electricsheepafrica/africa-world-bank-climate-change-indicators-for-somalia-fed-rep

---
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
- som
pretty_name: "Somalia, Fed. Rep. - Climate Change"
dataset_info:
splits:
- name: train
num_examples: 1029
- name: test
num_examples: 257
---

# Somalia, Fed. Rep. - Climate Change

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

*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)** | 1,287 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 1,029 rows |
| **Test split** | 257 rows |
| **Geographic scope** | SOM |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Somalia, Fed. Rep.), `country_iso3` (SOM), `year` (range 1960.0–2025.0).

**Outcome / Measurement** — `value` (range -4.7895–42940000.0).

**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` (2026-04-09).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-climate-change-indicators-for-somalia-fed-rep")
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% | Somalia, Fed. Rep. |
| `country_iso3` | object | 0.0% | SOM |
| `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 1997.6356) |
| `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% | -4.7895 – 42940000.0 (mean 726541.0219) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-09 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 1997.6356 | 2001.0 |
| `value` | -4.7895 | 42940000.0 | 726541.0219 | 27.7225 |

---

## 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-somalia-fed-rep) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_climate_change_indicators_for_somalia_fed_rep,
title = {Somalia, Fed. Rep. - Climate Change},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-somalia-fed-rep},
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.*

注释创作者：
- 无注释
语言采集方式：
- 公开获取自现有资源
语言：
- 英语
许可证：CC BY 4.0（知识共享署名4.0国际许可协议）
多语言类型：
- 单语言
数据规模：
- 1000<n<10000
源数据集：
- 原生数据集
任务类别：
- 表格分类
- 表格回归
任务子类别：
- 无
标签：
- 非洲
- 人道主义
- HDX（人道主义数据交换平台）
- Electric Sheep Africa（电羊非洲）
- 气候与气象
- 指标
- SOM（索马里国家ISO3代码）
数据集名称："索马里联邦共和国——气候变化"
数据集信息：
划分集：
- 名称：训练集
样本数：1029
- 名称：测试集
样本数：257

# 索马里联邦共和国——气候变化

**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-climate-change-indicators-for-somalia-fed-rep) · **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平台上另有一份[索马里联邦共和国综合国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-somalia-fed-rep)。

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。发展中国家在消除贫困、饥饿与疾病方面取得的近期成果，以及数十亿民众的生计与生命安全，均处于风险之中。应对气候变化需要前所未有的跨境全球合作。世界银行集团正助力支持发展中国家，为全球解决方案贡献力量，同时针对不同发展中国家合作伙伴的差异化需求定制相关方案。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级汇总数据。数据最近一次在HDX平台更新的时间为2026-03-27。地理覆盖范围：**SOM（索马里）**。

*本数据集已由[Electric Sheep Africa（电羊非洲）](https://huggingface.co/electricsheepafrica)整理为适用于机器学习的Parquet格式。*

---

## 数据集特征

| | |
|---|---|
| **领域** | 粮食安全与营养 |
| **观测单元** | 国家级汇总数据 |
| **总行数** | 1287 |
| **列数** | 8列（2个数值型、6个分类型、0个日期时间型） |
| **训练集划分** | 1029行 |
| **测试集划分** | 257行 |
| **地理覆盖范围** | SOM（索马里） |
| **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`（索马里联邦共和国）、`country_iso3`（SOM国家代码）、`year`（取值范围1960.0–2025.0）。

**结果/测量类变量**：`value`（取值范围-4.7895–42940000.0）。

**标识符/元数据类变量**：`indicator_name`（百万以上人口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`（EN.URB.MCTY.TL.ZS、SP.URB.TOTL.IN.ZS、SP.URB.TOTL）、`esa_source`（HDX）、`esa_processed`（2026-04-09）。

---

## 快速上手

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-climate-change-indicators-for-somalia-fed-rep")
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 | 缺失率 | 取值范围/示例值 |
|---|---|---|---|
| `country_name` | 字符型 | 0.0% | 索马里联邦共和国 |
| `country_iso3` | 字符型 | 0.0% | SOM（索马里国家代码） |
| `year` | 64位整型 | 0.0% | 1960.0 – 2025.0（均值1997.6356） |
| `indicator_name` | 字符型 | 0.0% | 百万以上人口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` | 字符型 | 0.0% | EN.URB.MCTY.TL.ZS、SP.URB.TOTL.IN.ZS、SP.URB.TOTL |
| `value` | 64位浮点型 | 0.0% | -4.7895 – 42940000.0（均值726541.0219） |
| `esa_source` | 字符型 | 0.0% | HDX |
| `esa_processed` | 字符型 | 0.0% | 2026-04-09 |

---

## 数值统计摘要

| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 1997.6356 | 2001.0 |
| `value` | -4.7895 | 42940000.0 | 726541.0219 | 27.7225 |

---

## 数据整理说明

原始数据通过CKAN API从HDX平台下载并转换为Parquet格式。列名均转换为小写并统一为蛇形命名法。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）均被统一替换为`NaN`。本数据集以固定随机种子（42）按80/20比例划分为训练集与测试集，并以Snappy压缩格式保存为Parquet文件。

---

## 数据集局限性

- 数据源自世界银行集团，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集中的错误报告值、定义不一致或采样偏差问题。
- 请查阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-somalia-fed-rep)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_climate_change_indicators_for_somalia_fed_rep,
title = {Somalia, Fed. Rep. - Climate Change},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-somalia-fed-rep},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

*[Electric Sheep Africa（电羊非洲）](https://huggingface.co/electricsheepafrica)——非洲机器学习数据集基础设施，尼日利亚拉各斯。*