electricsheepafrica/africa-health-facilities-central-african-republic
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---
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
- caf
pretty_name: "Central African Republic Healthsites"
dataset_info:
splits:
- name: train
num_examples: 344
- name: test
num_examples: 86
---
# Central African Republic Healthsites
**Publisher:** Global Healthsites Mapping Project · **Source:** [HDX](https://data.humdata.org/dataset/central-african-republic-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: **CAF**.
*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)** | 431 |
| **Columns** | 17 (6 numeric, 10 categorical, 0 datetime) |
| **Train split** | 344 rows |
| **Test split** | 86 rows |
| **Geographic scope** | CAF |
| **Publisher** | Global Healthsites Mapping Project |
| **HDX last updated** | 2025-10-15 |
---
## Variables
**Geographic** — `x` (range 14.7912–25.1057), `y` (range 3.9207–10.2791), `osm_type` (way, node), `amenity` (hospital, doctors, clinic), `operator_type` (government, private, NGO) and 1 others.
**Temporal** — `changeset_timestamp`.
**Identifier / Metadata** — `osm_id` (range 188499972.0–11966306669.0), `name` (Institut Pasteur, Centre de Santé de Wantiguere, Enfant Jésus Yole), `source` (UNICEF, UNICEF,2012, Bing;UNICEF), `changeset_id` (range 15502222.0–168849082.0), `uuid` (de785a944cc043ec976bd4d95881f832, 045d930bb56b4965947572371fe65f88, 44ef8b2771f64820801bfe73747088b1) and 2 others.
**Other** — `completeness` (range 6.25–28.125), `healthcare` (hospital, doctor, clinic), `changeset_version` (range 1.0–12.0).
---
## Quick Start
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-health-facilities-central-african-republic")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()
```
---
## Schema
| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `x` | float64 | 53.6% | 14.7912 – 25.1057 (mean 17.8836) |
| `y` | float64 | 53.6% | 3.9207 – 10.2791 (mean 5.9205) |
| `osm_id` | int64 | 0.0% | 188499972.0 – 11966306669.0 (mean 1785364103.9188) |
| `osm_type` | object | 0.0% | way, node |
| `completeness` | float64 | 0.0% | 6.25 – 28.125 (mean 18.3657) |
| `amenity` | object | 0.5% | hospital, doctors, clinic |
| `healthcare` | object | 57.1% | hospital, doctor, clinic |
| `name` | object | 2.1% | Institut Pasteur, Centre de Santé de Wantiguere, Enfant Jésus Yole |
| `source` | object | 17.9% | UNICEF, UNICEF,2012, Bing;UNICEF |
| `operator_type` | object | 21.8% | government, private, NGO |
| `addr_city` | object | 26.2% | Bossangoa, Berbérati, Carnot |
| `changeset_id` | int64 | 0.0% | 15502222.0 – 168849082.0 (mean 97884310.0418) |
| `changeset_version` | int64 | 0.0% | 1.0 – 12.0 (mean 3.3527) |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | |
| `uuid` | object | 0.0% | de785a944cc043ec976bd4d95881f832, 045d930bb56b4965947572371fe65f88, 44ef8b2771f64820801bfe73747088b1 |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-20 |
---
## Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `x` | 14.7912 | 25.1057 | 17.8836 | 17.4539 |
| `y` | 3.9207 | 10.2791 | 5.9205 | 5.9514 |
| `osm_id` | 188499972.0 | 11966306669.0 | 1785364103.9188 | 785811793.0 |
| `completeness` | 6.25 | 28.125 | 18.3657 | 18.75 |
| `changeset_id` | 15502222.0 | 168849082.0 | 97884310.0418 | 88789830.0 |
| `changeset_version` | 1.0 | 12.0 | 3.3527 | 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`. 20 column(s) with >80% missing values were removed: `operator`, `speciality`, `operational_status`, `opening_hours`, `beds`, `staff_doctors`.... 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`, `operator_type`, `addr_city`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/central-african-republic-healthsites) for the publisher's own methodology notes and caveats.
