electricsheepafrica/africa-world-bank-external-debt-indicators-for-somalia-fed-rep
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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-regression task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - economics - indicators - som pretty_name: "Somalia, Fed. Rep. - External Debt" dataset_info: splits: - name: train num_examples: 1440 - name: test num_examples: 360 --- # Somalia, Fed. Rep. - External Debt **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-external-debt-indicators-for-somalia-fed-rep) · **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-somalia-fed-rep) on HDX. Debt statistics provide a detailed picture of debt stocks and flows of developing countries. Data presented as part of the Quarterly External Debt Statistics takes a closer look at the external debt of high-income countries and emerging markets to enable a more complete understanding of global financial flows. The Quarterly Public Sector Debt database provides further data on public sector valuation methods, debt instruments, and clearly defined tiers of debt for central, state and local government, as well as extra-budgetary agencies and funds. Data are gathered from national statistical organizations and central banks as well as by various major multilateral institutions and World Bank staff. Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **SOM**. *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)** | 1,800 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 1,440 rows | | **Test split** | 360 rows | | **Geographic scope** | SOM | | **Publisher** | World Bank Group | | **HDX last updated** | 2026-03-27 | --- ## Variables **Geographic** — `country_name` (Somalia, Fed. Rep.), `country_iso3` (SOM), `year` (range 1960.0–2024.0). **Outcome / Measurement** — `value` (range -350052126.8–12210000000.0). **Identifier / Metadata** — `indicator_name` (GNI (current US$), Technical cooperation grants (BoP, current US$), Net ODA received per capita (current US$)), `indicator_code` (NY.GNP.MKTP.CD, BX.GRT.TECH.CD.WD, DT.ODA.ODAT.PC.ZS), `esa_source` (HDX), `esa_processed` (2026-04-09). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-external-debt-indicators-for-somalia-fed-rep") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `country_name` | object | 0.0% | Somalia, Fed. Rep. | | `country_iso3` | object | 0.0% | SOM | | `year` | int64 | 0.0% | 1960.0 – 2024.0 (mean 1994.4972) | | `indicator_name` | object | 0.0% | GNI (current US$), Technical cooperation grants (BoP, current US$), Net ODA received per capita (current US$) | | `indicator_code` | object | 0.0% | NY.GNP.MKTP.CD, BX.GRT.TECH.CD.WD, DT.ODA.ODAT.PC.ZS | | `value` | float64 | 0.0% | -350052126.8 – 12210000000.0 (mean 347327551.2183) | | `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 | 1994.4972 | 1992.0 | | `value` | -350052126.8 | 12210000000.0 | 347327551.2183 | 1989850.05 | --- ## 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-external-debt-indicators-for-somalia-fed-rep) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_external_debt_indicators_for_somalia_fed_rep, title = {Somalia, Fed. Rep. - External Debt}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-external-debt-indicators-for-somalia-fed-rep}, 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.*
--- 标注创建者： - 无标注 语言采集方式： - 现有资源采集 语言： - 英语 授权协议：CC BY 4.0 多语言类型： - 单语言 样本量范围： - 1000 < 样本量 < 10000 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（Humanitarian Data Exchange） - Electric Sheep Africa - 经济学 - 指标 - SOM 数据集展示名："索马里联邦共和国——外债" 数据集信息： 划分： - 名称：训练集 样本数：1440 - 名称：测试集 样本数：360 --- # 索马里联邦共和国——外债 **发布方**：世界银行集团 · **数据来源**：[HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/world-bank-external-debt-indicators-for-somalia-fed-rep) · **授权协议**：`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[整合后的国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-somalia-fed-rep)。 外债统计数据可详细展现发展中国家的债务存量与流量情况。季度外债统计（Quarterly External Debt Statistics）板块所呈现的数据，聚焦高收入国家与新兴市场的外债状况，助力更全面地理解全球资金流动。公共部门季度债务数据库则提供了更多关于公共部门估值方法、债务工具，以及中央、州、地方政府及预算外机构与基金的明确债务层级划分相关的数据。本数据集的数据采集自各国统计机构、中央银行，以及各类主要多边机构与世界银行工作人员。 本数据集的每一行均代表国家层面的汇总数据。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：**SOM**。 *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。* --- ## 数据集特征 | | | |---|---| | **领域** | 市场与价格监测 | | **观测单元** | 国家层面汇总数据 | | **总行数** | 1800 | | **列数** | 8（2个数值型，6个分类型，0个日期型） | | **训练集划分** | 1440行 | | **测试集划分** | 360行 | | **地理覆盖范围** | SOM | | **发布方** | 世界银行集团 | | **HDX最后更新时间** | 2026-03-27 | --- ## 变量 **地理类变量** — `country_name`（国家名称：索马里联邦共和国）、`country_iso3`（ISO3国家代码：SOM）、`year`（年份范围：1960.0–2024.0）。 **结果/测量变量** — `value`（数值范围：-350052126.8–12210000000.0）。 **标识符/元数据变量** — `indicator_name`（指标名称：国民总收入（当前美元）、技术合作赠款（国际收支平衡表，当前美元）、人均官方发展援助净流入（当前美元））、`indicator_code`（指标代码：NY.GNP.MKTP.CD、BX.GRT.TECH.CD.WD、DT.ODA.ODAT.PC.ZS）、`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-external-debt-indicators-for-somalia-fed-rep") 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% | 索马里联邦共和国 | | `country_iso3` | 字符型（object） | 0.0% | SOM | | `year` | 64位整型（int64） | 0.0% | 1960.0 – 2024.0（均值：1994.4972） | | `indicator_name` | 字符型（object） | 0.0% | 国民总收入（当前美元）、技术合作赠款（国际收支平衡表，当前美元）、人均官方发展援助净流入（当前美元） | | `indicator_code` | 字符型（object） | 0.0% | NY.GNP.MKTP.CD、BX.GRT.TECH.CD.WD、DT.ODA.ODAT.PC.ZS | | `value` | 64位浮点型（float64） | 0.0% | -350052126.8 – 12210000000.0（均值：347327551.2183） | | `esa_source` | 字符型（object） | 0.0% | HDX | | `esa_processed` | 字符型（object） | 0.0% | 2026-04-09 | --- ## 数值型统计量 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `year` | 1960.0 | 2024.0 | 1994.4972 | 1992.0 | | `value` | -350052126.8 | 12210000000.0 | 347327551.2183 | 1989850.05 | --- ## 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文件存储。 --- ## 数据集局限性 - 本数据集的数据源自世界银行集团，并未经Electric Sheep Africa（ESA）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-external-debt-indicators-for-somalia-fed-rep)。 --- ## 引用格式 bibtex @dataset{hdx_africa_world_bank_external_debt_indicators_for_somalia_fed_rep, title = {索马里联邦共和国——外债}, author = {世界银行集团}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-external-debt-indicators-for-somalia-fed-rep}, note = {由Electric Sheep Africa（https://huggingface.co/electricsheepafrica）重新打包以适配机器学习场景} } --- *[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。*
