean 32.1864) |
| `osm_id` | int64 | 0.0% | 95248345.0 – 13203310815.0 (mean 4648923270.1019) |
| `osm_type` | object | 0.0% | node, way |
| `completeness` | float64 | 0.0% | 6.25 – 40.625 (mean 11.7774) |
| `loc_amenity` | object | 0.6% | pharmacy, hospital, clinic |
| `meta_healthcare` | object | 54.0% | hospital, pharmacy, clinic |
| `loc_name` | object | 15.9% | صيدلية, صيدلية العافية, مستوصف |
| `changeset_id` | int64 | 0.0% | 7383079.0 – 173017752.0 (mean 100336788.5929) |
| `changeset_version` | int64 | 0.0% | 1.0 – 28.0 (mean 2.5053) |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | |
| `meta_id` | object | 0.0% | be789d1f90674d6b8d766dd22c0600bf, a7da5963d8f048888777b246f2834637, 2195df6cb88e4cb3a4d3870800036914 |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-20 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `x` | 9.4886 | 25.0499 | 15.0269 | 13.262 |
| `y` | 24.1942 | 32.9511 | 32.1864 | 32.6775 |
| `osm_id` | 95248345.0 | 13203310815.0 | 4648923270.1019 | 4663357790.0 |
| `completeness` | 6.25 | 40.625 | 11.7774 | 9.375 |
| `changeset_id` | 7383079.0 | 173017752.0 | 100336788.5929 | 94670743.0 |
| `changeset_version` | 1.0 | 28.0 | 2.5053 | 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`. 23 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`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/libya-healthsites) for the publisher's own methodology notes and caveats.

---

## Citation

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

annotations_creators: 无注释
language_creators: 现有资源获取
language: 英语
license: 其他
multilinguality: 单语言
size_categories: 1000 < n < 10000
source_datasets: 原创数据集
task_categories: 表格分类
task_ids: 无
tags: 非洲、人道主义、HDX、Electric Sheep Africa、医疗设施、人道主义交换语言（HXL）、LBY
pretty_name: "利比亚医疗设施站点"
dataset_info:
splits:
- name: train
num_examples: 2356
- name: test
num_examples: 589

# 利比亚医疗设施站点

**发布方：全球医疗设施测绘项目（Global Healthsites Mapping Project）** · **来源：** [人道主义数据交换（HDX）](https://data.humdata.org/dataset/libya-healthsites) · **许可证：** `ODbL（开放数据库许可证）` · **更新时间：** 2025-10-15

---

## 摘要

本数据集收录了利比亚境内所有运营中的医疗设施列表，包含的属性字段包括：设施名称、设施类型、开展业务、纬度、经度。数据集中的每一行均代表一条标准化表格记录。数据最近一次在HDX平台的更新时间为2025-10-15，地理覆盖范围为**LBY（利比亚）**。

本数据集已由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为适配机器学习任务的Parquet格式。

---

## 数据集特征

| 指标 | 详情 |
|---|---|
| **领域** | 公共卫生 |
| **观测单元** | 表格记录 |
| **总行数** | 2945 |
| **列数** | 14（6个数值型、7个分类型、0个日期时间型） |
| **训练集样本量** | 2356条 |
| **测试集样本量** | 589条 |
| **地理覆盖范围** | LBY |
| **发布方** | 全球医疗设施测绘项目 |
| **HDX平台最后更新时间** | 2025-10-15 |

---

## 变量说明

**地理类变量** — `x`（经度，取值范围9.4886–25.0499）、`y`（纬度，取值范围24.1942–32.9511）、`osm_type`（OpenStreetMap类型，可选值：节点、道路）、`loc_amenity`（设施类型，可选值：药房、医院、诊所）。

