electricsheepafrica/africa-disability-comoros

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: other
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- disability
- disease
- environment
- health
- hxl
- indicators
- malaria
- maternity
- com
pretty_name: "Comoros - Health Indicators"
dataset_info:
splits:
- name: train
num_examples: 14107
- name: test
num_examples: 3526
---

# Comoros - Health Indicators

**Publisher:** World Health Organization · **Source:** [HDX](https://data.humdata.org/dataset/who-data-for-comoros) · **License:** `hdx-other` · **Updated:** 2025-02-07

---

## Abstract

This dataset contains data from WHO's [data portal](https://www.who.int/gho/en/) covering the following categories:

Air pollution, Antimicrobial resistance (AMR), Assistive technology, Child mortality, Dementia diagnosis, treatment and care, Dementia policy and legislation, Environment and health, Foodborne Diseases Estimates, Global Dementia Observatory (GDO), Global Health Estimates: Life expectancy and leading causes of death and disability, Global Information System on Alcohol and Health, HIV, Health Inequality Monitor, Health financing, Health systems, Health taxes, Health workforce, Hepatitis, Immunization coverage and vaccine-preventable diseases, International Health Regulations (2005) monitoring framework, Malaria, Maternal and reproductive health, Mental health, Neglected tropical diseases, Noncommunicable diseases, Nutrition, Oral Health, Priority health technologies, Resources for Substance Use Disorders, Road Safety, SDG Target 3.8 | Achieve universal health coverage (UHC), Sexually Transmitted Infections, Tobacco control, Tuberculosis, Vaccine-preventable communicable diseases, Violence against women, Violence prevention, Water, sanitation and hygiene (WASH), Women and health, World Health Statistics.

For links to individual indicator metadata, see resource descriptions.

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2025-02-07. Geographic scope: **COM**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Food security and nutrition |
| **Unit of observation** | First-level administrative unit observations |
| **Rows (total)** | 17,634 |
| **Columns** | 19 (6 numeric, 13 categorical, 0 datetime) |
| **Train split** | 14,107 rows |
| **Test split** | 3,526 rows |
| **Geographic scope** | COM |
| **Publisher** | World Health Organization |
| **HDX last updated** | 2025-02-07 |

---

## Variables

**Geographic** — `gho_display` (Number of deaths, Distribution of causes of death among children aged < 5 years (%), Deaths per 1 000 live births), `year_display` (range 1961.0–2030.0), `startyear` (range 1961.0–2030.0), `endyear` (range 1961.0–2030.0), `region_code` (AFR, #region+code) and 4 others.

**Outcome / Measurement** — `value`.

**Identifier / Metadata** — `gho_code` (MORT_100, MORT_300, MORT_200), `dimension_code` (SEX_BTSX, SEX_FMLE, SEX_MLE), `dimension_name` (Both sexes, Female, Male), `esa_source`, `esa_processed`.

**Other** — `gho_url` (https://www.who.int/data/gho/data/indicators/indicator-details/GHO/gho-ghe-life-tables-by-who-region-global-health-estimates, https://www.who.int/data/gho/data/indicators/indicator-details/GHO/number-of-deaths, https://www.who.int/data/gho/data/indicators/indicator-details/GHO/deaths-per-1-000-live-births), `numeric` (range -0.0052–8700000.0), `low` (range -0.102–20121.293), `high` (range 0.0–27802.0684).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-disability-comoros")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `gho_code` | object | 0.0% | MORT_100, MORT_300, MORT_200 |
| `gho_display` | object | 0.0% | Number of deaths, Distribution of causes of death among children aged < 5 years (%), Deaths per 1 000 live births |
| `gho_url` | object | 0.0% | https://www.who.int/data/gho/data/indicators/indicator-details/GHO/gho-ghe-life-tables-by-who-region-global-health-estimates, https://www.who.int/data/gho/data/indicators/indicator-details/GHO/number-of-deaths, https://www.who.int/data/gho/data/indicators/indicator-details/GHO/deaths-per-1-000-live-births |
| `year_display` | float64 | 0.0% | 1961.0 – 2030.0 (mean 2008.0598) |
| `startyear` | float64 | 0.0% | 1961.0 – 2030.0 (mean 2008.0569) |
| `endyear` | float64 | 0.0% | 1961.0 – 2030.0 (mean 2008.0598) |
| `region_code` | object | 0.0% | AFR, #region+code |
| `region_display` | object | 0.0% | Africa, #region+name |
| `country_code` | object | 0.0% | COM, #country+code |
| `country_display` | object | 0.0% | Comoros, #country+name |
| `dimension_type` | object | 18.8% | SEX, RESIDENCEAREATYPE, AGEGROUP |
| `dimension_code` | object | 18.8% | SEX_BTSX, SEX_FMLE, SEX_MLE |
| `dimension_name` | object | 18.8% | Both sexes, Female, Male |
| `numeric` | float64 | 10.2% | -0.0052 – 8700000.0 (mean 68152.8489) |
| `value` | object | 0.3% | |
| `low` | float64 | 46.1% | -0.102 – 20121.293 (mean 74.2062) |
| `high` | float64 | 46.1% | 0.0 – 27802.0684 (mean 139.6561) |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year_display` | 1961.0 | 2030.0 | 2008.0598 | 2010.0 |
| `startyear` | 1961.0 | 2030.0 | 2008.0569 | 2010.0 |
| `endyear` | 1961.0 | 2030.0 | 2008.0598 | 2010.0 |
| `numeric` | -0.0052 | 8700000.0 | 68152.8489 | 8.8296 |
| `low` | -0.102 | 20121.293 | 74.2062 | 4.3438 |
| `high` | 0.0 | 27802.0684 | 139.6561 | 13.1968 |

