electricsheepafrica/africa-world-bank-gender-indicators-for-cabo-verde
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---
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:
- tabular-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- gender
- indicators
- cpv
pretty_name: "Cabo Verde - Gender"
dataset_info:
splits:
- name: train
num_examples: 3530
- name: test
num_examples: 882
---
# Cabo Verde - Gender
**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-gender-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.
Gender equality is a core development objective in its own right. It is also smart development policy and sound business practice. It is integral to economic growth, business growth and good development outcomes. Gender equality can boost productivity, enhance prospects for the next generation, build resilience, and make institutions more representative and effective. In December 2015, the World Bank Group Board discussed our new Gender Equality Strategy 2016-2023, which aims to address persistent gaps and proposed a sharpened focus on more and better gender data. The Bank Group is continually scaling up commitments and expanding partnerships to fill significant gaps in gender data. The database hosts the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.
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** | Public health |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 4,413 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 3,530 rows |
| **Test split** | 882 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 0.0–98789.0).
**Identifier / Metadata** — `indicator_name` (Age population, age 02, female, Age population, age 03, male, Age population, age 01, female), `indicator_code` (SP.POP.AG02.FE.IN, SP.POP.AG03.MA.IN, SP.POP.AG01.FE.IN), `esa_source` (HDX), `esa_processed` (2026-04-16).
---
## Quick Start
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-world-bank-gender-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 2000.8516) |
| `indicator_name` | object | 0.0% | Age population, age 02, female, Age population, age 03, male, Age population, age 01, female |
| `indicator_code` | object | 0.0% | SP.POP.AG02.FE.IN, SP.POP.AG03.MA.IN, SP.POP.AG01.FE.IN |
| `value` | float64 | 0.0% | 0.0 – 98789.0 (mean 1664.8463) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-16 |
---
## Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 2000.8516 | 2004.0 |
| `value` | 0.0 | 98789.0 | 1664.8463 | 56.1503 |
---
## 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-gender-indicators-for-cabo-verde) for the publisher's own methodology notes and caveats.
---
## Citation
```bibtex
@dataset{hdx_africa_world_bank_gender_indicators_for_cabo_verde,
title = {Cabo Verde - Gender},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-gender-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:
- 现有数据源获取
language:
- 英语
license: CC-BY-4.0
multilinguality:
- 单语言
size_categories:
- 1000 < 样本数 < 10000
source_datasets:
- 原创数据集
task_categories:
- 表格分类
- 表格回归
task_ids: []
tags:
- 非洲
- 人道主义
- HDX（人道主义数据交换平台，Humanitarian Data Exchange）
- Electric Sheep Africa（非洲电力羊团队）
- 性别议题
- 统计指标
- CPV（佛得角ISO 3166-1阿尔法3代码）
pretty_name: "佛得角——性别议题"
dataset_info:
splits:
- name: train
num_examples: 3530
- name: test
num_examples: 882
# 佛得角——性别议题
**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-gender-indicators-for-cabo-verde) · **许可证**：`CC-BY` · **最后更新时间**：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[佛得角综合国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-cabo-verde)。
性别平等本身就是核心发展目标，同时也是明智的发展政策与稳健的商业实践。它与经济增长、企业发展及优质发展成果密不可分。性别平等能够提升生产力、改善下一代的发展前景、增强韧性，并让各类机构更具代表性与实效性。2015年12月，世界银行集团董事会审议通过了《2016-2023年性别平等战略》，该战略旨在解决长期存在的性别数据缺口，并提出进一步聚焦于获取更多、更优质的性别数据。世行集团正持续加大投入、拓展合作，以填补性别数据领域的重大缺口。本数据库收录了最新的分性别统计数据与性别相关统计指标，覆盖人口统计、教育、健康、经济机会获取、公共生活与决策参与以及个人自主权等领域。
本数据集的每一行均代表国家层面的汇总数据。数据在HDX平台的最后更新时间为2026年3月27日。地理覆盖范围：**CPV（佛得角）**。
*本数据集已由[Electric Sheep Africa（非洲电力羊机器学习团队）](https://huggingface.co/electricsheepafrica)整理为适配机器学习的Parquet格式。*
---
## 数据集特征
| 项 | 详情 |
|---|---|
| **领域** | 公共卫生 |
| **观测单元** | 国家层面汇总数据 |
| **总样本行数** | 4413 |
| **列数** | 8列（2个数值型、6个分类型、0个日期时间型） |
| **训练集样本数** | 3530行 |
| **测试集样本数** | 882行 |
| **地理覆盖范围** | CPV（佛得角） |
| **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：佛得角）、`country_iso3`（国家ISO3代码：CPV）、`year`（年份范围：1960.0至2025.0）。
### 结果/测量类变量
`value`（指标数值，取值范围：0.0至98789.0）。
### 标识/元数据类变量
`indicator_name`（指标名称：0-2岁女性人口、0-3岁男性人口、0-1岁女性人口）、`indicator_code`（指标代码：SP.POP.AG02.FE.IN、SP.POP.AG03.MA.IN、SP.POP.AG01.FE.IN）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-16）。
---
## 快速上手
python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-world-bank-gender-indicators-for-cabo-verde")
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% | 佛得角 |
| `country_iso3` | 字符型 | 0.0% | CPV |
| `year` | 64位整数型 | 0.0% | 1960.0–2025.0（均值：2000.8516） |
| `indicator_name` | 字符型 | 0.0% | 0-2岁女性人口、0-3岁男性人口、0-1岁女性人口 |
| `indicator_code` | 字符型 | 0.0% | SP.POP.AG02.FE.IN、SP.POP.AG03.MA.IN、SP.POP.AG01.FE.IN |
| `value` | 64位浮点型 | 0.0% | 0.0–98789.0（均值：1664.8463） |
| `esa_source` | 字符型 | 0.0% | HDX |
| `esa_processed` | 字符型 | 0.0% | 2026-04-16 |
---
## 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 | 2000.8516 | 2004.0 |
| `value` | 0.0 | 98789.0 | 1664.8463 | 56.1503 |
---
## 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（snake_case）。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。本数据集采用固定随机种子（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
- 本数据集数据源自世界银行集团，未由Electric Sheep Africa进行独立验证。
- 自动化清洗流程无法修正原始数据采集阶段的错报值、定义不一致或抽样偏差问题。
- 如需了解发布方的方法论说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-gender-indicators-for-cabo-verde)。
---
## 引用格式
bibtex
@dataset{hdx_africa_world_bank_gender_indicators_for_cabo_verde,
title = {Cabo Verde - Gender},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-gender-indicators-for-cabo-verde},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
*注：本数据集由Electric Sheep Africa重新打包，适配机器学习场景（https://huggingface.co/electricsheepafrica）*
---
*[Electric Sheep Africa（非洲机器学习数据集基础设施提供商）](https://huggingface.co/electricsheepafrica) — 尼日利亚拉各斯。*
提供机构：
electricsheepafrica
