electricsheepafrica/africa-health-facilities-sudan
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--- 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 - sdn pretty_name: "Sudan Healthsites" dataset_info: splits: - name: train num_examples: 1140 - name: test num_examples: 285 --- # Sudan Healthsites **Publisher:** Global Healthsites Mapping Project · **Source:** [HDX](https://data.humdata.org/dataset/sudan-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: **SDN**. *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)** | 1,425 | | **Columns** | 15 (6 numeric, 8 categorical, 0 datetime) | | **Train split** | 1,140 rows | | **Test split** | 285 rows | | **Geographic scope** | SDN | | **Publisher** | Global Healthsites Mapping Project | | **HDX last updated** | 2025-10-15 | --- ## Variables **Geographic** — `x` (range 22.1589–37.2254), `y` (range 9.9746–20.7487), `osm_type` (node, way), `amenity` (pharmacy, hospital, clinic). **Temporal** — `changeset_timestamp`. **Identifier / Metadata** — `osm_id` (range 5773443.0–13186644832.0), `name` (صيدلية علياء, المركز الصحي, صيدلية الاول), `changeset_id` (range 15833692.0–173157154.0), `uuid` (87ceb4cfc61c4a01829fb323b0a4f63f, 9b52124e8d4244f2b645a065a8d677f1, 956454c5449842519512f6fc5724dce5), `esa_source` (HDX) and 1 others. **Other** — `completeness` (range 6.25–31.25), `healthcare` (pharmacy, hospital, clinic), `dispensing` (yes, no), `changeset_version` (range 1.0–10.0). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-health-facilities-sudan") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `x` | float64 | 21.3% | 22.1589 – 37.2254 (mean 32.3614) | | `y` | float64 | 21.3% | 9.9746 – 20.7487 (mean 15.4739) | | `osm_id` | int64 | 0.0% | 5773443.0 – 13186644832.0 (mean 5609771368.5242) | | `osm_type` | object | 0.0% | node, way | | `completeness` | float64 | 0.0% | 6.25 – 31.25 (mean 12.7697) | | `amenity` | object | 0.9% | pharmacy, hospital, clinic | | `healthcare` | object | 38.7% | pharmacy, hospital, clinic | | `name` | object | 5.3% | صيدلية علياء, المركز الصحي, صيدلية الاول | | `dispensing` | object | 77.4% | yes, no | | `changeset_id` | int64 | 0.0% | 15833692.0 – 173157154.0 (mean 99357921.047) | | `changeset_version` | int64 | 0.0% | 1.0 – 10.0 (mean 1.7361) | | `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | | | `uuid` | object | 0.0% | 87ceb4cfc61c4a01829fb323b0a4f63f, 9b52124e8d4244f2b645a065a8d677f1, 956454c5449842519512f6fc5724dce5 | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-20 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `x` | 22.1589 | 37.2254 | 32.3614 | 32.5302 | | `y` | 9.9746 | 20.7487 | 15.4739 | 15.5989 | | `osm_id` | 5773443.0 | 13186644832.0 | 5609771368.5242 | 6833721514.0 | | `completeness` | 6.25 | 31.25 | 12.7697 | 12.5 | | `changeset_id` | 15833692.0 | 173157154.0 | 99357921.047 | 80090679.0 | | `changeset_version` | 1.0 | 10.0 | 1.7361 | 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`. 22 column(s) with >80% missing values were removed: `operator`, `source`, `speciality`, `operator_type`, `operational_status`, `opening_hours`.... 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`, `dispensing`. - Refer to the [original HDX dataset page](https://data.humdata.org/dataset/sudan-healthsites) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_health_facilities_sudan, title = {Sudan Healthsites}, author = {Global Healthsites Mapping Project}, year = {2025}, url = {https://data.humdata.org/dataset/sudan-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: 现有资源采集 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、HXL、苏丹（SDN） pretty_name: "苏丹医疗站点" dataset_info: 划分方式: - 名称: 训练集 样本数: 1140 - 名称: 测试集 样本数: 285 --- # 苏丹医疗站点 **发布方：** 全球医疗站点测绘项目（Global Healthsites Mapping Project） · **来源：** [HDX（Humanitarian Data Exchange，人道主义数据交换平台）](https://data.humdata.org/dataset/sudan-healthsites) · **许可证：** `ODbL` · **更新时间：** 2025-10-15 --- ## 摘要 本数据集收录了苏丹境内所有运营中的医疗设施列表，包含的属性包括：设施名称、设施类型、服务活动、纬度、经度。 