---

## 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`. 322 exact duplicate rows were removed. 6 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 World Health Organization 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: `low`, `high`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/who-data-for-comoros) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_disability_comoros,
title = {Comoros - Health Indicators},
author = {World Health Organization},
year = {2025},
url = {https://data.humdata.org/dataset/who-data-for-comoros},
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:
- 现有公开资源获取
language:
- 英语
license:
- 其他
multilinguality:
- 单语言
size_categories:
- 1万至10万条数据
source_datasets:
- 原始数据集
task_categories:
- 表格分类
task_ids: []
tags:
- 非洲
- 人道主义
- HDX
- Electric Sheep Africa
- 残障
- 疾病
- 环境
- 健康
- HXL
- 指标
- 疟疾
- 孕产
- COM
pretty_name: "科摩罗——健康指标数据集"
dataset_info:
splits:
- name: 训练集
num_examples: 14107
- name: 测试集
num_examples: 3526
---

# 科摩罗——健康指标数据集

**发布方**：世界卫生组织（World Health Organization） · **来源**：[HDX](https://data.humdata.org/dataset/who-data-for-comoros) · **许可证**：`hdx-other` · **最后更新**：2025-02-07

---

## 摘要

本数据集收录源自世界卫生组织（WHO）[数据门户](https://www.who.int/gho/en/)的以下类别的数据：

空气污染、抗菌素耐药性（Antimicrobial resistance, AMR）、辅助技术、儿童死亡率、痴呆症的诊断、治疗与照护、痴呆症相关政策与法规、环境与健康、食源性疾病估算数据、全球痴呆观察站（Global Dementia Observatory, GDO）、全球健康估算：预期寿命及主要死亡与致残原因、全球酒精与健康信息系统、艾滋病病毒（HIV）、健康不平等监测、健康筹资、卫生系统、健康税、卫生人力、肝炎、免疫接种覆盖率与疫苗可预防疾病、《国际卫生条例（2005）》监测框架、疟疾、孕产与生殖健康、精神卫生、被忽视的热带病、非传染性疾病、营养、口腔健康、优先卫生技术、物质使用障碍相关资源、道路安全、可持续发展目标3.8 | 实现全民健康覆盖（Universal Health Coverage, UHC）、性传播感染、烟草控制、结核病、疫苗可预防传染病、针对妇女的暴力、暴力预防、水、环境卫生与个人卫生（Water, Sanitation and Hygiene, WASH）、妇女与健康、世界卫生统计。

如需获取各指标元数据的链接，请参阅资源说明。

本数据集的每一行均代表一级行政单元的观测数据。本数据集最后一次在HDX平台更新的时间为2025-02-07。地理覆盖范围：**COM（科摩罗）**。

*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。*

---

## 数据集特征

| | |
|---|---|
| **领域** | 粮食安全与营养 |
| **观测单元** | 一级行政单元观测数据 |
| **总数据行数** | 17,634 |
| **列数** | 19列（6列数值型、13列分类型、0列日期时间型） |
| **训练集划分** | 14,107行 |
| **测试集划分** | 3,526行 |
| **地理覆盖范围** | COM（科摩罗） |
| **发布方** | 世界卫生组织（World Health Organization） |
| **HDX平台最后更新时间** | 2025-02-07 |

