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

---
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
- cpv
pretty_name: "Cabo Verde - Social Protection and Labor"
dataset_info:
splits:
- name: train
num_examples: 2556
- name: test
num_examples: 639
---

# Cabo Verde - Social Protection and Labor

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

*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)** | 3,195 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 2,556 rows |
| **Test split** | 639 rows |
| **Geographic scope** | CPV |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Cabo Verde), `country_iso3` (CPV), `year` (range 1960.0–2025.0).

**Outcome / Measurement** — `value` (range 0.0–262084.0).

**Identifier / Metadata** — `indicator_name` (Labor force participation rate, female (% of female population ages 15+) (modeled ILO estimate), Labor force participation rate, total (% of total population ages 15+) (modeled ILO estimate), Labor force, total), `indicator_code` (SL.TLF.CACT.FE.ZS, SL.TLF.CACT.ZS, SL.TLF.TOTL.IN), `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-cabo-verde")
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% | Cabo Verde |
| `country_iso3` | object | 0.0% | CPV |
| `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 2007.7693) |
| `indicator_name` | object | 0.0% | Labor force participation rate, female (% of female population ages 15+) (modeled ILO estimate), Labor force participation rate, total (% of total population ages 15+) (modeled ILO estimate), Labor force, total |
| `indicator_code` | object | 0.0% | SL.TLF.CACT.FE.ZS, SL.TLF.CACT.ZS, SL.TLF.TOTL.IN |
| `value` | float64 | 0.0% | 0.0 – 262084.0 (mean 4710.9232) |
| `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 | 2007.7693 | 2007.0 |
| `value` | 0.0 | 262084.0 | 4710.9232 | 26.1754 |

---

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

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_social_protection_and_labor_indicators_for_cabo_verde,
title = {Cabo Verde - Social Protection and Labor},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-cabo-verde},
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:
- 单语种
size_categories:
- 1K<n<10K
source_datasets:
- 原始数据集
task_categories:
- 其他
task_ids: []
tags:
- 非洲
- 人道主义
- HDX
- 非洲电羊（Electric Sheep Africa）
- 指标
- 社会经济
- CPV
pretty_name: "佛得角——社会保障与劳动"
dataset_info:
splits:
- name: train
num_examples: 2556
- name: test
num_examples: 639
---

# 佛得角——社会保障与劳动

**发布方**：世界银行集团（World Bank Group） · **来源**：[HDX](https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-cabo-verde) · **许可协议**：`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平台上另有一份[整合式国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-cabo-verde)。

经济体中的可用劳动力供给涵盖就业人员、失业且正在求职的人员，以及首次求职者。并非所有参与劳动的人员均被纳入统计：无报酬劳动者、家庭帮工及学生通常被排除在外，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）基于劳动力调查、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汇编而成。

本数据集的每一行均代表国家级汇总数据。其在HDX平台的最后更新时间为2026-03-27。地理覆盖范围：**CPV（佛得角国家代码）**。

*由[非洲电羊（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** | 国家级汇总数据 |
| **总行数** | 3,195 |
| **列数** | 8列（2列数值型、6列分类型、0列日期时间型） |
| **训练集划分** | 2556行 |
| **测试集划分** | 639行 |
| **地理覆盖范围** | CPV |
| **发布方** | 世界银行集团 |
| **HDX最后更新时间** | 2026-03-27 |

---

## 变量说明

**地理类变量**：`country_name`（国家名称：佛得角）、`country_iso3`（国家ISO3代码：CPV）、`year`（年份范围：1960.0–2025.0）。

**结果/测量类变量**：`value`（数值范围：0.0–262084.0）。

**标识符/元数据类变量**：`indicator_name`（指标名称：女性劳动力参与率（%，15岁及以上女性人口，ILO估算模型）、总劳动力参与率（%，15岁及以上总人口，ILO估算模型）、总劳动力）、`indicator_code`（指标代码：SL.TLF.CACT.FE.ZS、SL.TLF.CACT.ZS、SL.TLF.TOTL.IN）、`esa_source`（数据来源：HDX）、`esa_processed`（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-cabo-verde")
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 | 空值占比 | 取值范围/示例值 |
|---|---|---|---|
| `country_name` | 字符型 | 0.0% | 佛得角 |
| `country_iso3` | 字符型 | 0.0% | CPV |
| `year` | 64位整型 | 0.0% | 1960.0 – 2025.0（均值2007.7693） |
| `indicator_name` | 字符型 | 0.0% | 女性劳动力参与率（%，15岁及以上女性人口，ILO估算模型）、总劳动力参与率（%，15岁及以上总人口，ILO估算模型）、总劳动力 |
| `indicator_code` | 字符型 | 0.0% | SL.TLF.CACT.FE.ZS、SL.TLF.CACT.ZS、SL.TLF.TOTL.IN |
| `value` | 64位浮点型 | 0.0% | 0.0 – 262084.0（均值4710.9232） |
| `esa_source` | 字符型 | 0.0% | HDX |
| `esa_processed` | 字符型 | 0.0% | 2026-04-17 |

---

## 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 | 2007.7693 | 2007.0 |
| `value` | 0.0 | 262084.0 | 4710.9232 | 26.1754 |

---

## 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。列名全部转为小写，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`。本数据集使用固定随机种子（42）按照80/20的比例划分为训练集与测试集，并以Snappy压缩的Parquet格式存储。

---

## 数据集局限性

- 数据源自世界银行集团，并未经非洲电羊（ESA）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。
- 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-cabo-verde)获取发布方提供的方法说明与注意事项。

---

## 引用格式

bibtex
@dataset{hdx_africa_world_bank_social_protection_and_labor_indicators_for_cabo_verde,
title = {Cabo Verde - Social Protection and Labor},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-cabo-verde},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

*[非洲电羊（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。*