electricsheepafrica/africa-world-bank-private-sector-indicators-for-eswatini

--- 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-regression task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - economics - indicators - swz pretty_name: "Eswatini - Private Sector" dataset_info: splits: - name: train num_examples: 2248 - name: test num_examples: 562 --- # Eswatini - Private Sector **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-eswatini) · **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-eswatini) on HDX. Private markets drive economic growth, tapping initiative and investment to create productive jobs and raise incomes. Trade is also a driver of economic growth as it integrates developing countries into the world economy and generates benefits for their people. Data on the private sector and trade are from the World Bank Group's Private Participation in Infrastructure Project Database, Enterprise Surveys, and Doing Business Indicators, as well as from the International Monetary Fund's Balance of Payments database and International Financial Statistics, the UN Commission on Trade and Development, the World Trade Organization, and various other sources. Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **SWZ**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Market and price monitoring | | **Unit of observation** | Country-level aggregates | | **Rows (total)** | 2,810 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 2,248 rows | | **Test split** | 562 rows | | **Geographic scope** | SWZ | | **Publisher** | World Bank Group | | **HDX last updated** | 2026-03-27 | --- ## Variables **Geographic** — `country_name` (Eswatini), `country_iso3` (SWZ), `year` (range 1960.0–2024.0). **Outcome / Measurement** — `value` (range -23.9678–3101036608.0). **Identifier / Metadata** — `indicator_name` (Merchandise imports (current US$), Merchandise trade (% of GDP), Merchandise exports (current US$)), `indicator_code` (TM.VAL.MRCH.CD.WT, TG.VAL.TOTL.GD.ZS, TX.VAL.MRCH.CD.WT), `esa_source` (HDX), `esa_processed` (2026-04-10). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-private-sector-indicators-for-eswatini") 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% | Eswatini | | `country_iso3` | object | 0.0% | SWZ | | `year` | int64 | 0.0% | 1960.0 – 2024.0 (mean 2006.0256) | | `indicator_name` | object | 0.0% | Merchandise imports (current US$), Merchandise trade (% of GDP), Merchandise exports (current US$) | | `indicator_code` | object | 0.0% | TM.VAL.MRCH.CD.WT, TG.VAL.TOTL.GD.ZS, TX.VAL.MRCH.CD.WT | | `value` | float64 | 0.0% | -23.9678 – 3101036608.0 (mean 77204279.7545) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-10 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1960.0 | 2024.0 | 2006.0256 | 2009.0 | | `value` | -23.9678 | 3101036608.0 | 77204279.7545 | 21.5274 | --- ## 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-private-sector-indicators-for-eswatini) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_private_sector_indicators_for_eswatini, title = {Eswatini - Private Sector}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-eswatini}, 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: - 获取型 language: - 英语 license: cc-by-4.0 multilinguality: - 单语言 size_categories: - 1000<样本数<10000 source_datasets: - 原始数据集 task_categories: - 表格回归 task_ids: [] tags: - 非洲 - 人道主义 - HDX - Electric Sheep Africa - 经济学 - 指标 - SWZ pretty_name: "斯威士兰 - 私营部门" dataset_info: splits: - name: 训练集 num_examples: 2248 - name: 测试集 num_examples: 562 # 斯威士兰 — 私营部门 **发布方：** 世界银行集团（World Bank Group） · **来源：** [HDX（人道主义数据交换平台，Humanitarian Data Exchange）](https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-eswatini) · **许可证：** `cc-by` · **最后更新：** 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[合并后的国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-eswatini)。 私营市场通过激发创新与投资，创造生产性就业岗位并提升居民收入，是经济增长的核心驱动力。贸易同样推动经济增长：它将发展中国家融入全球经济体系，为当地民众创造福祉。本数据集的私营部门与贸易相关数据，源自世界银行集团的《私营部门参与基础设施项目数据库》《企业调查》与《营商环境指标》，同时也来自国际货币基金组织的《国际收支数据库》与《国际金融统计》、联合国贸易和发展会议、世界贸易组织以及其他多个来源。 本数据集的每一行均代表国家级汇总数据。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：**SWZ（斯威士兰ISO 3166-1 alpha-3国家代码）**。 *本数据集已由[非洲电羊团队（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)整理为适合机器学习使用的Parquet格式。* ## 数据集特征 | | | |---|---| | **领域** | 市场与价格监测 | | **观测单元** | 国家级汇总数据 | | **总行数** | 2,810 | | **列数** | 8（2个数值型，6个分类型，0个日期时间型） | | **训练集划分** | 2,248 行 | | **测试集划分** | 562 行 | | **地理覆盖范围** | SWZ | | **发布方** | 世界银行集团 | | **HDX最后更新时间** | 2026-03-27 | ## 变量说明 **地理类变量** — `country_name`（国家名称：斯威士兰）、`country_iso3`（国家ISO3代码：SWZ）、`year`（年份：取值范围1960.0–2024.0）。 **结果/测量类变量** — `value`（指标数值：取值范围-23.9678–3101036608.0）。 **标识符/元数据类变量** — `indicator_name`（指标名称：商品进口额（现价美元）、商品贸易总额（占GDP百分比）、商品出口额（现价美元））、`indicator_code`（指标代码：TM.VAL.MRCH.CD.WT、TG.VAL.TOTL.GD.ZS、TX.VAL.MRCH.CD.WT）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理日期：2026-04-10）。 ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-private-sector-indicators-for-eswatini") 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` | 字符型（object） | 0.0% | 斯威士兰 | | `country_iso3` | 字符型（object） | 0.0% | SWZ | | `year` | 整型（int64） | 0.0% | 1960.0 – 2024.0（均值2006.0256） | | `indicator_name` | 字符型（object） | 0.0% | 商品进口额（现价美元）、商品贸易总额（占GDP百分比）、商品出口额（现价美元） | | `indicator_code` | 字符型（object） | 0.0% | TM.VAL.MRCH.CD.WT、TG.VAL.TOTL.GD.ZS、TX.VAL.MRCH.CD.WT | | `value` | 浮点型（float64） | 0.0% | -23.9678 – 3101036608.0（均值77204279.7545） | | `esa_source` | 字符型（object） | 0.0% | HDX | | `esa_processed` | 字符型（object） | 0.0% | 2026-04-10 | ## 数值统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `year` | 1960.0 | 2024.0 | 2006.0256 | 2009.0 | | `value` | -23.9678 | 3101036608.0 | 77204279.7545 | 21.5274 | ## 数据整理流程 原始数据通过CKAN应用程序编程接口（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采用蛇形命名法（snake_case）进行标准化。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，并保存为Snappy压缩的Parquet文件。 ## 局限性说明 - 本数据集的原始数据源自世界银行集团，未经过非洲电羊团队（Electric Sheep Africa，简称ESA）的独立验证。 - 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。 - 如需了解发布方的方法说明与免责条款，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-eswatini)。 ## 引用格式 bibtex @dataset{hdx_africa_world_bank_private_sector_indicators_for_eswatini, title = {斯威士兰 - 私营部门}, author = {世界银行集团}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-eswatini}, note = {由非洲电羊团队（https://huggingface.co/electricsheepafrica）重新打包为机器学习可用格式} } *[非洲电羊团队（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica) — 非洲机器学习数据集基础设施提供商，总部位于尼日利亚拉各斯。*