electricsheepafrica/africa-health-facilities-rwanda

---
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
- rwa
pretty_name: "Rwanda Healthsites"
dataset_info:
splits:
- name: train
num_examples: 1076
- name: test
num_examples: 269
---

# Rwanda Healthsites

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

*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)** | 1,345 |
| **Columns** | 13 (6 numeric, 6 categorical, 0 datetime) |
| **Train split** | 1,076 rows |
| **Test split** | 269 rows |
| **Geographic scope** | RWA |
| **Publisher** | Global Healthsites Mapping Project |
| **HDX last updated** | 2025-10-15 |

---

## Variables

**Geographic** — `x` (range 28.8744–30.8256), `y` (range -2.7804–-1.1254), `osm_type` (node, way), `loc_amenity` (hospital, pharmacy, clinic).

**Temporal** — `changeset_timestamp`.

**Identifier / Metadata** — `osm_id` (range 151366969.0–12958827069.0), `loc_name` (Murambi Health Centre, Nyamiyaga Health Centre, Rite Pharmacy), `changeset_id` (range 8997714.0–173080134.0), `meta_id` (6c3ce060a4da462b92d92c943e91182a, 93aea201b3ac4d83854ada4b9bdd2175, 4e7cf43f3afb4664a9cd3b845f71d5e0), `esa_source` (HDX) and 1 others.