---

## 变量说明

**地理类变量**：`gho_display`（死亡数、<5岁儿童死亡原因分布（%）、每1000活产儿死亡数）、`year_display`（取值范围1961.0–2030.0）、`startyear`（取值范围1961.0–2030.0）、`endyear`（取值范围1961.0–2030.0）、`region_code`（AFR、#region+code）以及另外4个变量。

**结果/测量变量**：`value`。

**标识符/元数据变量**：`gho_code`（MORT_100、MORT_300、MORT_200）、`dimension_code`（SEX_BTSX、SEX_FMLE、SEX_MLE）、`dimension_name`（两性、女性、男性）、`esa_source`、`esa_processed`。

**其他变量**：`gho_url`（示例链接：https://www.who.int/data/gho/data/indicators/indicator-details/GHO/gho-ghe-life-tables-by-who-region-global-health-estimates、https://www.who.int/data/gho/data/indicators/indicator-details/GHO/number-of-deaths、https://www.who.int/data/gho/data/indicators/indicator-details/GHO/deaths-per-1-000-live-births）、`numeric`（取值范围-0.0052–8700000.0）、`low`（取值范围-0.102–20121.293）、`high`（取值范围0.0–27802.0684）。

---

## 快速入门

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-disability-comoros")
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 |
|---|---|---|---|
| `gho_code` | 字符型 | 0.0% | MORT_100、MORT_300、MORT_200 |
| `gho_display` | 字符型 | 0.0% | 死亡数、<5岁儿童死亡原因分布（%）、每1000活产儿死亡数 |
| `gho_url` | 字符型 | 0.0% | 示例链接：https://www.who.int/data/gho/data/indicators/indicator-details/GHO/gho-ghe-life-tables-by-who-region-global-health-estimates、https://www.who.int/data/gho/data/indicators/indicator-details/GHO/number-of-deaths、https://www.who.int/data/gho/data/indicators/indicator-details/GHO/deaths-per-1-000-live-births |
| `year_display` | 浮点型 | 0.0% | 1961.0 – 2030.0（均值2008.0598） |
| `startyear` | 浮点型 | 0.0% | 1961.0 – 2030.0（均值2008.0569） |
| `endyear` | 浮点型 | 0.0% | 1961.0 – 2030.0（均值2008.0598） |
| `region_code` | 字符型 | 0.0% | AFR、#region+code |
| `region_display` | 字符型 | 0.0% | 非洲、#region+name |
| `country_code` | 字符型 | 0.0% | COM、#country+code |
| `country_display` | 字符型 | 0.0% | 科摩罗、#country+name |
| `dimension_type` | 字符型 | 18.8% | SEX、RESIDENCEAREATYPE、AGEGROUP |
| `dimension_code` | 字符型 | 18.8% | SEX_BTSX、SEX_FMLE、SEX_MLE |
| `dimension_name` | 字符型 | 18.8% | 两性、女性、男性 |
| `numeric` | 浮点型 | 10.2% | -0.0052 – 8700000.0（均值68152.8489） |
| `value` | 字符型 | 0.3% | 无 |
| `low` | 浮点型 | 46.1% | -0.102 – 20121.293（均值74.2062） |
| `high` | 浮点型 | 46.1% | 0.0 – 27802.0684（均值139.6561） |
| `esa_source` | 字符型 | 0.0% | 无 |
| `esa_processed` | 字符型 | 0.0% | 无 |

---

## 数值型变量统计摘要

| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year_display` | 1961.0 | 2030.0 | 2008.0598 | 2010.0 |
| `startyear` | 1961.0 | 2030.0 | 2008.0569 | 2010.0 |
| `endyear` | 1961.0 | 2030.0 | 2008.0598 | 2010.0 |
| `numeric` | -0.0052 | 8700000.0 | 68152.8489 | 8.8296 |
| `low` | -0.102 | 20121.293 | 74.2062 | 4.3438 |
| `high` | 0.0 | 27802.0684 | 139.6561 | 13.1968 |

---

## 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。所有列名均转换为小写并统一为蛇形命名法（snake_case）。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。共移除322条完全重复的行。基于解析成功率（阈值>85%），将6列从字符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80/20比例划分为训练集与测试集，并以Snappy压缩的Parquet格式存储。

---

## 数据集局限性

- 本数据集源自世界卫生组织（World Health Organization），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、定义不一致或抽样偏差问题。
- 以下列的缺失率超过20%，在建模时需谨慎使用：`low`、`high`。
- 如需了解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/who-data-for-comoros)。

---

## 引用格式

bibtex
@dataset{hdx_africa_disability_comoros,
title = {Comoros - Health Indicators},
author = {World Health Organization},
year = {2025},
url = {https://data.humdata.org/dataset/who-data-for-comoros},
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。*