electricsheepafrica/africa-disability-cote-divoire

---
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
- civ
pretty_name: "Côte d'Ivoire - Health Indicators"
dataset_info:
splits:
- name: train
num_examples: 15609
- name: test
num_examples: 3902
---

# Côte d'Ivoire - Health Indicators

**Publisher:** World Health Organization · **Source:** [HDX](https://data.humdata.org/dataset/who-data-for-cote-d-ivoire) · **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: **CIV**.

*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)** | 19,512 |
| **Columns** | 19 (6 numeric, 13 categorical, 0 datetime) |
| **Train split** | 15,609 rows |
| **Test split** | 3,902 rows |
| **Geographic scope** | CIV |
| **Publisher** | World Health Organization |
| **HDX last updated** | 2025-02-07 |

---

## Variables

**Geographic** — `gho_display` (Number of deaths, Deaths per 1 000 live births, Distribution of causes of death among children aged < 5 years (%)), `year_display` (range 1955.0–2030.0), `startyear` (range 1955.0–2030.0), `endyear` (range 1955.0–2030.0), `region_code` (AFR, #region+code) and 4 others.

**Outcome / Measurement** — `value`.

**Identifier / Metadata** — `gho_code` (MORT_100, MORT_200, MORT_300), `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/number-of-deaths, 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/deaths-per-1-000-live-births), `numeric` (range -0.0007–148000000.0), `low` (range -0.0374–640000.0), `high` (range 0.0–893763.3125).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-disability-cote-divoire")
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_200, MORT_300 |
| `gho_display` | object | 0.0% | Number of deaths, Deaths per 1 000 live births, Distribution of causes of death among children aged < 5 years (%) |
| `gho_url` | object | 0.0% | 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/gho-ghe-life-tables-by-who-region-global-health-estimates, https://www.who.int/data/gho/data/indicators/indicator-details/GHO/deaths-per-1-000-live-births |
| `year_display` | float64 | 0.0% | 1955.0 – 2030.0 (mean 2007.7497) |
| `startyear` | float64 | 0.0% | 1955.0 – 2030.0 (mean 2007.7456) |
| `endyear` | float64 | 0.0% | 1955.0 – 2030.0 (mean 2007.7497) |
| `region_code` | object | 0.0% | AFR, #region+code |
| `region_display` | object | 0.0% | Africa, #region+name |
| `country_code` | object | 0.0% | CIV, #country+code |
| `country_display` | object | 0.0% | Côte d'Ivoire, #country+name |
| `dimension_type` | object | 18.4% | SEX, RESIDENCEAREATYPE, AGEGROUP |
| `dimension_code` | object | 18.4% | SEX_BTSX, SEX_FMLE, SEX_MLE |
| `dimension_name` | object | 18.5% | Both sexes, Female, Male |
| `numeric` | float64 | 8.8% | -0.0007 – 148000000.0 (mean 134214.1294) |
| `value` | object | 0.1% | |
| `low` | float64 | 45.7% | -0.0374 – 640000.0 (mean 4187.1969) |
| `high` | float64 | 45.7% | 0.0 – 893763.3125 (mean 6563.9068) |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year_display` | 1955.0 | 2030.0 | 2007.7497 | 2010.0 |
| `startyear` | 1955.0 | 2030.0 | 2007.7456 | 2010.0 |
| `endyear` | 1955.0 | 2030.0 | 2007.7497 | 2010.0 |
| `numeric` | -0.0007 | 148000000.0 | 134214.1294 | 14.5041 |
| `low` | -0.0374 | 640000.0 | 4187.1969 | 8.2 |
| `high` | 0.0 | 893763.3125 | 6563.9068 | 17.4 |

---

## 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`. 193 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-cote-d-ivoire) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_disability_cote_divoire,
title = {Côte d'Ivoire - Health Indicators},
author = {World Health Organization},
year = {2025},
url = {https://data.humdata.org/dataset/who-data-for-cote-d-ivoire},
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:
- 已获取
language:
- 英语
license:
- 其他
multilinguality:
- 单语言
size_categories:
- 10K<n<100K
source_datasets:
- 原创
task_categories:
- 表格分类
task_ids: []
tags:
- 非洲
- 人道主义
- HDX(HDX)
- electric-sheep-africa
- 残疾
- 疾病
- 环境
- 健康
- HXL(HXL)
- 指标
- 疟疾
- 孕产
- CIV
pretty_name: "科特迪瓦——健康指标"
dataset_info:
splits:
- name: train
num_examples: 15609
- name: test
num_examples: 3902

---

# 科特迪瓦——健康指标

**发布方：** 世界卫生组织 · **数据源：** [HDX(HDX)](https://data.humdata.org/dataset/who-data-for-cote-d-ivoire) · **许可证：** `hdx-other` · **更新时间：** 2025-02-07

---

## 摘要

本数据集包含来自世界卫生组织[数据门户](https://www.who.int/gho/en/)的数据，涵盖以下类别：

空气污染、抗菌药物耐药性（Antimicrobial resistance, AMR）、辅助技术、儿童死亡率、痴呆诊断、治疗与照护、痴呆政策与立法、环境与健康、食源性疾病估算、全球痴呆观察站（Global Dementia Observatory, GDO）、全球健康估算：预期寿命与主要死亡及残疾原因、全球酒精与健康信息系统、艾滋病（HIV）、健康不平等监测、卫生筹资、卫生系统、健康税、卫生人力、肝炎、免疫接种覆盖与疫苗可预防疾病、《国际卫生条例（2005）》监测框架、疟疾、孕产妇与生殖健康、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、物质使用障碍资源、道路安全、可持续发展目标3.8|实现全民健康覆盖（UHC）、性传播感染、烟草控制、结核病、疫苗可预防传染病、针对女性的暴力行为、暴力预防、水、环境卫生与个人卫生（WASH）、女性与健康、世界卫生统计。