**时间类变量** — `changeset_timestamp`（变更集时间戳）。

**标识符与元数据** — `osm_id`（OpenStreetMap标识符，取值范围95248345.0–13203310815.0）、`loc_name`（设施本地名称，示例值：صيدلية、صيدلية العافية、مستوصف，对应阿拉伯语的药房、健康药房、诊所）、`changeset_id`（变更集标识符，取值范围7383079.0–173017752.0）、`meta_id`（元数据标识符，示例值：be789d1f90674d6b8d766dd22c0600bf、a7da5963d8f048888777b246f2834637、2195df6cb88e4cb3a4d3870800036914）、`esa_source`（数据来源，值为HDX）及其他1个字段。

**其他变量** — `completeness`（数据完整度，取值范围6.25–40.625）、`meta_healthcare`（医疗设施分类，可选值：医院、药房、诊所）、`changeset_version`（变更集版本号，取值范围1.0–28.0）。

---

## 快速上手

python
from datasets import load_dataset

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

print(train.shape)
train.head()

---

## 数据schema

| 列名 | 数据类型 | 缺失率 | 取值范围/示例值 |
|---|---|---|---|
| `x` | float64 | 26.7% | 9.4886 – 25.0499（均值15.0269） |
| `y` | float64 | 26.7% | 24.1942 – 32.9511（均值32.1864） |
| `osm_id` | int64 | 0.0% | 95248345.0 – 13203310815.0（均值4648923270.1019） |
| `osm_type` | object | 0.0% | node, way（节点、道路） |
| `completeness` | float64 | 0.0% | 6.25 – 40.625（均值11.7774） |
| `loc_amenity` | object | 0.6% | pharmacy, hospital, clinic（药房、医院、诊所） |
| `meta_healthcare` | object | 54.0% | hospital, pharmacy, clinic（医院、药房、诊所） |
| `loc_name` | object | 15.9% | صيدلية, صيدلية العافية, مستوصف（阿拉伯语：药房、健康药房、诊所） |
| `changeset_id` | int64 | 0.0% | 7383079.0 – 173017752.0（均值100336788.5929） |
| `changeset_version` | int64 | 0.0% | 1.0 – 28.0（均值2.5053） |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | 无 |
| `meta_id` | object | 0.0% | be789d1f90674d6b8d766dd22c0600bf、a7da5963d8f048888777b246f2834637、2195df6cb88e4cb3a4d3870800036914 |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-20 |

---

## 数值型变量统计摘要

| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `x` | 9.4886 | 25.0499 | 15.0269 | 13.262 |
| `y` | 24.1942 | 32.9511 | 32.1864 | 32.6775 |
| `osm_id` | 95248345.0 | 13203310815.0 | 4648923270.1019 | 4663357790.0 |
| `completeness` | 6.25 | 40.625 | 11.7774 | 9.375 |
| `changeset_id` | 7383079.0 | 173017752.0 | 100336788.5929 | 94670743.0 |
| `changeset_version` | 1.0 | 28.0 | 2.5053 | 2.0 |

---

## 数据整理流程

原始数据通过CKAN API从HDX平台下载，并转换为Parquet格式。对列名进行标准化处理：统一转换为小写并采用蛇形命名法。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。移除了23个缺失值占比超过80%的列，包括`meta_operator`、`geo_bounds_url`、`meta_speciality`、`meta_operator_type`、`contact_phone`、`status_operational_status`等。根据解析成功率阈值（>85%），将1列从字符串类型转换为数值型或日期时间型。本数据集采用固定随机种子（42）按80/20的比例划分为训练集与测试集，并以Snappy压缩格式的Parquet文件保存。

---

## 数据集局限性

- 数据源自全球医疗设施测绘项目，尚未经Electric Sheep Africa独立验证。
- 自动化清洗流程无法修正原始数据收集中的错误报告值、定义不一致或采样偏差问题。
- 以下列的缺失值占比超过20%，在建模时需谨慎使用：`x`、`y`、`meta_healthcare`。
- 如需了解发布方的官方方法说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/libya-healthsites)。

---

## 引用格式

bibtex
@dataset{hdx_africa_health_facilities_libya,
title = {Libya Healthsites},
author = {Global Healthsites Mapping Project},
year = {2025},
url = {https://data.humdata.org/dataset/libya-healthsites},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — 非洲机器学习数据集基础设施平台，尼日利亚拉各斯。*