electricsheepafrica/africa-health-facilities-egypt

---
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
- egy
pretty_name: "Egypt Healthsites"
dataset_info:
splits:
- name: train
num_examples: 1348
- name: test
num_examples: 337
---

# Egypt Healthsites

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

*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)** | 1,686 |
| **Columns** | 14 (6 numeric, 7 categorical, 0 datetime) |
| **Train split** | 1,348 rows |
| **Test split** | 337 rows |
| **Geographic scope** | EGY |
| **Publisher** | Global Healthsites Mapping Project |
| **HDX last updated** | 2025-10-15 |

---

## Variables

**Geographic** — `x` (range 25.1592–35.4111), `y` (range 22.3489–31.5609), `osm_type` (node, way), `loc_amenity` (pharmacy, hospital, clinic).

**Temporal** — `changeset_timestamp`.

**Identifier / Metadata** — `osm_id` (range 28661710.0–13186139479.0), `loc_name` (صيدلية, Clinic, صيدلية العزبي), `changeset_id` (range 814532.0–173280214.0), `meta_id` (ef437516174a4c1bad720924c5b91e72, 70e61b7253834e3790a1fe06bc13a5e6, b8ca99e2ea0b471fb88222599f13f171), `esa_source` (HDX) and 1 others.

**Other** — `completeness` (range 6.25–37.5), `meta_healthcare` (pharmacy, hospital, clinic), `changeset_version` (range 1.0–21.0).

