electricsheepafrica/africa-world-bank-environment-indicators-for-zambia
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--- 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 - environment - indicators - zmb pretty_name: "Zambia - Environment" dataset_info: splits: - name: train num_examples: 3784 - name: test num_examples: 946 --- # Zambia - Environment **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-environment-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. Natural and man-made environmental resources – fresh water, clean air, forests, grasslands, marine resources, and agro-ecosystems – provide sustenance and a foundation for social and economic development. The need to safeguard these resources crosses all borders. Today, the World Bank is one of the key promoters and financiers of environmental upgrading in the developing world. Data here cover forests, biodiversity, emissions, and pollution. Other indicators relevant to the environment are found under data pages for Agriculture & Rural Development, Energy & Mining, Infrastructure, and Urban Development. 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** | Water, sanitation and hygiene (wash) | | **Unit of observation** | Country-level aggregates | | **Rows (total)** | 4,730 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 3,784 rows | | **Test split** | 946 rows | | **Geographic scope** | ZMB | | **Publisher** | World Bank Group | | **HDX last updated** | 2026-03-27 | --- ## Variables **Geographic** — `country_name` (Zambia), `country_iso3` (ZMB), `year` (range 1960.0–2024.0). **Outcome / Measurement** — `value` (range -360670000.0–6611117739.78). **Identifier / Metadata** — `indicator_name` (Total fisheries production (metric tons), Capture fisheries production (metric tons), Aquaculture production (metric tons)), `indicator_code` (ER.FSH.PROD.MT, ER.FSH.CAPT.MT, ER.FSH.AQUA.MT), `esa_source` (HDX), `esa_processed` (2026-04-09). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-environment-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 – 2024.0 (mean 2000.36) | | `indicator_name` | object | 0.0% | Total fisheries production (metric tons), Capture fisheries production (metric tons), Aquaculture production (metric tons) | | `indicator_code` | object | 0.0% | ER.FSH.PROD.MT, ER.FSH.CAPT.MT, ER.FSH.AQUA.MT | | `value` | float64 | 0.0% | -360670000.0 – 6611117739.78 (mean 58780425.3472) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-09 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1960.0 | 2024.0 | 2000.36 | 2003.0 | | `value` | -360670000.0 | 6611117739.78 | 58780425.3472 | 3.6297 | --- ## 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-environment-indicators-for-zambia) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_environment_indicators_for_zambia, title = {Zambia - Environment}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-environment-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.*
注释生成方式： - 无注释 语言生成方式： - 现有资源采集 语言： - 英语 许可协议：CC BY 4.0 多语言类型： - 单语言 数据规模： - 1000 < 样本数 < 10000 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： - 无 标签： - 非洲 - 人道主义 - HDX（人道主义数据交换平台） - Electric Sheep Africa - 环境 - 指标 - ZMB 美观名称："赞比亚——环境" 数据集信息： 数据集划分： - 名称：训练集，样本数量：3784 - 名称：测试集，样本数量：946 # 赞比亚——环境 **发布方**：世界银行集团 · **数据来源**：[HDX（人道主义数据交换平台）](https://data.humdata.org/dataset/world-bank-environment-indicators-for-zambia) · **许可协议**：`cc-by` · **最后更新时间**：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[赞比亚综合国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-zambia)可供获取。 自然与人工环境资源——淡水、洁净空气、森林、草原、海洋资源以及农业生态系统——为社会与经济发展提供了支撑与基础。保护这些资源的需求无国界之分。如今，世界银行是发展中国家环境升级的核心推动者与融资方之一。本数据集涵盖森林、生物多样性、碳排放与污染相关数据。其他与环境相关的指标可在农业与农村发展、能源与矿业、基础设施以及城市发展的数据页面中获取。 本数据集的每一行均代表国家级汇总数据。数据最后于2026-03-27在HDX平台更新。地理覆盖范围：**ZMB**。 *本数据集由[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 | | | |---|---| | **领域** | 水、环境卫生与个人卫生（Water, Sanitation and Hygiene，简称WASH） | | **观测单元** | 国家级汇总数据 | | **总样本行数** | 4730 | | **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** | 3784行 | | **测试集划分** | 946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`（ISO 3位国家代码：ZMB）、`year`（年份范围：1960.0~2024.0）。 **结果/测量类变量** — `value`（指标数值，取值范围：-360670000.0~6611117739.78）。 **标识符/元数据类变量** — `indicator_name`（指标名称：渔业总产量（公吨）、捕捞渔业产量（公吨）、水产养殖产量（公吨））、`indicator_code`（指标代码：ER.FSH.PROD.MT、ER.FSH.CAPT.MT、ER.FSH.AQUA.MT）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-09）。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-environment-indicators-for-zambia") 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` | 对象型（object） | 0.0% | 赞比亚 | | `country_iso3` | 对象型（object） | 0.0% | ZMB | | `year` | 64位整型（int64） | 0.0% | 1960.0~2024.0（均值：2000.36） | | `indicator_name` | 对象型（object） | 0.0% | 渔业总产量（公吨）、捕捞渔业产量（公吨）、水产养殖产量（公吨） | | `indicator_code` | 对象型（object） | 0.0% | ER.FSH.PROD.MT、ER.FSH.CAPT.MT、ER.FSH.AQUA.MT | | `value` | 64位浮点型（float64） | 0.0% | -360670000.0~6611117739.78（均值：58780425.3472） | | `esa_source` | 对象型（object） | 0.0% | HDX | | `esa_processed` | 对象型（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 | 2024.0 | 2000.36 | 2003.0 | | `value` | -360670000.0 | 6611117739.78 | 58780425.3472 | 3.6297 | --- ## 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标准化为蛇形命名法（snake_case）。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80/20的比例划分为训练集与测试集，并以Snappy压缩格式的Parquet文件保存。 --- ## 数据局限性 - 本数据集源自世界银行集团，Electric Sheep Africa（ESA）未对其进行独立验证。 - 自动化清洗流程无法修正原始数据集中的错报值、定义不一致问题或采样偏差。 - 如需了解发布方的方法说明与注意事项，请参阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/world-bank-environment-indicators-for-zambia)。 --- ## 引用格式 bibtex @dataset{hdx_africa_world_bank_environment_indicators_for_zambia, title = {Zambia - Environment}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-environment-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。*
