electricsheepafrica/africa-world-bank-environment-indicators-for-cameroon

--- 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 - cmr pretty_name: "Cameroon - Environment" dataset_info: splits: - name: train num_examples: 3919 - name: test num_examples: 979 --- # Cameroon - Environment **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-environment-indicators-for-cameroon) · **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-cameroon) 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: **CMR**. *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)** | 4,899 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 3,919 rows | | **Test split** | 979 rows | | **Geographic scope** | CMR | | **Publisher** | World Bank Group | | **HDX last updated** | 2026-03-27 | --- ## Variables **Geographic** — `country_name` (Cameroon), `country_iso3` (CMR), `year` (range 1960.0–2024.0). **Outcome / Measurement** — `value` (range -1740078727.6168–5040301570.7625). **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` (2026-04-15). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-environment-indicators-for-cameroon") 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% | Cameroon | | `country_iso3` | object | 0.0% | CMR | | `year` | int64 | 0.0% | 1960.0 – 2024.0 (mean 2000.0267) | | `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% | -1740078727.6168 – 5040301570.7625 (mean 43661151.1888) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-15 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1960.0 | 2024.0 | 2000.0267 | 2002.0 | | `value` | -1740078727.6168 | 5040301570.7625 | 43661151.1888 | 3.7105 | --- ## 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-cameroon) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_environment_indicators_for_cameroon, title = {Cameroon - Environment}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-environment-indicators-for-cameroon}, 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（no-annotation） language_creators: - 采集所得（found） language: - 英语（en） license: cc-by-4.0 multilinguality: - 单语言（monolingual） size_categories: - 1000<n<10000 source_datasets: - 原创数据集（original） task_categories: - 表格分类（tabular-classification） - 表格回归（tabular-regression） task_ids: [] tags: - 非洲（africa） - 人道主义（humanitarian） - HDX（Humanitarian Data Exchange） - Electric Sheep Africa（electric-sheep-africa） - 环境（environment） - 指标（indicators） - CMR pretty_name: "喀麦隆——环境" dataset_info: splits: - name: train num_examples: 3919 - name: test num_examples: 979 # 喀麦隆——环境 **发布方:** 世界银行集团 · **数据源:** [HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/world-bank-environment-indicators-for-cameroon) · **许可证:** `cc-by` · **最后更新时间:** 2026-03-27 --- ## 摘要 本数据集包含世界银行[数据门户](http://data.worldbank.org/)的公开数据。HDX平台上另有一份[整合型国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-cameroon)可供获取。 自然与人工环境资源——包括淡水、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。保护此类资源的需求不受国界限制。当前，世界银行是发展中经济体环境升级改造的核心推动者与融资方之一。本数据集收录的数据涵盖森林、生物多样性、碳排放与污染相关内容。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对应的数据页面中查阅。 本数据集的每一行均代表国家级聚合统计数据。本数据集在HDX平台的最后更新时间为2026-03-27。地理覆盖范围：**CMR（喀麦隆）**。 *本数据集已由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为适用于机器学习的Parquet格式（Parquet）。* --- ## 数据集特征 | | | |---|---| | **领域** | 水、环境卫生与个人卫生（Water, Sanitation and Hygiene，WASH） | | **观测单元** | 国家级聚合统计数据 | | **总样本行数** | 4,899 | | **总列数** | 8（2个数值型列，6个分类型列，0个日期时间列） | | **训练集样本数** | 3,919 | | **测试集样本数** | 979 | | **地理覆盖范围** | CMR（喀麦隆） | | **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 **地理标识类字段** — `country_name`（国家名称：喀麦隆）、`country_iso3`（国家ISO3代码：CMR）、`year`（年份范围：1960.0–2024.0）。 **结果/测量类字段** — `value`（指标数值，取值范围：-1740078727.6168–5040301570.7625）。 **标识符/元数据类字段** — `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：2026-04-15）。 --- ## 快速入门 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-environment-indicators-for-cameroon") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 数据结构（Schema） | 列名 | 数据类型 | 空值占比 | 取值范围/示例值 | |---|---|---|---| | `country_name` | 字符串（object） | 0.0% | 喀麦隆 | | `country_iso3` | 字符串（object） | 0.0% | CMR | | `year` | 64位整数（int64） | 0.0% | 1960.0 – 2024.0（均值2000.0267） | | `indicator_name` | 字符串（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` | 字符串（object） | 0.0% | ER.FSH.PROD.MT、ER.FSH.CAPT.MT、ER.FSH.AQUA.MT | | `value` | 64位浮点数（float64） | 0.0% | -1740078727.6168 – 5040301570.7625（均值43661151.1888） | | `esa_source` | 字符串（object） | 0.0% | HDX | | `esa_processed` | 字符串（object） | 0.0% | 2026-04-15 | --- ## 数值型字段统计摘要 | 列名 | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1960.0 | 2024.0 | 2000.0267 | 2002.0 | | `value` | -1740078727.6168 | 5040301570.7625 | 43661151.1888 | 3.7105 | --- ## 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。列名均转换为小写并标准化为蛇形命名法（snake_case）。常见缺失值标记（`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）按照80/20的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 - 本数据集源自世界银行集团，未由Electric Sheep Africa进行独立验证。 - 自动化清洗流程无法修正原始数据收集中的错报值、定义不一致或抽样偏差问题。 - 如需查看发布方提供的方法说明与免责声明，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-environment-indicators-for-cameroon)。 --- ## 引用格式 bibtex @dataset{hdx_africa_world_bank_environment_indicators_for_cameroon, title = {Cameroon - Environment}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-environment-indicators-for-cameroon}, 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提供商。尼日利亚拉各斯。*