---
## Citation
```bibtex
@dataset{hdx_africa_health_facilities_central_african_republic,
title = {Central African Republic Healthsites},
author = {Global Healthsites Mapping Project},
year = {2025},
url = {https://data.humdata.org/dataset/central-african-republic-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:
- 现有资源采集
language:
- 英语（English）
license:
- 其他
multilinguality:
- 单语言
size_categories:
- 样本数少于1000
source_datasets:
- 原创数据集
task_categories:
- 表格分类（tabular-classification）
task_ids:
- 无
tags:
- 非洲
- 人道主义
- HDX（Humanitarian Data Exchange，人道主义数据交换平台）
- Electric Sheep Africa
- 医疗机构
- HXL（Humanitarian Exchange Language，人道主义交换语言）
- CAF（Central African Republic，中非共和国）
pretty_name: "中非共和国医疗机构点位（Central African Republic Healthsites）"
dataset_info:
splits:
- name: 训练集
num_examples: 344
- name: 测试集
num_examples: 86
# 中非共和国医疗机构点位（Central African Republic Healthsites）
**发布方**：全球医疗机构测绘项目（Global Healthsites Mapping Project） · **数据源**：[HDX（Humanitarian Data Exchange，人道主义数据交换平台）](https://data.humdata.org/dataset/central-african-republic-healthsites) · **许可证**：`ODbL` · **更新时间**：2025-10-15
---
## 摘要
本数据集收录了正在运营的医疗机构清单，包含的属性字段有：名称、医疗机构性质、开展业务、纬度、经度。
数据集中每一行均为一条表格记录。本数据集最后一次在HDX平台更新的时间为2025年10月15日，地理覆盖范围：**CAF（Central African Republic，中非共和国）**。
*本数据集已由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为适配机器学习的Parquet格式。*
---
## 数据集特征
| | |
|---|---|
| **领域** | 公共卫生 |
| **观测单元** | 表格记录 |
| **总记录数** | 431条 |
| **字段数** | 17个（6个数值型、10个分类型、0个日期时间型） |
| **训练集样本数** | 344条 |
| **测试集样本数** | 86条 |
| **地理覆盖范围** | CAF（Central African Republic，中非共和国） |
| **发布方** | 全球医疗机构测绘项目（Global Healthsites Mapping Project） |
| **HDX平台最后更新时间** | 2025-10-15 |
---
## 字段分类
**地理类字段**：`x`（取值范围14.7912–25.1057）、`y`（取值范围3.9207–10.2791）、`osm_type`（OpenStreetMap（OSM，开放街道地图）类型，取值为way、node）、`amenity`（公共设施类型，取值为hospital、doctors、clinic）、`operator_type`（运营方类型，取值为government、private、NGO（Non-Governmental Organization，非政府组织））及其他1个字段。
**时间类字段**：`changeset_timestamp`（变更集时间戳）。
**标识/元数据字段**：`osm_id`（OSM标识，取值范围188499972.0–11966306669.0）、`name`（医疗机构名称，示例值：Institut Pasteur、Centre de Santé de Wantiguere、Enfant Jésus Yole）、`source`（数据来源，示例值：UNICEF（United Nations Children's Fund，联合国儿童基金会）、UNICEF,2012, Bing;UNICEF）、`changeset_id`（变更集标识，取值范围15502222.0–168849082.0）、`uuid`（通用唯一识别码，示例值：de785a944cc043ec976bd4d95881f832、045d930bb56b4965947572371fe65f88、44ef8b2771f64820801bfe73747088b1）及其他2个字段。
**其他字段**：`completeness`（数据完整度，取值范围6.25–28.125）、`healthcare`（医疗服务类型，取值为hospital、doctor、clinic）、`changeset_version`（变更集版本，取值范围1.0–12.0）。
---
## 快速上手
python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-health-facilities-central-african-republic")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()
---
## 数据结构
| 字段名 | 数据类型 | 缺失率 | 取值范围/示例值 |
|---|---|---|---|
| `x` | float64 | 53.6% | 14.7912 – 25.1057（均值 17.8836） |
| `y` | float64 | 53.6% | 3.9207 – 10.2791（均值 5.9205） |
| `osm_id` | int64 | 0.0% | 188499972.0 – 11966306669.0（均值 1785364103.9188） |
| `osm_type` | object | 0.0% | way、node |
| `completeness` | float64 | 0.0% | 6.25 – 28.125（均值 18.3657） |
| `amenity` | object | 0.5% | hospital、doctors、clinic |
| `healthcare` | object | 57.1% | hospital、doctor、clinic |
| `name` | object | 2.1% | Institut Pasteur、Centre de Santé de Wantiguere、Enfant Jésus Yole |
| `source` | object | 17.9% | UNICEF、UNICEF,2012, Bing;UNICEF |
| `operator_type` | object | 21.8% | government、private、NGO |
| `addr_city` | object | 26.2% | Bossangoa、Berbérati、Carnot |
| `changeset_id` | int64 | 0.0% | 15502222.0 – 168849082.0（均值 97884310.0418） |
| `changeset_version` | int64 | 0.0% | 1.0 – 12.0（均值 3.3527） |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | 无 |
| `uuid` | 字符串型 | 0.0% | de785a944cc043ec976bd4d95881f832、045d930bb56b4965947572371fe65f88、44ef8b2771f64820801bfe73747088b1 |
| `esa_source` | 字符串型 | 0.0% | HDX |
| `esa_processed` | 字符串型 | 0.0% | 2026-04-20 |
---
## 数值型字段统计
| 字段名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `x` | 14.7912 | 25.1057 | 17.8836 | 17.4539 |
| `y` | 3.9207 | 10.2791 | 5.9205 | 5.9514 |
| `osm_id` | 188499972.0 | 11966306669.0 | 1785364103.9188 | 785811793.0 |
| `completeness` | 6.25 | 28.125 | 18.3657 | 18.75 |
| `changeset_id` | 15502222.0 | 168849082.0 | 97884310.0418 | 88789830.0 |
| `changeset_version` | 1.0 | 12.0 | 3.3527 | 3.0 |
---
## 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。字段名统一转换为小写并采用蛇形命名法（snake_case）进行标准化。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20个缺失率超过80%的字段：`operator`、`speciality`、`operational_status`、`opening_hours`、`beds`、`staff_doctors`等。根据解析成功率（阈值为85%），将1个字段从字符串型转换为数值型或日期时间型。本数据集以固定随机种子（42）按照80/20的比例划分为训练集与测试集，并以Snappy压缩的Parquet格式存储。
---
## 数据集局限性
- 本数据集源自全球医疗机构测绘项目，尚未由Electric Sheep Africa（ESA）进行独立验证。
- 自动化数据清洗无法修正原始数据集中的错误上报值、定义不一致或采样偏差问题。
- 以下字段的缺失率超过20%，在建模过程中需谨慎使用：`x`、`y`、`healthcare`、`operator_type`、`addr_city`。
- 如需了解发布方的方法论说明与免责条款，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/central-african-republic-healthsites)。
---
## 引用格式
bibtex
@dataset{hdx_africa_health_facilities_central_african_republic,
title = {Central African Republic Healthsites},
author = {Global Healthsites Mapping Project},
year = {2025},
url = {https://data.humdata.org/dataset/central-african-republic-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提供商，总部位于尼日利亚拉各斯。*
提供机构：
electricsheepafrica
