electricsheepafrica/africa-world-bank-urban-development-indicators-for-sudan
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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 - indicators - sdn pretty_name: "Sudan - Urban Development" dataset_info: splits: - name: train num_examples: 474 - name: test num_examples: 118 --- # Sudan - Urban Development **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-sudan) · **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-sudan) 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 2026-03-27. Geographic scope: **SDN**. *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)** | 593 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 474 rows | | **Test split** | 118 rows | | **Geographic scope** | SDN | | **Publisher** | World Bank Group | | **HDX last updated** | 2026-03-27 | --- ## Variables **Geographic** — `country_name` (Sudan), `country_iso3` (SDN), `year` (range 1960.0–2025.0). **Outcome / Measurement** — `value` (range 0.0007–17590192.0). **Identifier / Metadata** — `indicator_name` (Population in largest city, Population in the largest city (% of urban population), Population in urban agglomerations of more than 1 million), `indicator_code` (EN.URB.LCTY, EN.URB.LCTY.UR.ZS, EN.URB.MCTY), `esa_source` (HDX), `esa_processed` (2026-04-09). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-urban-development-indicators-for-sudan") 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% | Sudan | | `country_iso3` | object | 0.0% | SDN | | `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 1995.8516) | | `indicator_name` | object | 0.0% | Population in largest city, Population in the largest city (% of urban population), Population in urban agglomerations of more than 1 million | | `indicator_code` | object | 0.0% | EN.URB.LCTY, EN.URB.LCTY.UR.ZS, EN.URB.MCTY | | `value` | float64 | 0.0% | 0.0007 – 17590192.0 (mean 1446891.3003) | | `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 | 1995.8516 | 1999.0 | | `value` | 0.0007 | 17590192.0 | 1446891.3003 | 39.0718 | --- ## 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-urban-development-indicators-for-sudan) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_urban_development_indicators_for_sudan, title = {Sudan - Urban Development}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-sudan}, 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.*
注释生成者： - 无注释 语言数据生成方式： - 公开数据源采集 语言： - 英语 授权协议：知识共享署名4.0（CC BY 4.0） 多语言类型： - 单语言 样本量分类： - 样本量小于1000 源数据集： - 原始数据集 任务类别： - 表格分类 - 表格回归 任务子类别： - [] 标签： - 非洲 - 人道主义 - 人类数据交换（HDX） - 电动绵羊非洲（Electric Sheep Africa） - 发展 - 指标 - SDN 美观名称："苏丹——城市发展" 数据集信息： 划分： - 名称：训练集 样本数：474 - 名称：测试集 样本数：118 # 苏丹——城市发展数据集 **发布方：世界银行集团（World Bank Group）** · **数据源：[人类数据交换平台（HDX）](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-sudan)** · **授权协议：`CC BY`** · **更新时间：2026-03-27** --- ## 摘要 本数据集包含源自世界银行[数据门户（data.worldbank.org）](http://data.worldbank.org/)的相关数据。人类数据交换平台（HDX）上还提供了一份整合后的苏丹国家综合数据集[链接](https://data.humdata.org/dataset/world-bank-combined-indicators-for-sudan)。 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可及性也显著提升。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大。本数据集涉及的城市化、交通拥堵与空气污染相关数据，分别源自联合国人口司、世界卫生组织、国际道路联合会、世界资源研究所及其他多家机构。 本数据集的每一行均代表国家级汇总统计数据。该数据集在HDX平台的最后更新时间为2026-03-27，地理覆盖范围为**SDN（苏丹）**。 *本数据集已由[电动绵羊非洲团队（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)整理为适配机器学习的Parquet格式。* --- ## 数据集特征 | 项目 | 内容 | |---|---| | **领域** | 公共卫生 | | **观测单元** | 国家级汇总统计数据 | | **总样本行数** | 593 | | **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** | 474行 | | **测试集划分** | 118行 | | **地理覆盖范围** | SDN（苏丹） | | **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：苏丹）、`country_iso3`（国家ISO3代码：SDN）、`year`（年份：取值范围1960.0–2025.0）。 **结果/测量类变量** — `value`（指标数值：取值范围0.0007–17590192.0）。 **标识符/元数据类变量** — `indicator_name`（指标名称：最大城市人口数、最大城市人口占城镇人口比例、百万人口以上城市聚集区人口）；`indicator_code`（指标代码：EN.URB.LCTY、EN.URB.LCTY.UR.ZS、EN.URB.MCTY）；`esa_source`（数据来源：HDX）；`esa_processed`（数据处理时间：2026-04-09）。 --- ## 快速入门 python from datasets import load_dataset # 加载数据集 ds = load_dataset("electricsheepafrica/africa-world-bank-urban-development-indicators-for-sudan") # 将训练集、测试集转换为Pandas DataFrame格式 train = ds["train"].to_pandas() test = ds["test"].to_pandas() # 打印训练集维度 print(train.shape) # 查看训练集前5行数据 train.head() --- ## 数据模式 | 列名 | 数据类型 | 缺失率 | 取值范围/示例值 | |---|---|---|---| | `country_name` | 字符串（object） | 0.0% | 苏丹 | | `country_iso3` | 字符串（object） | 0.0% | SDN | | `year` | 64位整数（int64） | 0.0% | 1960.0 – 2025.0（均值1995.8516） | | `indicator_name` | 字符串（object） | 0.0% | 最大城市人口数、最大城市人口占城镇人口比例、百万人口以上城市聚集区人口 | | `indicator_code` | 字符串（object） | 0.0% | EN.URB.LCTY、EN.URB.LCTY.UR.ZS、EN.URB.MCTY | | `value` | 64位浮点数（float64） | 0.0% | 0.0007 – 17590192.0（均值1446891.3003） | | `esa_source` | 字符串（object） | 0.0% | HDX | | `esa_processed` | 字符串（object） | 0.0% | 2026-04-09 | --- ## 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 | 1995.8516 | 1999.0 | | `value` | 0.0007 | 17590192.0 | 1446891.3003 | 39.0718 | --- ## 数据整理流程 原始数据通过CKAN应用程序编程接口（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（snake_case）。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 1. 本数据集源自世界银行集团，尚未由电动绵羊非洲团队（ESA）进行独立验证。 2. 自动化数据清洗无法修正原始数据中存在的数值错报、定义不一致或采样偏差问题。 3. 如需了解发布方的方法说明与免责声明，请参阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-sudan)。 --- ## 引用格式 bibtex @dataset{hdx_africa_world_bank_urban_development_indicators_for_sudan, title = {苏丹——城市发展}, author = {世界银行集团}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-sudan}, note = {由电动绵羊非洲团队（Electric Sheep Africa）重新打包适配机器学习应用（https://huggingface.co/electricsheepafrica)} } --- *[电动绵羊非洲团队（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica) — 非洲机器学习数据集基础设施提供商，尼日利亚拉各斯。*