**Other** — `completeness` (range 6.25–31.25), `changeset_version` (range 1.0–7.0).

---

## Quick Start

```python
from datasets import load_dataset

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

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `x` | float64 | 7.7% | 28.8744 – 30.8256 (mean 29.9191) |
| `y` | float64 | 7.7% | -2.7804 – -1.1254 (mean -1.9862) |
| `osm_id` | int64 | 0.0% | 151366969.0 – 12958827069.0 (mean 11606659655.9532) |
| `osm_type` | object | 0.0% | node, way |
| `completeness` | float64 | 0.0% | 6.25 – 31.25 (mean 10.4949) |
| `loc_amenity` | object | 0.8% | hospital, pharmacy, clinic |
| `loc_name` | object | 4.1% | Murambi Health Centre, Nyamiyaga Health Centre, Rite Pharmacy |
| `changeset_id` | int64 | 0.0% | 8997714.0 – 173080134.0 (mean 159722663.9695) |
| `changeset_version` | int64 | 0.0% | 1.0 – 7.0 (mean 1.1323) |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | |
| `meta_id` | object | 0.0% | 6c3ce060a4da462b92d92c943e91182a, 93aea201b3ac4d83854ada4b9bdd2175, 4e7cf43f3afb4664a9cd3b845f71d5e0 |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-20 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `x` | 28.8744 | 30.8256 | 29.9191 | 30.059 |
| `y` | -2.7804 | -1.1254 | -1.9862 | -1.9582 |
| `osm_id` | 151366969.0 | 12958827069.0 | 11606659655.9532 | 12950467407.0 |
| `completeness` | 6.25 | 31.25 | 10.4949 | 9.375 |
| `changeset_id` | 8997714.0 | 173080134.0 | 159722663.9695 | 168068019.0 |
| `changeset_version` | 1.0 | 7.0 | 1.1323 | 1.0 |

---

## 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`. 24 column(s) with >80% missing values were removed: `meta_healthcare`, `meta_operator`, `geo_bounds_url`, `meta_speciality`, `meta_operator_type`, `contact_phone`.... 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.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/rwanda-healthsites) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_health_facilities_rwanda,
title = {Rwanda Healthsites},
author = {Global Healthsites Mapping Project},
year = {2025},
url = {https://data.humdata.org/dataset/rwanda-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（no-annotation）
language_creators:
- 获取型（found）
language:
- 英语（en）
license:
- 其他（other）
multilinguality:
- 单语言（monolingual）
size_categories:
- 1000<n<10000
source_datasets:
- 原创（original）
task_categories:
- 表格分类（tabular-classification）
task_ids: []
tags:
- 非洲（africa）
- 人道主义（humanitarian）
- HDX（Humanitarian Data Exchange）
- Electric Sheep Africa（electric-sheep-africa）
- 医疗设施（health-facilities）
- HXL（HXL）
- 卢旺达（rwa）
pretty_name: "卢旺达医疗站点（Rwanda Healthsites）"
dataset_info:
splits:
- name: train
num_examples: 1076
- name: test
num_examples: 269

---

# 卢旺达医疗站点

**发布者：** 全球医疗站点映射项目 · **来源：** [HDX](https://data.humdata.org/dataset/rwanda-healthsites) · **授权协议：** `ODbL` · **更新日期：** 2025-10-15

---

## 摘要

本数据集收录了卢旺达境内所有运营中医疗设施的列表，包含以下属性：设施名称、设施性质、服务活动、纬度（Lat）、经度（Long）。数据集中每一行均代表一条标准化表格记录。该数据最后一次在HDX平台更新的时间为2025年10月15日。地理覆盖范围：**卢旺达（RWA）**。
本数据集已由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为可供机器学习使用的Parquet格式（Parquet）。

---

## 数据集特征

| | |
|---|---|
| **领域** | 公共卫生 |
| **观测单元** | 表格记录 |
| **总记录数** | 1345条 |
| **字段数** | 13个（6个数值型、6个分类型、0个日期时间型） |
| **训练集划分** | 1076条 |
| **测试集划分** | 269条 |
| **地理覆盖范围** | 卢旺达（RWA） |
| **发布者** | 全球医疗站点映射项目 |
| **HDX最后更新时间** | 2025-10-15 |

---

## 字段分类

**地理类** — `x`（取值范围28.8744–30.8256）、`y`（取值范围-2.7804–-1.1254）、`osm_type`（OpenStreetMap类型，osm_type）、`loc_amenity`（设施类型，取值为医院、药房、诊所）。
**时间类** — `changeset_timestamp`（变更集时间戳，changeset_timestamp）。
**标识符/元数据类** — `osm_id`（OpenStreetMap标识符，osm_id，取值范围151366969.0–12958827069.0）、`loc_name`（设施名称，示例：Murambi Health Centre、Nyamiyaga Health Centre、Rite Pharmacy）、`changeset_id`（变更集标识符，changeset_id，取值范围8997714.0–173080134.0）、`meta_id`（元数据标识符，meta_id，示例：6c3ce060a4da462b92d92c943e91182a、93aea201b3ac4d83854ada4b9bdd2175、4e7cf43f3afb4664a9cd3b845f71d5e0）、`esa_source`（数据来源，取值为HDX）及其他1个字段。
**其他类** — `completeness`（数据完整度，completeness，取值范围6.25–31.25）、`changeset_version`（变更集版本，changeset_version，取值范围1.0–7.0）。

---

## 快速上手

python
from datasets import load_dataset

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

print(train.shape)
train.head()

---

## 字段结构

| 字段名 | 数据类型 | 缺失率 | 取值范围/示例值 |
|---|---|---|---|
| `x` | float64 | 7.7% | 28.8744 – 30.8256（均值29.9191） |
| `y` | float64 | 7.7% | -2.7804 – -1.1254（均值-1.9862） |
| `osm_id` | int64 | 0.0% | 151366969.0 – 12958827069.0（均值11606659655.9532） |
| `osm_type` | object | 0.0% | 节点、道路 |
| `completeness` | float64 | 0.0% | 6.25 – 31.25（均值10.4949） |
| `loc_amenity` | object | 0.8% | 医院、药房、诊所 |
| `loc_name` | object | 4.1% | 示例：Murambi Health Centre、Nyamiyaga Health Centre、Rite Pharmacy |
| `changeset_id` | int64 | 0.0% | 8997714.0 – 173080134.0（均值159722663.9695） |
| `changeset_version` | int64 | 0.0% | 1.0 – 7.0（均值1.1323） |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | 无 |
| `meta_id` | object | 0.0% | 示例：6c3ce060a4da462b92d92c943e91182a、93aea201b3ac4d83854ada4b9bdd2175、4e7cf43f3afb4664a9cd3b845f71d5e0 |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 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` | 28.8744 | 30.8256 | 29.9191 | 30.059 |
| `y` | -2.7804 | -1.1254 | -1.9862 | -1.9582 |
| `osm_id` | 151366969.0 | 12958827069.0 | 11606659655.9532 | 12950467407.0 |
| `completeness` | 6.25 | 31.25 | 10.4949 | 9.375 |
| `changeset_id` | 8997714.0 | 173080134.0 | 159722663.9695 | 168068019.0 |
| `changeset_version` | 1.0 | 7.0 | 1.1323 | 1.0 |

---

## 数据整理流程

原始数据通过CKAN应用程序编程接口（CKAN API）从HDX平台下载，并转换为Parquet格式。将所有字段名转为小写并统一为蛇形命名法（snake_case）。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24个缺失值占比超过80%的字段：`meta_healthcare`、`meta_operator`、`geo_bounds_url`、`meta_speciality`、`meta_operator_type`、`contact_phone`……根据解析成功率阈值（>85%），将1个字段从字符串类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，并保存为Snappy压缩（Snappy）的Parquet格式。

---

## 局限性

- 本数据源自全球医疗站点映射项目，未经过Electric Sheep Africa的独立验证。
- 自动化清洗无法修正原始数据收集中的错误上报值、定义不一致或采样偏差问题。
- 如需查看发布方的方法说明与免责声明，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/rwanda-healthsites)。

---

## 引用格式

bibtex
@dataset{hdx_africa_health_facilities_rwanda,
title = {卢旺达医疗站点},
author = {Global Healthsites Mapping Project},
year = {2025},
url = {https://data.humdata.org/dataset/rwanda-healthsites},
note = {由Electric Sheep Africa重新打包以适配机器学习场景 (https://huggingface.co/electricsheepafrica)}
}

---

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