数据集中每一行均代表一条独立的表格记录。该数据最近一次在HDX平台的更新时间为2025年10月15日。地理覆盖范围：**苏丹（SDN）**。 *本数据集已由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为适用于机器学习的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** | 1425条 | | **字段数** | 15个（6个数值型、8个分类型、0个日期时间型） | | **训练集划分** | 1140条记录 | | **测试集划分** | 285条记录 | | **地理覆盖范围** | 苏丹（SDN） | | **发布方** | 全球医疗站点测绘项目 | | **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22.1589–37.2254）、`y`（纬度，取值范围9.9746–20.7487）、`osm_type`（OpenStreetMap，OSM 类型：节点、道路）、`amenity`（公共服务设施类型：药房、医院、诊所）。 **时间类变量** — `changeset_timestamp`（变更集时间戳）。 **标识符与元数据类变量** — `osm_id`（OSM 标识符，取值范围5773443.0–13186644832.0）、`name`（设施名称，示例：صيدلية علياء、المركز الصحي、صيدلية الاول，保留阿拉伯语原名）、`changeset_id`（变更集标识符，取值范围15833692.0–173157154.0）、`uuid`（通用唯一标识符，示例：87ceb4cfc61c4a01829fb323b0a4f63f、9b52124e8d4244f2b645a065a8d677f1、956454c5449842519512f6fc5724dce5）、`esa_source`（数据来源：HDX，共1种其他来源）。 **其他类变量** — `completeness`（数据完整度，取值范围6.25–31.25）、`healthcare`（医疗服务类型：药房、医院、诊所）、`dispensing`（是否提供配药服务：是、否）、`changeset_version`（变更集版本，取值范围1.0–10.0）。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-health-facilities-sudan") 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 | 21.3% | 22.1589 – 37.2254（均值32.3614） | | `y` | float64 | 21.3% | 9.9746 – 20.7487（均值15.4739） | | `osm_id` | int64 | 0.0% | 5773443.0 – 13186644832.0（均值5609771368.5242） | | `osm_type` | object | 0.0% | node, way（节点、道路） | | `completeness` | float64 | 0.0% | 6.25 – 31.25（均值12.7697） | | `amenity` | object | 0.9% | pharmacy, hospital, clinic（药房、医院、诊所） | | `healthcare` | object | 38.7% | pharmacy, hospital, clinic（药房、医院、诊所） | | `name` | object | 5.3% | صيدلية علياء, المركز الصحي, صيدلية الاول（保留阿拉伯语原名） | | `dispensing` | object | 77.4% | yes, no（是、否） | | `changeset_id` | int64 | 0.0% | 15833692.0 – 173157154.0（均值99357921.047） | | `changeset_version` | int64 | 0.0% | 1.0 – 10.0（均值1.7361） | | `changeset_timestamp` | datetime64[ns, UTC] | 0.0% | | | `uuid` | object | 0.0% | 87ceb4cfc61c4a01829fb323b0a4f63f, 9b52124e8d4244f2b645a065a8d677f1, 956454c5449842519512f6fc5724dce5 | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-20 | --- ## 数值型变量统计摘要 | 字段名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `x` | 22.1589 | 37.2254 | 32.3614 | 32.5302 | | `y` | 9.9746 | 20.7487 | 15.4739 | 15.5989 | | `osm_id` | 5773443.0 | 13186644832.0 | 5609771368.5242 | 6833721514.0 | | `completeness` | 6.25 | 31.25 | 12.7697 | 12.5 | | `changeset_id` | 15833692.0 | 173157154.0 | 99357921.047 | 80090679.0 | | `changeset_version` | 1.0 | 10.0 | 1.7361 | 1.0 | --- ## 数据整理流程 原始数据通过CKAN（Comprehensive Knowledge Archive Network，综合知识存档网络）应用程序接口从HDX平台下载，并转换为Parquet格式。所有字段名均转换为小写，并统一为蛇形命名规范。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。删除了22个缺失值占比超过80%的字段：`operator`（运营方）、`source`（来源）、`speciality`（专科）、`operator_type`（运营方类型）、`operational_status`（运营状态）、`opening_hours`（开放时间）等。根据解析成功率（阈值为85%），将1个字段从字符串类型转换为数值型或日期时间型。本数据集使用固定随机种子（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。 --- ## 局限性说明 - 本数据集源自全球医疗站点测绘项目，尚未由Electric Sheep Africa进行独立验证。 - 自动化清洗流程无法修正原始数据收集中的错报值、定义不一致或采样偏差问题。 - 以下字段的缺失值占比超过20%，在建模过程中需谨慎使用：`x`、`y`、`healthcare`、`dispensing`。 - 如需查看发布方的官方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/sudan-healthsites)。 --- ## 引用格式 bibtex @dataset{hdx_africa_health_facilities_sudan, title = {Sudan Healthsites}, author = {Global Healthsites Mapping Project}, year = {2025}, url = {https://data.humdata.org/dataset/sudan-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。尼日利亚拉各斯。*
