electricsheepafrica/africa-world-bank-urban-development-indicators-for-federal-republic-of-somalia
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---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- development
- hxl
- indicators
- som
pretty_name: "Federal Republic of Somalia - Urban Development"
dataset_info:
splits:
- name: train
num_examples: 502
- name: test
num_examples: 125
---
# Federal Republic of Somalia - Urban Development
**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-federal-republic-of-somalia) · **License:** `cc-by` · **Updated:** 2025-11-04
---
## 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-federal-republic-of-somalia) on HDX.
Cities can be tremendously efficient. It is easier to provide water and sanitation to people living closer together, while access to health, education, and other social and cultural services is also much more readily available. However, as cities grow, the cost of meeting basic needs increases, as does the strain on the environment and natural resources. Data on urbanization, traffic and congestion, and air pollution are from the United Nations Population Division, World Health Organization, International Road Federation, World Resources Institute, and other sources.
Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2025-11-04. Geographic scope: **SOM**.
*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)** | 628 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 502 rows |
| **Test split** | 125 rows |
| **Geographic scope** | SOM |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2025-11-04 |
---
## Variables
**Geographic** — `country_name` (Federal Republic of Somalia, #country+name), `country_iso3` (SOM, #country+code), `year` (range 1960.0–2024.0).
**Outcome / Measurement** — `value` (range -4.4311–9223050.0).
**Identifier / Metadata** — `indicator_name` (Urban population (% of total population), Population in the largest city (% of urban population), Urban population), `indicator_code` (SP.URB.TOTL.IN.ZS, EN.URB.LCTY.UR.ZS, SP.URB.TOTL), `esa_source` (HDX), `esa_processed` (2026-04-07).
---
## Quick Start
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-world-bank-urban-development-indicators-for-federal-republic-of-somalia")
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% | Federal Republic of Somalia, #country+name |
| `country_iso3` | object | 0.0% | SOM, #country+code |
| `year` | float64 | 0.2% | 1960.0 – 2024.0 (mean 1994.807) |
| `indicator_name` | object | 0.0% | Urban population (% of total population), Population in the largest city (% of urban population), Urban population |
| `indicator_code` | object | 0.0% | SP.URB.TOTL.IN.ZS, EN.URB.LCTY.UR.ZS, SP.URB.TOTL |
| `value` | float64 | 0.2% | -4.4311 – 9223050.0 (mean 528204.0597) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-07 |
---
## Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2024.0 | 1994.807 | 1997.0 |
| `value` | -4.4311 | 9223050.0 | 528204.0597 | 29.9551 |
---
## 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`. 2 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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-urban-development-indicators-for-federal-republic-of-somalia) for the publisher's own methodology notes and caveats.
---
## Citation
```bibtex
@dataset{hdx_africa_world_bank_urban_development_indicators_for_federal_republic_of_somalia,
title = {Federal Republic of Somalia - Urban Development},
author = {World Bank Group},
year = {2025},
