electricsheepafrica/africa-world-bank-climate-change-indicators-for-ethiopia

---
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
- eth
pretty_name: "Ethiopia - Climate Change"
dataset_info:
splits:
- name: train
num_examples: 1124
- name: test
num_examples: 281
---

# Ethiopia - Climate Change

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

*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)** | 1,406 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 1,124 rows |
| **Test split** | 281 rows |
| **Geographic scope** | ETH |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Ethiopia), `country_iso3` (ETH), `year` (range 1960.0–2025.0).

**Outcome / Measurement** — `value` (range -1617210000.0–935320000.0).

**Identifier / Metadata** — `indicator_name` (Population in urban agglomerations of more than 1 million (% of total population), Urban population (% of total population), Urban population), `indicator_code` (EN.URB.MCTY.TL.ZS, SP.URB.TOTL.IN.ZS, SP.URB.TOTL), `esa_source` (HDX), `esa_processed` (2026-04-10).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-climate-change-indicators-for-ethiopia")
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% | Ethiopia |
| `country_iso3` | object | 0.0% | ETH |
| `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 2001.2873) |
| `indicator_name` | object | 0.0% | Population in urban agglomerations of more than 1 million (% of total population), Urban population (% of total population), Urban population |
| `indicator_code` | object | 0.0% | EN.URB.MCTY.TL.ZS, SP.URB.TOTL.IN.ZS, SP.URB.TOTL |
| `value` | float64 | 0.0% | -1617210000.0 – 935320000.0 (mean 2556191.6673) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-10 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 2001.2873 | 2004.0 |
| `value` | -1617210000.0 | 935320000.0 | 2556191.6673 | 18.5 |

---

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

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_climate_change_indicators_for_ethiopia,
title = {Ethiopia - Climate Change},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-ethiopia},
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:
- 无人工注释
language_creators:
- 公开采集
language:
- 英语
license: CC BY 4.0
multilinguality:
- 单语言
size_categories:
- 1000 < 样本数 < 10000
source_datasets:
- 原始数据集
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
- ETH
pretty_name: "埃塞俄比亚——气候变化"
dataset_info:
splits:
- 名称：训练集
样本数：1124
- 名称：测试集
样本数：281

# 埃塞俄比亚——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-ethiopia) · **许可协议**：`cc-by` · **最后更新**：2026-03-27

---

## 摘要

本数据集包含源自世界银行[数据门户](http://data.worldbank.org/)的相关数据。HDX平台上另有一份[整合后的国家级数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-ethiopia)可供使用。

气候变化对发展中国家的冲击预计将最为严峻。其影响包括气温升高、降水格局改变、海平面上升以及愈发频发的气象灾害，这些都对农业、粮食与水资源供应构成威胁。发展中国家在减贫、抗饥与防病领域近年取得的成果，以及数十亿民众的生计与生活，均面临严峻风险。应对气候变化需要全球各国开展前所未有的跨境合作。世界银行集团正助力发展中国家，并为全球气候治理贡献力量，同时针对不同发展中国家伙伴的差异化需求定制解决方案。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等相关数据。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、能源与采矿、卫生、基础设施、减贫以及城市发展等板块。

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：**ETH（埃塞俄比亚）**。

*本数据集由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为适合机器学习使用的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** | 1406 |
| **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** | 1124条数据 |
| **测试集划分** | 281条数据 |
| **地理覆盖范围** | ETH |
| **发布方** | 世界银行集团 |
| **HDX最后更新时间** | 2026-03-27 |

---

## 变量

**地理类变量** — `country_name`（国家名称：埃塞俄比亚）、`country_iso3`（国家ISO3代码：ETH）、`year`（年份：取值范围1960.0–2025.0）。
**结果/测量变量** — `value`（指标数值：取值范围-1617210000.0–935320000.0）。
**标识符/元数据变量** — `indicator_name`（指标名称：人口超过100万的城市集聚区人口占总人口比例、城镇人口占总人口比例、城镇人口总量）、`indicator_code`（指标代码：EN.URB.MCTY.TL.ZS、SP.URB.TOTL.IN.ZS、SP.URB.TOTL）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-10）。

---

## 快速上手

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-climate-change-indicators-for-ethiopia")
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` | 字符串型 | 0.0% | 埃塞俄比亚 |
| `country_iso3` | 字符串型 | 0.0% | ETH |
| `year` | 64位整型 | 0.0% | 1960.0 – 2025.0（均值2001.2873） |
| `indicator_name` | 字符串型 | 0.0% | 人口超过100万的城市集聚区人口占总人口比例、城镇人口占总人口比例、城镇人口总量 |
| `indicator_code` | 字符串型 | 0.0% | EN.URB.MCTY.TL.ZS、SP.URB.TOTL.IN.ZS、SP.URB.TOTL |
| `value` | 64位浮点型 | 0.0% | -1617210000.0 – 935320000.0（均值2556191.6673） |
| `esa_source` | 字符串型 | 0.0% | HDX |
| `esa_processed` | 字符串型 | 0.0% | 2026-04-10 |

---

## 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 | 2001.2873 | 2004.0 |
| `value` | -1617210000.0 | 935320000.0 | 2556191.6673 | 18.5 |

---

## 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（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）按照80/20的比例划分为训练集与测试集，并保存为Snappy压缩的Parquet格式文件。

---

## 数据集局限性

- 数据源自世界银行集团，尚未由Electric Sheep Africa进行独立验证。
- 自动化清洗流程无法修正原始数据收集阶段存在的错报值、定义不一致或抽样偏差问题。
- 如需查看发布方提供的方法说明与免责声明，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-ethiopia)。

---

## 引用格式

bibtex
@dataset{hdx_africa_world_bank_climate_change_indicators_for_ethiopia,
title = {Ethiopia - Climate Change},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-ethiopia},
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。*