electricsheepafrica/africa-world-bank-economy-and-growth-indicators-for-cameroon
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--- annotations_creators: - no-annotation language_creators: - found language: - en license: cc-by-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - tabular-regression task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - economics - indicators - cmr pretty_name: "Cameroon - Economy and Growth" dataset_info: splits: - name: train num_examples: 10356 - name: test num_examples: 2589 --- # Cameroon - Economy and Growth **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-economy-and-growth-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. Economic growth is central to economic development. When national income grows, real people benefit. While there is no known formula for stimulating economic growth, data can help policy-makers better understand their countries' economic situations and guide any work toward improvement. Data here covers measures of economic growth, such as gross domestic product (GDP) and gross national income (GNI). It also includes indicators representing factors known to be relevant to economic growth, such as capital stock, employment, investment, savings, consumption, government spending, imports, and exports. 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** | Humanitarian and development data | | **Unit of observation** | Country-level aggregates | | **Rows (total)** | 12,945 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 10,356 rows | | **Test split** | 2,589 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 -1513466539711.75–33304200000000.0). **Identifier / Metadata** — `indicator_name` (GDP (constant LCU), Gross national expenditure (constant 2015 US$), Gross capital formation (constant 2015 US$)), `indicator_code` (NY.GDP.MKTP.KN, NE.DAB.TOTL.KD, NE.GDI.TOTL.KD), `esa_source` (HDX), `esa_processed` (2026-04-15). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-economy-and-growth-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 1996.539) | | `indicator_name` | object | 0.0% | GDP (constant LCU), Gross national expenditure (constant 2015 US$), Gross capital formation (constant 2015 US$) | | `indicator_code` | object | 0.0% | NY.GDP.MKTP.KN, NE.DAB.TOTL.KD, NE.GDI.TOTL.KD | | `value` | float64 | 0.0% | -1513466539711.75 – 33304200000000.0 (mean 871367505250.4517) | | `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 | 1996.539 | 1997.0 | | `value` | -1513466539711.75 | 33304200000000.0 | 871367505250.4517 | 25730096.5938 | --- ## 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-economy-and-growth-indicators-for-cameroon) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_economy_and_growth_indicators_for_cameroon, title = {Cameroon - Economy and Growth}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-economy-and-growth-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.*
--- 注释创建者： - 无注释 语言生成方式： - 发现式（从公开资源中抓取获取） 语言： - 英语 许可证： - CC-BY 4.0 多语言属性： - 单语言 数据规模分类： - 10000 < 样本数 < 100000 源数据集： - 原创数据集 任务类别： - 表格回归 任务子类别： - 无 标签： - 非洲 - 人道主义 - HDX - Electric Sheep Africa - 经济学 - 指标 - CMR 美观名称: "喀麦隆——经济与增长" 数据集信息： 拆分方式： - 名称：训练集（train），样本数：10356 - 名称：测试集（test），样本数：2589 --- # 喀麦隆——经济与增长 **发布方**：世界银行集团 · **数据源**：[人道主义数据交换平台（HDX）](https://data.humdata.org/dataset/world-bank-economy-and-growth-indicators-for-cameroon) · **许可证**：`CC-BY` · **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/）](http://data.worldbank.org/)的公开数据。此外，人道主义数据交换平台（HDX）上还提供了一份整合后的喀麦隆国家数据集（https://data.humdata.org/dataset/world-bank-combined-indicators-for-cameroon）。 经济增长是经济发展的核心议题。当国民收入实现增长时，普通民众将切实获益。尽管目前尚无公认的经济增长刺激方案，数据仍可帮助政策制定者更好地理解本国经济状况，并为经济改善工作提供指引。本数据集涵盖经济增长相关衡量指标，例如国内生产总值（GDP, Gross Domestic Product）与国民总收入（GNI, Gross National Income）；同时包含与经济增长密切相关的各类影响因素指标，如资本存量、就业、投资、储蓄、消费、政府支出、进口与出口。 本数据集的每一行均代表国家层面的汇总统计数据。数据最近一次在HDX平台更新的时间为2026-03-27。地理覆盖范围：**喀麦隆（CMR）**。 *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 | 指标项 | 详情 | |---|---| | **领域** | 人道主义与发展数据 | | **观测单元** | 国家层面汇总数据 | | **总样本行数** | 12945 | | **列数** | 8列（2列数值型、6列分类型、0列日期时间型） | | **训练集规模** | 10356行 | | **测试集规模** | 2589行 | | **地理覆盖范围** | 喀麦隆（CMR） | | **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：喀麦隆）、`country_iso3`（国家ISO3代码：CMR）、`year`（年份：取值范围1960.0至2024.0）。 ### 结果/测量变量 `value`（指标数值：取值范围-1513466539711.75至33304200000000.0）。 ### 标识/元数据变量 `indicator_name`（指标名称：例如按不变本地货币计算的GDP、按2015年不变美元计价的国民总支出、按2015年不变美元计价的资本形成总额）、`indicator_code`（指标代码：例如NY.GDP.MKTP.KN、NE.DAB.TOTL.KD、NE.GDI.TOTL.KD）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-15）。 --- ## 快速上手 python from datasets import load_dataset # 加载数据集 ds = load_dataset("electricsheepafrica/africa-world-bank-economy-and-growth-indicators-for-cameroon") # 将训练集转换为Pandas DataFrame格式 train = ds["train"].to_pandas() # 将测试集转换为Pandas DataFrame格式 test = ds["test"].to_pandas() # 打印训练集的形状 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 | 空值占比 | 取值范围/示例值 | |---|---|---|---| | `country_name` | 字符型 | 0.0% | 喀麦隆 | | `country_iso3` | 字符型 | 0.0% | CMR | | `year` | 整数型（int64） | 0.0% | 1960.0 – 2024.0（均值1996.539） | | `indicator_name` | 字符型 | 0.0% | 按不变本地货币计算的GDP、按2015年不变美元计价的国民总支出、按2015年不变美元计价的资本形成总额 | | `indicator_code` | 字符型 | 0.0% | NY.GDP.MKTP.KN、NE.DAB.TOTL.KD、NE.GDI.TOTL.KD | | `value` | 浮点型（float64） | 0.0% | -1513466539711.75 – 33304200000000.0（均值871367505250.4517） | | `esa_source` | 字符型 | 0.0% | HDX | | `esa_processed` | 字符型 | 0.0% | 2026-04-15 | --- ## 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 | 1996.539 | 1997.0 | | `value` | -1513466539711.75 | 33304200000000.0 | 871367505250.4517 | 25730096.5938 | --- ## 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（snake_case）。常见的缺失值标记（如`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。 --- ## 数据集局限性 - 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中存在的错误报告值、定义不一致问题或采样偏差。 - 有关发布方的方法论说明与注意事项，请参阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/world-bank-economy-and-growth-indicators-for-cameroon)。 --- ## 引用格式 bibtex @dataset{hdx_africa_world_bank_economy_and_growth_indicators_for_cameroon, title = {喀麦隆——经济与增长}, author = {世界银行集团}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-economy-and-growth-indicators-for-cameroon}, note = {由Electric Sheep Africa（https://huggingface.co/electricsheepafrica）重新打包为机器学习适配格式} } --- *[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。*