---

## Quick Start

```python
from datasets import load_dataset

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

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `x` | float64 | 17.1% | 25.1592 – 35.4111 (mean 31.5352) |
| `y` | float64 | 17.1% | 22.3489 – 31.5609 (mean 29.2856) |
| `osm_id` | int64 | 0.0% | 28661710.0 – 13186139479.0 (mean 5500568075.2046) |
| `osm_type` | object | 0.0% | node, way |
| `completeness` | float64 | 0.0% | 6.25 – 37.5 (mean 13.1821) |
| `loc_amenity` | object | 2.0% | pharmacy, hospital, clinic |
| `meta_healthcare` | object | 40.5% | pharmacy, hospital, clinic |
| `loc_name` | object | 17.7% | صيدلية, Clinic, صيدلية العزبي |
| `changeset_id` | int64 | 0.0% | 814532.0 – 173280214.0 (mean 108053160.9015) |
| `changeset_version` | int64 | 0.0% | 1.0 – 21.0 (mean 2.4407) |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | |
| `meta_id` | object | 0.0% | ef437516174a4c1bad720924c5b91e72, 70e61b7253834e3790a1fe06bc13a5e6, b8ca99e2ea0b471fb88222599f13f171 |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-20 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `x` | 25.1592 | 35.4111 | 31.5352 | 31.3056 |
| `y` | 22.3489 | 31.5609 | 29.2856 | 30.0319 |
| `osm_id` | 28661710.0 | 13186139479.0 | 5500568075.2046 | 4827467071.5 |
| `completeness` | 6.25 | 37.5 | 13.1821 | 12.5 |
| `changeset_id` | 814532.0 | 173280214.0 | 108053160.9015 | 114007859.0 |
| `changeset_version` | 1.0 | 21.0 | 2.4407 | 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: `meta_healthcare`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/egypt-healthsites) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_health_facilities_egypt,
title = {Egypt Healthsites},
author = {Global Healthsites Mapping Project},
year = {2025},
url = {https://data.humdata.org/dataset/egypt-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:
- 无标注
language_creators:
- 发现式获取
language:
- en
license: 其他
multilinguality:
- 单语言
size_categories:
- 1000<n<10000
source_datasets:
- 原始数据集
task_categories:
- 表格分类
task_ids: []
tags:
- 非洲
- 人道主义
- HXL
- 电羊非洲（Electric Sheep Africa）
- 医疗设施
- HDX
- 埃及（EGY）
pretty_name: "埃及医疗站点"

# 埃及医疗站点

**发布方**：全球医疗站点映射项目 · **来源**：[人道主义数据交换平台（HDX）](https://data.humdata.org/dataset/egypt-healthsites) · **许可证**：`ODbL` · **最后更新**：2025-10-15

---

## 摘要
本数据集收录了埃及境内所有运营中的医疗设施列表，包含的属性有：设施名称、设施性质、服务活动、纬度、经度。
数据集中每一行均为一条独立的表格记录。该数据在HDX平台的最后更新时间为2025-10-15，地理覆盖范围为**埃及（EGY）**。
*本数据集已由[电羊非洲（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 |
| **总数据行数** | 1686 |
| **数据列数** | 14（6个数值型、7个分类型、0个日期时间型） |
| **训练集划分** | 1348行 |
| **测试集划分** | 337行 |
| **地理覆盖范围** | 埃及（EGY） |
| **发布方** | 全球医疗站点映射项目 |
| **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25.1592–35.4111）、`y`（纬度，取值范围22.3489–31.5609）、`osm_type`（开放街道地图类型，取值为节点、路径）、`loc_amenity`（设施类型，取值为药房、医院、诊所）。
### 时间类变量
`changeset_timestamp`（变更集时间戳）。
### 标识符/元数据类变量
`osm_id`（取值范围28661710.0–13186139479.0）、`loc_name`（包含阿拉伯语“صيدلية”（药房）、“Clinic”（诊所）、“صيدلية العزبي”（阿兹比药房）等示例值）、`changeset_id`（取值范围814532.0–173280214.0）、`meta_id`（示例值：ef437516174a4c1bad720924c5b91e72、70e61b7253834e3790a1fe06bc13a5e6、b8ca99e2ea0b471fb88222599f13f171）、`esa_source`（取值为HDX，共1个附加字段）。
### 其他变量
`completeness`（完整性评分，取值范围6.25–37.5）、`meta_healthcare`（医疗属性分类，取值为药房、医院、诊所）、`changeset_version`（变更集版本，取值范围1.0–21.0）。

---

## 快速上手
python
from datasets import load_dataset

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

print(train.shape)
train.head()

---

## 数据结构
| 列名 | 数据类型 | 缺失率 | 取值范围/示例值 |
|---|---|---|---|
| `x` | float64 | 17.1% | 25.1592 – 35.4111（均值31.5352） |
| `y` | float64 | 17.1% | 22.3489 – 31.5609（均值29.2856） |
| `osm_id` | int64 | 0.0% | 28661710.0 – 13186139479.0（均值5500568075.2046） |
| `osm_type` | object | 0.0% | node, way（节点、路径） |
| `completeness` | float64 | 0.0% | 6.25 – 37.5（均值13.1821） |
| `loc_amenity` | object | 2.0% | pharmacy, hospital, clinic（药房、医院、诊所） |
| `meta_healthcare` | object | 40.5% | pharmacy, hospital, clinic（药房、医院、诊所） |
| `loc_name` | object | 17.7% | صيدلية、Clinic、صيدلية العزبي（其中صيدلية译为“药房”） |
| `changeset_id` | int64 | 0.0% | 814532.0 – 173280214.0（均值108053160.9015） |
| `changeset_version` | int64 | 0.0% | 1.0 – 21.0（均值2.4407） |
| `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | |
| `meta_id` | object | 0.0% | ef437516174a4c1bad720924c5b91e72、70e61b7253834e3790a1fe06bc13a5e6、b8ca99e2ea0b471fb88222599f13f171 |
| `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` | 25.1592 | 35.4111 | 31.5352 | 31.3056 |
| `y` | 22.3489 | 31.5609 | 29.2856 | 30.0319 |
| `osm_id` | 28661710.0 | 13186139479.0 | 5500568075.2046 | 4827467071.5 |
| `completeness` | 6.25 | 37.5 | 13.1821 | 12.5 |
| `changeset_id` | 814532.0 | 173280214.0 | 108053160.9015 | 114007859.0 |
| `changeset_version` | 1.0 | 21.0 | 2.4407 | 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。对列名进行了小写转换与蛇形命名法标准化处理；将常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。移除了23列缺失值占比超过80%的字段，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压缩的Parquet格式。

---

## 数据集局限性
- 本数据源自全球医疗站点映射项目，未经过电羊非洲（ESA）的独立验证。
- 自动化清洗流程无法修正原始数据收集中的错报值、定义不一致或抽样偏差问题。
- 以下列的缺失值占比超过20%，在建模过程中需谨慎使用：`meta_healthcare`。
- 如需了解发布方的方法论说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/egypt-healthsites)。

---

## 引用格式
bibtex
@dataset{hdx_africa_health_facilities_egypt,
title = {Egypt Healthsites},
author = {Global Healthsites Mapping Project},
year = {2025},
url = {https://data.humdata.org/dataset/egypt-healthsites},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

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