electricsheepafrica/africa-world-bank-poverty-indicators-for-south-africa

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- indicators
- poverty
- zaf
pretty_name: "South Africa - Poverty"
dataset_info:
splits:
- name: train
num_examples: 96
- name: test
num_examples: 24
---

# South Africa - Poverty

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-poverty-indicators-for-south-africa) · **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-south-africa) on HDX.

For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods. Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **ZAF**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Poverty and economic vulnerability |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 120 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 96 rows |
| **Test split** | 24 rows |
| **Geographic scope** | ZAF |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (South Africa), `country_iso3` (ZAF), `year` (range 1993.0–2022.0).

**Outcome / Measurement** — `value` (range -1.35–78.5).

**Identifier / Metadata** — `indicator_name` (Population living in slums (% of urban population), Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population), Poverty gap at $8.30 a day (2021 PPP) (%)), `indicator_code` (EN.POP.SLUM.UR.ZS, SI.POV.DDAY, SI.POV.UMIC.GP), `esa_source` (HDX), `esa_processed` (2026-04-10).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-poverty-indicators-for-south-africa")
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% | South Africa |
| `country_iso3` | object | 0.0% | ZAF |
| `year` | int64 | 0.0% | 1993.0 – 2022.0 (mean 2006.425) |
| `indicator_name` | object | 0.0% | Population living in slums (% of urban population), Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population), Poverty gap at $8.30 a day (2021 PPP) (%) |
| `indicator_code` | object | 0.0% | EN.POP.SLUM.UR.ZS, SI.POV.DDAY, SI.POV.UMIC.GP |
| `value` | float64 | 0.0% | -1.35 – 78.5 (mean 30.032) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-10 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1993.0 | 2022.0 | 2006.425 | 2008.0 |
| `value` | -1.35 | 78.5 | 30.032 | 25.4 |

---

## 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`. 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-poverty-indicators-for-south-africa) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_poverty_indicators_for_south_africa,
title = {South Africa - Poverty},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-poverty-indicators-for-south-africa},
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:
- 公开获取
language:
- 英语
license: CC BY 4.0
multilinguality:
- 单语言
size_categories:
- n<1K（样本量少于1000）
source_datasets:
- 原创数据集
task_categories:
- 表格回归
task_ids: []
tags:
- 非洲
- 人道主义
- HDX（Humanitarian Data Exchange）
- Electric Sheep Africa
- 指标
- 贫困
- ZAF
pretty_name: "南非——贫困状况"
dataset_info:
splits:
- name: train
num_examples: 96
- name: test
num_examples: 24

# 南非——贫困状况

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

---

## 摘要

本数据集包含来自世界银行[官方数据门户](http://data.worldbank.org/)的相关数据，HDX平台上另有一份[南非综合国家指标数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-south-africa)可供获取。

对于建立了成熟贫困监测机制的国家，世界银行会与本国相关机构、其他发展机构及民间社会组织合作，定期开展分析工作，以评估贫困与不平等问题的规模与成因，分析经济增长与公共政策的影响，并梳理家庭调查数据与测算方法。本数据集收录的贫困与不平等测算数据，来源于各类分析报告、国家贫困监测项目，以及世界银行发展研究局（Development Research Group）的相关成果——该局自1990年起便持续发布具备国际可比性的全球贫困测算结果与贫困线标准。

本数据集的每一条样本均代表国家层面的汇总统计数据。本数据集在HDX平台的最后更新时间为2026-03-27，地理覆盖范围：**ZAF（南非）**。

*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** | 贫困与经济脆弱性 |
| **观测单元** | 国家层面汇总数据 |
| **总样本量** | 120 |
| **字段数** | 8个（2个数值型、6个分类型、0个日期时间型） |
| **训练集划分** | 96条样本 |
| **测试集划分** | 24条样本 |
| **地理覆盖范围** | ZAF（南非） |
| **发布方** | 世界银行集团 |
| **HDX平台最后更新时间** | 2026-03-27 |

---

## 字段说明

**地理类字段**：`country_name`（国家名称：南非）、`country_iso3`（国家ISO3代码：ZAF）、`year`（年份范围：1993.0至2022.0）。

**结果/测算类字段**：`value`（测算值范围：-1.35至78.5）。

**标识/元数据类字段**：`indicator_name`（指标名称：城市贫民窟人口占比、每日3美元（2021年购买力平价）贫困线以下人口占比、每日8.30美元（2021年购买力平价）贫困缺口率）、`indicator_code`（指标代码：EN.POP.SLUM.UR.ZS、SI.POV.DDAY、SI.POV.UMIC.GP）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-10）。

---

## 快速上手

以下为快速使用示例代码：
python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-poverty-indicators-for-south-africa")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()

---

## 数据结构

| 字段名 | 数据类型 | 空值占比 | 取值范围/示例值 |
|---|---|---|---|
| `country_name` | 字符串型 | 0.0% | 南非 |
| `country_iso3` | 字符串型 | 0.0% | ZAF |
| `year` | 整型 | 0.0% | 1993.0 – 2022.0（均值：2006.425） |
| `indicator_name` | 字符串型 | 0.0% | 城市贫民窟人口占比、每日3美元（2021年购买力平价）贫困线以下人口占比、每日8.30美元（2021年购买力平价）贫困缺口率 |
| `indicator_code` | 字符串型 | 0.0% | EN.POP.SLUM.UR.ZS、SI.POV.DDAY、SI.POV.UMIC.GP |
| `value` | 浮点型 | 0.0% | -1.35 – 78.5（均值：30.032） |
| `esa_source` | 字符串型 | 0.0% | HDX |
| `esa_processed` | 字符串型 | 0.0% | 2026-04-10 |

---

## 数值型字段统计摘要

| 字段名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1993.0 | 2022.0 | 2006.425 | 2008.0 |
| `value` | -1.35 | 78.5 | 30.032 | 25.4 |

---

## 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。字段名称统一转为小写并采用蛇形命名法（snake_case）进行标准化。常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。本数据集以固定随机种子（42）按80/20的比例划分为训练集与测试集，并以Snappy压缩格式的Parquet文件存储。

---

## 数据集局限性

1. 本数据集数据来源于世界银行集团，Electric Sheep Africa未对其进行独立验证。
2. 自动化清洗流程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。
3. 如需了解发布方提供的方法论说明与相关注意事项，请参阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/world-bank-poverty-indicators-for-south-africa)。

---

## 引用格式

bibtex
@dataset{hdx_africa_world_bank_poverty_indicators_for_south_africa,
title = {South Africa - Poverty},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-poverty-indicators-for-south-africa},
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运营商，尼日利亚拉各斯。*