如需获取各指标元数据的链接，请参阅资源描述。

本数据集的每一行代表一级行政单元的观测数据。数据最后一次在HDX更新的时间为2025-02-07。地理覆盖范围：**CIV（科特迪瓦国家代码）**。

*本数据集已由[Electric Sheep Africa(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** | 粮食安全与营养 |
| **观测单元** | 一级行政单元观测数据 |
| **总行数** | 19512 |
| **列数** | 19列（6列数值型，13列分类型，0列日期型） |
| **训练集划分** | 15609行 |
| **测试集划分** | 3902行 |
| **地理覆盖范围** | CIV |
| **发布方** | 世界卫生组织 |
| **HDX最后更新时间** | 2025-02-07 |

---

## 变量说明

**地理类变量** —— `gho_display`（死亡数、每1000活产儿死亡数、<5岁儿童死亡原因分布（%））、`year_display`（取值范围1955.0–2030.0）、`startyear`（取值范围1955.0–2030.0）、`endyear`（取值范围1955.0–2030.0）、`region_code`（AFR，#region+code）及另外4个变量。
**结局/测量类变量** —— `value`。
**标识符/元数据类变量** —— `gho_code`（MORT_100、MORT_200、MORT_300）、`dimension_code`（SEX_BTSX、SEX_FMLE、SEX_MLE）、`dimension_name`（男女合计、女性、男性）、`esa_source`、`esa_processed`。
**其他变量** —— `gho_url`（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/gho-ghe-life-tables-by-who-region-global-health-estimates、https://www.who.int/data/gho/data/indicators/indicator-details/GHO/deaths-per-1-000-live-births）、`numeric`（取值范围-0.0007–148000000.0）、`low`（取值范围-0.0374–640000.0）、`high`（取值范围0.0–893763.3125）。

---

## 快速入门

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-disability-cote-divoire")
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 | 缺失率 | 取值范围/示例值 |
|---|---|---|---|
| `gho_code` | `object` | 0.0% | MORT_100、MORT_200、MORT_300 |
| `gho_display` | `object` | 0.0% | 死亡数、每1000活产儿死亡数、<5岁儿童死亡原因分布（%） |
| `gho_url` | `object` | 0.0% | 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/gho-ghe-life-tables-by-who-region-global-health-estimates、https://www.who.int/data/gho/data/indicators/indicator-details/GHO/deaths-per-1-000-live-births |
| `year_display` | `float64` | 0.0% | 1955.0 – 2030.0（均值2007.7497） |
| `startyear` | `float64` | 0.0% | 1955.0 – 2030.0（均值2007.7456） |
| `endyear` | `float64` | 0.0% | 1955.0 – 2030.0（均值2007.7497） |
| `region_code` | `object` | 0.0% | AFR、#region+code |
| `region_display` | `object` | 0.0% | 非洲、#region+name |
| `country_code` | `object` | 0.0% | CIV、#country+code |
| `country_display` | `object` | 0.0% | 科特迪瓦、#country+name |
| `dimension_type` | `object` | 18.4% | SEX、RESIDENCEAREATYPE、AGEGROUP |
| `dimension_code` | `object` | 18.4% | SEX_BTSX、SEX_FMLE、SEX_MLE |
| `dimension_name` | `object` | 18.5% | 男女合计、女性、男性 |
| `numeric` | `float64` | 8.8% | -0.0007 – 148000000.0（均值134214.1294） |
| `value` | `object` | 0.1% | 无 |
| `low` | `float64` | 45.7% | -0.0374 – 640000.0（均值4187.1969） |
| `high` | `float64` | 45.7% | 0.0 – 893763.3125（均值6563.9068） |
| `esa_source` | `object` | 0.0% | 无 |
| `esa_processed` | `object` | 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` | 1955.0 | 2030.0 | 2007.7497 | 2010.0 |
| `startyear` | 1955.0 | 2030.0 | 2007.7456 | 2010.0 |
| `endyear` | 1955.0 | 2030.0 | 2007.7497 | 2010.0 |
| `numeric` | -0.0007 | 148000000.0 | 134214.1294 | 14.5041 |
| `low` | -0.0374 | 640000.0 | 4187.1969 | 8.2 |
| `high` | 0.0 | 893763.3125 | 6563.9068 | 17.4 |

---

## 数据整理流程

原始数据通过CKAN API从HDX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。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193条完全重复的行。基于解析成功率（阈值>85%），将6列从字符串类型转换为数值型或日期型。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，并保存为Snappy压缩的Parquet格式。

---

## 局限性说明

- 数据源自世界卫生组织，未经过Electric Sheep Africa的独立验证。
- 自动化清洗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。
- 以下列的缺失率超过20%，在建模时需谨慎使用：`low`、`high`。
- 请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/who-data-for-cote-d-ivoire)获取发布方提供的方法学说明与免责条款。

---

## 引用格式

bibtex
@dataset{hdx_africa_disability_cote_divoire,
title = {Côte d'Ivoire - Health Indicators},
author = {World Health Organization},
year = {2025},
url = {https://data.humdata.org/dataset/who-data-for-cote-d-ivoire},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

*[Electric Sheep Africa(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。*