electricsheepafrica/africa-world-bank-climate-change-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:
- tabular-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- climate-weather
- indicators
- cpv
pretty_name: "Cabo Verde - Climate Change"
dataset_info:
splits:
- name: train
num_examples: 1049
- name: test
num_examples: 262
---

# Cabo Verde - Climate Change

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-climate-change-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.

Climate change is expected to hit developing countries the hardest. Its effects—higher temperatures, changes in precipitation patterns, rising sea levels, and more frequent weather-related disasters—pose risks for agriculture, food, and water supplies. At stake are recent gains in the fight against poverty, hunger and disease, and the lives and livelihoods of billions of people in developing countries. Addressing climate change requires unprecedented global cooperation across borders. The World Bank Group is helping support developing countries and contributing to a global solution, while tailoring our approach to the differing needs of developing country partners. Data here cover climate systems, exposure to climate impacts, resilience, greenhouse gas emissions, and energy use. Other indicators relevant to climate change are found under other data pages, particularly Environment, Agriculture & Rural Development, Energy & Mining, Health, Infrastructure, Poverty, and Urban Development.

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** | Food security and nutrition |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 1,312 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 1,049 rows |
| **Test split** | 262 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 1960.0–2024.0).

**Outcome / Measurement** — `value` (range -0.0046–89350000.0).

**Identifier / Metadata** — `indicator_name` (Urban population (% of total population), Urban population, Population, total), `indicator_code` (SP.URB.TOTL.IN.ZS, SP.URB.TOTL, SP.POP.TOTL), `esa_source` (HDX), `esa_processed` (2026-04-16).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-climate-change-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 – 2024.0 (mean 1999.1928) |
| `indicator_name` | object | 0.0% | Urban population (% of total population), Urban population, Population, total |
| `indicator_code` | object | 0.0% | SP.URB.TOTL.IN.ZS, SP.URB.TOTL, SP.POP.TOTL |
| `value` | float64 | 0.0% | -0.0046 – 89350000.0 (mean 710417.997) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-16 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2024.0 | 1999.1928 | 2003.0 |
| `value` | -0.0046 | 89350000.0 | 710417.997 | 19.5737 |

---

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

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_climate_change_indicators_for_cabo_verde,
title = {Cabo Verde - Climate Change},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-climate-change-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:
- 采集自现有数据
language:
- 英语（en）
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（Humanitarian Data Exchange）
- electric-sheep-africa
- 气候与天气
- 指标
- CPV（佛得角ISO 3位国家代码）
pretty_name: "佛得角——气候变化"
dataset_info:
splits:
- name: 训练集
num_examples: 1049
- name: 测试集
num_examples: 262
---

# 佛得角——气候变化

**发布方**：世界银行集团 · **来源**：[HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-cabo-verde) · **许可协议**：`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平台上另有一份[整合后的佛得角国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-cabo-verde)可供获取。

气候变化预计将对发展中国家造成最为严重的冲击。其影响包括气温升高、降水模式改变、海平面上升以及愈发频发的气象灾害，这些都将对农业、粮食与水资源供应构成威胁。我们在对抗贫困、饥饿与疾病方面取得的近期成果，以及发展中国家数十亿民众的生命与生计，都面临着严峻风险。应对气候变化需要全球范围内前所未有的跨境合作。世界银行集团正助力支持发展中国家，并为全球气候解决方案贡献力量，同时针对不同发展中国家合作伙伴的差异化需求调整工作方式。本数据集涵盖气候系统、气候影响暴露度、恢复力、温室气体排放以及能源使用相关数据。其他与气候变化相关的指标可在其他数据页面查询，尤其是环境、农业与农村发展、能源与矿业、卫生、基础设施、贫困以及城市发展板块。

本数据集的每一行均代表国家层面的汇总数据。该数据集最后一次在HDX平台更新的时间为2026-03-27。地理覆盖范围：**CPV（佛得角ISO 3位国家代码）**。

*本数据集由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为适合机器学习的Parquet格式。*

---

## 数据集特征

| | |
|---|---|
| **领域** | 粮食安全与营养 |
| **观测单元** | 国家层面汇总数据 |
| **总行数** | 1312 |
| **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** | 1049条数据 |
| **测试集划分** | 262条数据 |
| **地理覆盖范围** | CPV |
| **发布方** | 世界银行集团 |
| **HDX平台最后更新时间** | 2026-03-27 |

---

## 变量

**地理类字段** — `country_name`（国家名称：佛得角）、`country_iso3`（国家ISO 3位代码：CPV）、`year`（年份范围：1960.0–2024.0）。
**结果/测量类字段** — `value`（数值范围：-0.0046–89350000.0）。
**标识符/元数据字段** — `indicator_name`（指标名称：城镇人口占总人口比例、城镇总人口、总人口）、`indicator_code`（指标代码：SP.URB.TOTL.IN.ZS、SP.URB.TOTL、SP.POP.TOTL）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-16）。

---

## 快速入门

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-climate-change-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（object） | 0.0% | CPV |
| `year` | 64位整型（int64） | 0.0% | 1960.0 – 2024.0（平均值：1999.1928） |
| `indicator_name` | 字符型（object） | 0.0% | 城镇人口占总人口比例、城镇总人口、总人口 |
| `indicator_code` | 字符型（object） | 0.0% | SP.URB.TOTL.IN.ZS、SP.URB.TOTL、SP.POP.TOTL |
| `value` | 64位浮点型（float64） | 0.0% | -0.0046 – 89350000.0（平均值：710417.997） |
| `esa_source` | 字符型（object） | 0.0% | HDX |
| `esa_processed` | 字符型（object） | 0.0% | 2026-04-16 |

---

## 数值型统计摘要

| 字段 | 最小值 | 最大值 | 平均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1960.0 | 2024.0 | 1999.1928 | 2003.0 |
| `value` | -0.0046 | 89350000.0 | 710417.997 | 19.5737 |

---

## 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采用蛇形命名法规范。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。本数据集采用固定随机种子（42）按照80/20的比例划分为训练集与测试集，并以Snappy压缩格式的Parquet文件保存。

---

## 局限性说明

- 本数据集源自世界银行集团，并未经过Electric Sheep Africa的独立验证。
- 自动化清洗无法修正原始数据收集过程中存在的错报值、定义不一致或抽样偏差问题。
- 如需查看发布方提供的官方方法说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-cabo-verde)。

---

## 引用格式

bibtex
@dataset{hdx_africa_world_bank_climate_change_indicators_for_cabo_verde,
title = {佛得角——气候变化},
author = {世界银行集团},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-cabo-verde},
note = {由Electric Sheep Africa（https://huggingface.co/electricsheepafrica）重新打包为机器学习可用格式}
}

---

*[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。*