electricsheepafrica/africa-education-congo-dem-rep

该数据集提供了刚果民主共和国医疗和教育服务的空间可及性洞察。它使用免费开放工具（如openrouteservice）和开放数据源（主要是OpenStreetMap）创建。为了评估教育和医疗的可及性，数据集采用旅行时间等时线（表示汽车在给定时间或距离内可到达区域的多边形），并将其与WorldPop人口数据（提供100米分辨率估计）叠加。这样可以计算从医院服务10到120分钟距离内以及从学校5到50公里距离内的人口。分析单位基于geoboundaries国家边界，并在可用时在更细的行政级别（ADM 1-4）上汇总结果。数据结构包括14列：名称（地区或国家名称）、iso（ISO3国家代码）、id（行政单位的唯一标识符）、country（ISO3国家代码）、admin_level（行政级别）、category（服务类别：教育、医院或初级医疗）、range_type（捕获区方法：距离或时间）、range（距离（米）或时间（秒））、population（指定范围内的总人口）、school_age_population（范围内的学龄人口数）、school_age_population_share（学龄人口累计百分比）、school_age_population_interval（当前距离带新增的学龄人口）、school_age_population_interval_share（当前区间新学龄人口比例）、population_share（总人口累计百分比）、population_interval（当前距离带新增人口）、population_interval_share（当前区间人口占总人口比例）。数据集包含3,568行，分为2,854行训练集和713行测试集，用于表格分类、回归或其他任务，聚焦非洲、人道主义、教育、医疗设施和交通等领域。

This dataset provides insights into spatial accessibility to healthcare and education services across Democratic Republic of the Congo. It has been created using free and open tools such as openrouteservice and open data sources, primarily OpenStreetMap (OSM). To assess accessibility to education and healthcare, we use travel-time isochrones—polygons representing areas reachable within a given time or distance by car. We overlay these isochrones with WorldPop population data, which provides 100m-resolution estimates. This allows us to calculate the population within time intervals from 10 to 120 minutes away from hospital services and distance intervals from 5 to 50 km away from schools. The unit of analysis is defined by geoboundaries country borders, and where available we also summarise results at finer administrative levels (ADM 1–4). The data structure includes columns such as name, iso, id, country, admin_level, category, range_type, range, population, school_age_population, school_age_population_share, school_age_population_interval, school_age_population_interval_share, population_share, population_interval, and population_interval_share. The dataset contains 3,568 rows, split into 2,854 training and 713 test examples, and is intended for tabular classification, regression, or other tasks, with tags including Africa, humanitarian, education, health facilities, and transportation.