electricsheepafrica/africa-world-bank-health-indicators-for-guinea

--- annotations_creators: - no-annotation language_creators: - found language: - en license: cc-by-4.0 multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - tabular-classification task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - health - indicators - gin pretty_name: "Guinea - Health" dataset_info: splits: - name: train num_examples: 7736 - name: test num_examples: 1934 --- # Guinea - Health **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-health-indicators-for-guinea) · **License:** `cc-by` · **Updated:** 2026-03-27 --- ## Abstract Contains data from the World Bank's [data portal](http://data.worldbank.org/). There is also a [consolidated country dataset](https://data.humdata.org/dataset/world-bank-combined-indicators-for-guinea) on HDX. Improving health is central to the Millennium Development Goals, and the public sector is the main provider of health care in developing countries. To reduce inequities, many countries have emphasized primary health care, including immunization, sanitation, access to safe drinking water, and safe motherhood initiatives. Data here cover health systems, disease prevention, reproductive health, nutrition, and population dynamics. Data are from the United Nations Population Division, World Health Organization, United Nations Children's Fund, the Joint United Nations Programme on HIV/AIDS, and various other sources. Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **GIN**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Public health | | **Unit of observation** | Country-level aggregates | | **Rows (total)** | 9,670 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 7,736 rows | | **Test split** | 1,934 rows | | **Geographic scope** | GIN | | **Publisher** | World Bank Group | | **HDX last updated** | 2026-03-27 | --- ## Variables **Geographic** — `country_name` (Guinea), `country_iso3` (GIN), `year` (range 1960.0–2025.0). **Outcome / Measurement** — `value` (range -155020.0–14754785.0). **Identifier / Metadata** — `indicator_name` (Net migration, Population ages 0-14, male, Population ages 65 and above, female), `indicator_code` (SM.POP.NETM, SP.POP.0014.MA.IN, SP.POP.65UP.FE.IN), `esa_source` (HDX), `esa_processed` (2026-04-09). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-health-indicators-for-guinea") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `country_name` | object | 0.0% | Guinea | | `country_iso3` | object | 0.0% | GIN | | `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 1999.1007) | | `indicator_name` | object | 0.0% | Net migration, Population ages 0-14, male, Population ages 65 and above, female | | `indicator_code` | object | 0.0% | SM.POP.NETM, SP.POP.0014.MA.IN, SP.POP.65UP.FE.IN | | `value` | float64 | 0.0% | -155020.0 – 14754785.0 (mean 206496.5101) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-09 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1960.0 | 2025.0 | 1999.1007 | 2004.0 | | `value` | -155020.0 | 14754785.0 | 206496.5101 | 27.1 | --- ## 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`. 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 World Bank Group 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/world-bank-health-indicators-for-guinea) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_health_indicators_for_guinea, title = {Guinea - Health}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-health-indicators-for-guinea}, 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: - 现有语料采集 language: - 英语 license: 知识共享署名4.0（cc-by-4.0） multilinguality: - 单语言 size_categories: - 1000 < 数据量 < 10000 source_datasets: - 原创数据集 task_categories: - 表格分类（tabular-classification） task_ids: [] tags: - 非洲 - 人道主义 - HDX - Electric Sheep Africa - 健康 - 指标 - GIN pretty_name: "几内亚 - 健康指标" dataset_info: splits: - name: 训练集 num_examples: 7736 - name: 测试集 num_examples: 1934 # 几内亚 - 健康指标 **发布方：** 世界银行集团（World Bank Group） · **来源：** [人道主义数据交换（HDX）](https://data.humdata.org/dataset/world-bank-health-indicators-for-guinea) · **授权协议：** `cc-by` · **最后更新时间：** 2026-03-27 ## 摘要 本数据集包含源自世界银行[数据门户（data portal）](http://data.worldbank.org/)的数据。此外，人道主义数据交换（HDX）平台上还提供了一份[几内亚综合国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-guinea)。 改善健康状况是千年发展目标的核心内容，而在发展中国家，公共部门是医疗服务的主要供给方。为减少健康公平性差距，诸多国家均将重点放在初级医疗保健领域，包括免疫接种、环境卫生保障、安全饮用水获取以及孕产妇安全相关举措。本数据集涵盖医疗体系、疾病预防、生殖健康、营养与人口动态相关数据，数据来源包括联合国人口司、世界卫生组织（World Health Organization）、联合国儿童基金会（United Nations Children's Fund）、联合国艾滋病规划署（Joint United Nations Programme on HIV/AIDS）以及其他诸多渠道。 本数据集的每一行均代表国家级汇总数据。本数据集在人道主义数据交换（HDX）平台的最后更新时间为2026年3月27日，地理覆盖范围：**GIN**。 *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（Parquet）。* ## 数据集特征 | | | |---|---| | **领域** | 公共卫生（Public health） | | **观测单元** | 国家级汇总数据 | | **总行数** | 9670 | | **列数** | 8列（2个数值型、6个分类型、0个日期时间型） | | **训练集划分** | 7736行 | | **测试集划分** | 1934行 | | **地理覆盖范围** | GIN | | **发布方** | 世界银行集团（World Bank Group） | | **HDX平台最后更新时间** | 2026年3月27日 | ## 变量说明 **地理类变量** — `country_name`（国家名称：几内亚）、`country_iso3`（国家ISO3代码：GIN）、`year`（年份：范围1960.0–2025.0）。 **结果/测量类变量** — `value`（指标数值：范围-155020.0–14754785.0）。 **标识符/元数据类变量** — `indicator_name`（指标名称：净移民、0-14岁男性人口、65岁及以上女性人口）、`indicator_code`（指标代码：SM.POP.NETM、SP.POP.0014.MA.IN、SP.POP.65UP.FE.IN）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-09）。 ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-health-indicators-for-guinea") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ## 数据模式 | 列名 | 数据类型 | 空值占比 | 取值范围/示例值 | |---|---|---|---| | `country_name` | 字符型（object） | 0.0% | 几内亚 | | `country_iso3` | 字符型（object） | 0.0% | GIN | | `year` | 64位整型（int64） | 0.0% | 1960.0 – 2025.0（均值：1999.1007） | | `indicator_name` | 字符型（object） | 0.0% | 净移民、0-14岁男性人口、65岁及以上女性人口 | | `indicator_code` | 字符型（object） | 0.0% | SM.POP.NETM, SP.POP.0014.MA.IN, SP.POP.65UP.FE.IN | | `value` | 64位浮点型（float64） | 0.0% | -155020.0 – 14754785.0（均值：206496.5101） | | `esa_source` | 字符型（object） | 0.0% | HDX | | `esa_processed` | 字符型（object） | 0.0% | 2026-04-09 | ## 数值型变量统计 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `year` | 1960.0 | 2025.0 | 1999.1007 | 2004.0 | | `value` | -155020.0 | 14754785.0 | 206496.5101 | 27.1 | ## 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。列名统一转换为小写并标准化为蛇形命名法（snake_case）。常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）均被统一替换为`NaN`。本数据集采用固定随机种子（42）按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。 ## 局限性 - 数据源自世界银行集团，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报值、定义不一致问题或抽样偏差。 - 有关发布方的方法说明与免责条款，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-health-indicators-for-guinea)。 ## 引用格式 bibtex @dataset{hdx_africa_world_bank_health_indicators_for_guinea, title = {Guinea - Health}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-health-indicators-for-guinea}, 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。*