electricsheepafrica/africa-world-bank-urban-development-indicators-for-zambia

--- 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 - zmb pretty_name: "Zambia - Urban Development" dataset_info: splits: - name: train num_examples: 516 - name: test num_examples: 129 --- # Zambia - Urban Development **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-zambia) · **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-zambia) 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: **ZMB**. *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)** | 646 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 516 rows | | **Test split** | 129 rows | | **Geographic scope** | ZMB | | **Publisher** | World Bank Group | | **HDX last updated** | 2026-03-27 | --- ## Variables **Geographic** — `country_name` (Zambia), `country_iso3` (ZMB), `year` (range 1960.0–2025.0). **Outcome / Measurement** — `value` (range 0.0–9691992.0). **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-zambia") 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% | Zambia | | `country_iso3` | object | 0.0% | ZMB | | `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 1995.1115) | | `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% | 0.0 – 9691992.0 (mean 604859.6232) | | `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 | 1995.1115 | 1997.0 | | `value` | 0.0 | 9691992.0 | 604859.6232 | 31.6759 | --- ## 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-zambia) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_urban_development_indicators_for_zambia, title = {Zambia - Urban Development}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-zambia}, 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: - 现有文本采集 language: - 英语 license: cc-by-4.0 multilinguality: - 单语言 size_categories: - 数据量少于1000条 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，简称HDX） - Electric Sheep Africa - 发展 - 指标 - ZMB（赞比亚ISO 3166-1 alpha-3代码） pretty_name: "赞比亚——城市发展" dataset_info: splits: - name: train num_examples: 516 - name: test num_examples: 129 # 赞比亚——城市发展 **发布方**：世界银行集团 · **来源**：[HDX（Humanitarian Data Exchange，简称HDX）](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-zambia) · **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-zambia)。 城市具备极高的运行效率：为聚居人群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也更为便捷。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同步加剧。本数据集涉及的城市化、交通拥堵与空气污染数据，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相关机构。 本数据集的每一行均代表国家层面的汇总统计数据。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：**ZMB**。 *本数据集已由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为适合机器学习使用的Parquet（列存数据格式）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** | 646 | | **列数** | 8列（2列数值型、6列分类型、0列日期时间型） | | **训练集划分** | 516行 | | **测试集划分** | 129行 | | **地理覆盖范围** | ZMB | | **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：赞比亚）、`country_iso3`（国家ISO 3代码：ZMB）、`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0.0–9691992.0）。 **标识符/元数据变量** — `indicator_name`（指标名称：最大城市人口、最大城市人口（占城镇人口比例）、百万以上人口城市集聚区人口）、`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）。 --- ## 快速使用示例 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-urban-development-indicators-for-zambia") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 数据模式（Schema） | 列名 | 数据类型 | 缺失率 | 取值范围/示例值 | |---|---|---|---| | `"country_name"` | 字符型 | 0.0% | 赞比亚 | | `"country_iso3"` | 字符型 | 0.0% | ZMB | | `"year"` | 64位整型 | 0.0% | 1960.0 – 2025.0（平均值：1995.1115） | | `"indicator_name"` | 字符型 | 0.0% | 最大城市人口、最大城市人口（占城镇人口比例）、百万以上人口城市集聚区人口 | | `"indicator_code"` | 字符型 | 0.0% | EN.URB.LCTY、EN.URB.LCTY.UR.ZS、EN.URB.MCTY | | `"value"` | 64位浮点型 | 0.0% | 0.0 – 9691992.0（平均值：604859.6232） | | `"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 | 平均值 | 中位数 | |---|---|---|---|---| | `"year"` | 1960.0 | 2025.0 | 1995.1115 | 1997.0 | | `"value"` | 0.0 | 9691992.0 | 604859.6232 | 31.6759 | --- ## 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。所有列名均转为小写并标准化为蛇形命名法。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。本数据集采用固定随机种子（42）按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，未经过Electric Sheep Africa的独立验证。 - 自动化清洗流程无法修正原始数据收集阶段的错报值、定义不一致或抽样偏差问题。 - 如需查看发布方的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-urban-development-indicators-for-zambia)。 --- ## 引用格式 bibtex @dataset{hdx_africa_world_bank_urban_development_indicators_for_zambia, title = {Zambia - Urban Development}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-zambia}, 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。*