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

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- health
- indicators
- zwe
pretty_name: "Zimbabwe - Health"
dataset_info:
splits:
- name: train
num_examples: 8330
- name: test
num_examples: 2082
---

# Zimbabwe - Health

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-health-indicators-for-zimbabwe) · **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-zimbabwe) 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: **ZWE**.

*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)** | 10,413 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 8,330 rows |
| **Test split** | 2,082 rows |
| **Geographic scope** | ZWE |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Zimbabwe), `country_iso3` (ZWE), `year` (range 1960.0–2025.0).

**Outcome / Measurement** — `value` (range -243947.0–16634373.0).

**Identifier / Metadata** — `indicator_name` (Net migration, Population ages 15-64, male (% of male population), Population ages 15-64 (% of total population)), `indicator_code` (SM.POP.NETM, SP.POP.1564.MA.ZS, SP.POP.1564.TO.ZS), `esa_source` (HDX), `esa_processed` (2026-04-10).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-health-indicators-for-zimbabwe")
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% | Zimbabwe |
| `country_iso3` | object | 0.0% | ZWE |
| `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 1999.4206) |
| `indicator_name` | object | 0.0% | Net migration, Population ages 15-64, male (% of male population), Population ages 15-64 (% of total population) |
| `indicator_code` | object | 0.0% | SM.POP.NETM, SP.POP.1564.MA.ZS, SP.POP.1564.TO.ZS |
| `value` | float64 | 0.0% | -243947.0 – 16634373.0 (mean 250810.1121) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-10 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 1999.4206 | 2004.0 |
| `value` | -243947.0 | 16634373.0 | 250810.1121 | 30.1 |

---

## 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-zimbabwe) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_health_indicators_for_zimbabwe,
title = {Zimbabwe - Health},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-health-indicators-for-zimbabwe},
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.*

---
注释创建者:
- 无注释
语言创建者:
- 现有资源采集
语言:
- 英语
许可证: 知识共享署名4.0许可（CC BY 4.0）
多语言属性:
- 单语言
数据规模分类:
- 10000 < 样本数 < 100000
源数据集:
- 原始数据集
任务类别:
- 表格分类
任务子项: []
标签:
- 非洲
- 人道主义
- HDX（人道主义数据交换平台）
- Electric Sheep Africa
- 卫生
- 指标
- ZWE（津巴布韦）
展示名称: "津巴布韦——卫生"
数据集信息:
划分:
- 名称: 训练集
样本数: 8330
- 名称: 测试集
样本数: 2082
---

# 津巴布韦——卫生

**发布方**：世界银行集团 · **来源**：[HDX（人道主义数据交换平台）](https://data.humdata.org/dataset/world-bank-health-indicators-for-zimbabwe) · **许可证**：`CC BY 4.0` · **更新时间**：2026-03-27

---

## 摘要

本数据集收录世界银行[数据门户](http://data.worldbank.org/)的公开数据。HDX平台上同时提供一份[津巴布韦综合国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-zimbabwe)。

提升健康水平是千年发展目标的核心内容，公共部门是发展中国家医疗服务的主要供给方。为缩小健康公平差距，多国均将初级卫生保健作为工作重点，涵盖免疫接种、环境卫生、安全饮用水获取以及孕产安全举措等领域。本数据集覆盖卫生系统、疾病预防、生殖健康、营养状况与人口动态等维度，数据来源包括联合国人口司、世界卫生组织、联合国儿童基金会、联合国艾滋病规划署及其他多个官方机构。

本数据集的每一行均代表国家级汇总统计数据。其在HDX平台的最后更新时间为2026-03-27，地理覆盖范围为**ZWE（津巴布韦）**。

*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 |
| **观测单元** | 国家级汇总统计数据 |
| **总数据行数** | 10413条 |
| **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** | 8330条数据 |
| **测试集划分** | 2082条数据 |
| **地理覆盖范围** | ZWE（津巴布韦） |
| **发布方** | 世界银行集团 |
| **HDX平台最后更新时间** | 2026-03-27 |

---

## 变量说明

**地理类变量**：`country_name`（国家名称：津巴布韦）、`country_iso3`（国家ISO3代码：ZWE）、`year`（年份：取值范围1960.0–2025.0）。
**结果/测量类变量**：`value`（指标数值：取值范围-243947.0–16634373.0）。
**标识符/元数据类变量**：`indicator_name`（指标名称：净移民、15-64岁男性人口占男性总人口比例、15-64岁人口占总人口比例）、`indicator_code`（指标代码：SM.POP.NETM、SP.POP.1564.MA.ZS、SP.POP.1564.TO.ZS）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-10）。

---

## 快速上手

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-health-indicators-for-zimbabwe")
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 | 空值占比 | 取值范围/示例值 |
|---|---|---|---|
| `country_name` | 字符型（object） | 0.0% | 津巴布韦 |
| `country_iso3` | 字符型（object） | 0.0% | ZWE |
| `year` | 64位整型（int64） | 0.0% | 1960.0 – 2025.0（均值1999.4206） |
| `indicator_name` | 字符型（object） | 0.0% | 净移民、15-64岁男性人口占男性总人口比例、15-64岁人口占总人口比例 |
| `indicator_code` | 字符型（object） | 0.0% | SM.POP.NETM、SP.POP.1564.MA.ZS、SP.POP.1564.TO.ZS |
| `value` | 64位浮点型（float64） | 0.0% | -243947.0 – 16634373.0（均值250810.1121） |
| `esa_source` | 字符型（object） | 0.0% | HDX |
| `esa_processed` | 字符型（object） | 0.0% | 2026-04-10 |

---

## 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 | 1999.4206 | 2004.0 |
| `value` | -243947.0 | 16634373.0 | 250810.1121 | 30.1 |

---

## 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。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。本数据集以固定随机种子（42）按照80/20的比例划分为训练集与测试集，并保存为Snappy压缩格式的Parquet文件。

---

## 数据集局限性

- 本数据集数据源自世界银行集团，未经过Electric Sheep Africa的独立验证。
- 自动化清洗流程无法修正原始数据收集阶段存在的错报值、定义不一致或抽样偏差问题。
- 如需了解发布方提供的方法学说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-health-indicators-for-zimbabwe)。

---

## 引用格式

bibtex
@dataset{hdx_africa_world_bank_health_indicators_for_zimbabwe,
title = {津巴布韦——卫生},
author = {世界银行集团},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-health-indicators-for-zimbabwe},
note = {由Electric Sheep Africa重新打包适配机器学习场景 (https://huggingface.co/electricsheepafrica)}
}

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — 非洲的机器学习数据集基础设施。尼日利亚拉各斯。*