electricsheepafrica/africa-world-bank-social-protection-and-labor-indicators-for-angola

---
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:
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- indicators
- socioeconomics
- ago
pretty_name: "Angola - Social Protection and Labor"
dataset_info:
splits:
- name: train
num_examples: 2364
- name: test
num_examples: 591
---

# Angola - Social Protection and Labor

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-angola) · **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-angola) on HDX.

The supply of labor available in an economy includes people who are employed, those who are unemployed but seeking work, and first-time job-seekers. Not everyone who works is included: unpaid workers, family workers, and students are often omitted, while some countries do not count members of the armed forces. Data on labor and employment are compiled by the International Labour Organization (ILO) from labor force surveys, censuses, establishment censuses and surveys, and administrative records such as employment exchange registers and unemployment insurance schemes.

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

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Humanitarian and development data |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 2,956 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 2,364 rows |
| **Test split** | 591 rows |
| **Geographic scope** | AGO |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Angola), `country_iso3` (AGO), `year` (range 1960.0–2025.0).

**Outcome / Measurement** — `value` (range -0.1075–16321277.0).

**Identifier / Metadata** — `indicator_name` (Labor force participation rate, female (% of female population ages 15+) (modeled ILO estimate), Labor force participation rate for ages 15-24, total (%) (modeled ILO estimate), Ratio of female to male labor force participation rate (%) (modeled ILO estimate)), `indicator_code` (SL.TLF.CACT.FE.ZS, SL.TLF.ACTI.1524.ZS, SL.TLF.CACT.FM.ZS), `esa_source` (HDX), `esa_processed` (2026-04-17).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-social-protection-and-labor-indicators-for-angola")
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% | Angola |
| `country_iso3` | object | 0.0% | AGO |
| `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 2010.5873) |
| `indicator_name` | object | 0.0% | Labor force participation rate, female (% of female population ages 15+) (modeled ILO estimate), Labor force participation rate for ages 15-24, total (%) (modeled ILO estimate), Ratio of female to male labor force participation rate (%) (modeled ILO estimate) |
| `indicator_code` | object | 0.0% | SL.TLF.CACT.FE.ZS, SL.TLF.ACTI.1524.ZS, SL.TLF.CACT.FM.ZS |
| `value` | float64 | 0.0% | -0.1075 – 16321277.0 (mean 202374.3354) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-17 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 2010.5873 | 2014.0 |
| `value` | -0.1075 | 16321277.0 | 202374.3354 | 33.6355 |

---

## 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-social-protection-and-labor-indicators-for-angola) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_social_protection_and_labor_indicators_for_angola,
title = {Angola - Social Protection and Labor},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-angola},
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.*

注释生成方式:
- 无注释
语言数据来源:
- 公开数据源
语言:
- 英语
许可证:
- cc-by-4.0
多语言属性:
- 单语言
数据规模类别:
- 1000 < 样本数 < 10000
源数据集:
- 原始数据集
任务类别:
- 其他
任务子项:
- 无
标签:
- 非洲
- 人道主义
- HDX
- Electric Sheep Africa
- 指标
- 社会经济学
- AGO
友好名称: "安哥拉——社会保护与劳动力"
数据集信息:
划分:
- 名称: 训练集
样本数量: 2364
- 名称: 测试集
样本数量: 591

# 安哥拉——社会保护与劳动力

**发布方**: 世界银行集团 · **数据源**: [人道主义数据交换平台（Humanitarian Data Exchange，HDX）](https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-angola) · **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[数据门户（http://data.worldbank.org/）]的相关数据。HDX平台上还提供了一份[安哥拉整合国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-angola)。

经济体中的可用劳动力供给包括就业人员、正在求职的失业人员以及首次求职者。并非所有劳动者都会被纳入统计：无薪劳动者、家庭帮工与学生常被排除在外，部分国家还未将军人纳入统计范围。劳动力与就业数据由国际劳工组织（International Labour Organization，ILO）通过劳动力调查、人口普查、企业普查与调查，以及就业登记册、失业保险计划等行政记录整理汇编而成。

本数据集的每一行均代表国家级聚合数据。数据最后在HDX平台的更新时间为2026-03-27。地理覆盖范围：**AGO**。

*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** | 人道主义与发展数据 |
| **观测单元** | 国家级聚合数据 |
| **总数据行数** | 2956 |
| **列数** | 8（2个数值型，6个分类型，0个日期时间型） |
| **训练集划分** | 2364行 |
| **测试集划分** | 591行 |
| **地理覆盖范围** | AGO |
| **发布方** | 世界银行集团 |
| **HDX最后更新时间** | 2026-03-27 |

---

## 变量说明

### 变量分类
1. **地理类变量**: `country_name`（国家名称：安哥拉）、`country_iso3`（ISO 3166-1 alpha-3代码：AGO）、`year`（年份范围：1960.0–2025.0）。
2. **结果/测量类变量**: `value`（指标数值，范围：-0.1075–16321277.0）。
3. **标识符/元数据变量**: `indicator_name`（指标名称，包含：女性劳动力参与率（%，15岁及以上女性人口，国际劳工组织估算模型）、15-24岁总劳动力参与率（%，国际劳工组织估算模型）、女性与男性劳动力参与率之比（%，国际劳工组织估算模型）），`indicator_code`（指标代码：SL.TLF.CACT.FE.ZS、SL.TLF.ACTI.1524.ZS、SL.TLF.CACT.FM.ZS），`esa_source`（数据来源：HDX），`esa_processed`（数据处理时间：2026-04-17）。

---

## 快速上手
python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-social-protection-and-labor-indicators-for-angola")
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% | 安哥拉 |
| `country_iso3` | 字符型（object） | 0.0% | AGO |
| `year` | 64位整型（int64） | 0.0% | 1960.0 – 2025.0（均值：2010.5873） |
| `indicator_name` | 字符型（object） | 0.0% | 女性劳动力参与率（%，15岁及以上女性人口，国际劳工组织估算模型）、15-24岁总劳动力参与率（%，国际劳工组织估算模型）、女性与男性劳动力参与率之比（%，国际劳工组织估算模型） |
| `indicator_code` | 字符型（object） | 0.0% | SL.TLF.CACT.FE.ZS、SL.TLF.ACTI.1524.ZS、SL.TLF.CACT.FM.ZS |
| `value` | 64位浮点型（float64） | 0.0% | -0.1075 – 16321277.0（均值：202374.3354） |
| `esa_source` | 字符型（object） | 0.0% | HDX |
| `esa_processed` | 字符型（object） | 0.0% | 2026-04-17 |

---

## 数值型变量统计摘要
| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 2010.5873 | 2014.0 |
| `value` | -0.1075 | 16321277.0 | 202374.3354 | 33.6355 |

---

## 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。列名均转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`）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，并保存为Snappy压缩格式的Parquet文件。

---

## 数据局限性
- 本数据集源自世界银行集团，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收集中的错报值、定义不一致或抽样偏差问题。
- 请参阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-angola)获取发布方提供的方法说明与免责声明。

---

## 引用格式
bibtex
@dataset{hdx_africa_world_bank_social_protection_and_labor_indicators_for_angola,
title = {Angola - Social Protection and Labor},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-angola},
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。*