url = {https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-federal-republic-of-somalia},
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（found）
language:
- 英语
license: cc-by-4.0
multilinguality:
- 单语言
size_categories:
- 样本量少于1000条
source_datasets:
- 原始数据集
task_categories:
- 表格分类任务（tabular-classification）
- 表格回归任务（tabular-regression）
task_ids: []
tags:
- 非洲
- 人道主义
- HDX
- electric-sheep-africa
- 发展
- HXL
- 指标
- SOM
pretty_name: "索马里联邦共和国——城市发展"
dataset_info:
splits:
- name: 训练集
num_examples: 502
- name: 测试集
num_examples: 125
# 索马里联邦共和国——城市发展
**发布方**：世界银行集团 · **来源**：[人道主义数据交换（Humanitarian Data Exchange，HDX）](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-federal-republic-of-somalia) · **许可协议**：`cc-by` · **最后更新时间**：2025-11-04
---
## 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。同时，HDX平台上还提供了一份[整合后的国家级数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-federal-republic-of-somalia)。
城市具备极高的运行效率：为聚居人口提供供水与卫生设施的成本更低，同时医疗、教育及其他社会文化服务的获取门槛也大幅降低。然而，随着城市扩张，满足居民基本需求的成本不断攀升，对环境与自然资源的压力也随之加剧。本数据集涉及的城市化、交通拥堵与空气污染相关数据，分别来自联合国人口司、世界卫生组织、国际道路联合会、世界资源研究所及其他权威机构。
本数据集的每一行均代表国家层面的汇总统计数据。HDX平台上的该数据集最后更新于2025年11月4日。地理覆盖范围：**SOM（索马里）**。
*本数据集已由[电羊非洲（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** | 公共卫生 |
| **观测单元** | 国家层面汇总数据 |
| **总行数** | 628 |
| **列数** | 8（其中数值型2列、分类型6列，无日期时间型列） |
| **训练集划分** | 502条数据 |
| **测试集划分** | 125条数据 |
| **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** | 2025-11-04 |
---
## 变量说明
### 地理类变量
`country_name`（索马里联邦共和国，#country+name）、`country_iso3`（SOM，#country+code）、`year`（取值范围1960.0–2024.0）。
### 结果/测量类变量
`value`（取值范围-4.4311–9223050.0）。
### 标识符/元数据类变量
`indicator_name`（城镇人口占总人口比例、最大城市人口占城镇人口比例、城镇人口总数）、`indicator_code`（SP.URB.TOTL.IN.ZS、EN.URB.LCTY.UR.ZS、SP.URB.TOTL）、`esa_source`（HDX）、`esa_processed`（2026-04-07）。
---
## 快速上手示例
python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-world-bank-urban-development-indicators-for-federal-republic-of-somalia")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()
---
## 数据Schema
| 列名 | 数据类型 | 空值占比 | 取值范围/示例值 |
|---|---|---|
| `country_name` | 字符型 | 0.0% | 索马里联邦共和国，#country+name |
| `country_iso3` | 字符型 | 0.0% | SOM，#country+code |
| `year` | 浮点型 | 0.2% | 1960.0 – 2024.0（均值1994.807） |
| `indicator_name` | 字符型 | 0.0% | 城镇人口占总人口比例、最大城市人口占城镇人口比例、城镇人口总数 |
| `indicator_code` | 字符型 | 0.0% | SP.URB.TOTL.IN.ZS、EN.URB.LCTY.UR.ZS、SP.URB.TOTL |
| `value` | 浮点型 | 0.2% | -4.4311 – 9223050.0（均值528204.0597） |
| `esa_source` | 字符型 | 0.0% | HDX |
| `esa_processed` | 字符型 | 0.0% | 2026-04-07 |
---
## 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 | 2024.0 | 1994.807 | 1997.0 |
| `value` | -4.4311 | 9223050.0 | 528204.0597 | 29.9551 |
---
## 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。对列名进行了小写转换与蛇形命名标准化处理。将常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。基于解析成功率（阈值>85%），将2列从字符型转换为数值型或日期时间型。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
- 本数据集源自世界银行集团，尚未由电羊非洲进行独立验证。
- 自动化清洗流程无法修正原始数据集中的错报值、定义不一致问题或原始采集阶段的抽样偏差。
- 如需查看发布方提供的官方方法论说明与免责条款，请参阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-federal-republic-of-somalia)。
---
## 引用格式
bibtex
@dataset{hdx_africa_world_bank_urban_development_indicators_for_federal_republic_of_somalia,
title = {索马里联邦共和国——城市发展},
author = {世界银行集团},
year = {2025},
url = {https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-federal-republic-of-somalia},
note = {由电羊非洲（https://huggingface.co/electricsheepafrica）重新打包以适配机器学习场景}
}
---
*[电羊非洲（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。*
提供机构：
electricsheepafrica
