electricsheepafrica/africa-world-bank-social-development-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: - n<1K source_datasets: - original task_categories: - tabular-classification task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - development - indicators - som pretty_name: "Somalia, Fed. Rep. - Social Development" dataset_info: splits: - name: train num_examples: 617 - name: test num_examples: 154 --- # Somalia, Fed. Rep. - Social Development **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-social-development-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. Data here cover child labor, gender issues, refugees, and asylum seekers. Children in many countries work long hours, often combining studying with work for pay. The data on their paid work are from household surveys conducted by the International Labour Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. Gender disparities are measured using a compilation of data on key topics such as education, health, labor force participation, and political participation. Data on refugees are from the United Nations High Commissioner for Refugees complemented by statistics on Palestinian refugees under the mandate of the United Nations Relief and Works Agency. 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** | Public health | | **Unit of observation** | Country-level aggregates | | **Rows (total)** | 772 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 617 rows | | **Test split** | 154 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 1960.0–2025.0). **Outcome / Measurement** — `value` (range 0.1–138.52). **Identifier / Metadata** — `indicator_name` (Life expectancy at birth, male (years), Life expectancy at birth, female (years), Adolescent fertility rate (births per 1,000 women ages 15-19)), `indicator_code` (SP.DYN.LE00.MA.IN, SP.DYN.LE00.FE.IN, SP.ADO.TFRT), `esa_source` (HDX), `esa_processed` (2026-04-09). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-social-development-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 – 2025.0 (mean 2001.9184) | | `indicator_name` | object | 0.0% | Life expectancy at birth, male (years), Life expectancy at birth, female (years), Adolescent fertility rate (births per 1,000 women ages 15-19) | | `indicator_code` | object | 0.0% | SP.DYN.LE00.MA.IN, SP.DYN.LE00.FE.IN, SP.ADO.TFRT | | `value` | float64 | 0.0% | 0.1 – 138.52 (mean 35.1805) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-09 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1960.0 | 2025.0 | 2001.9184 | 2004.0 | | `value` | 0.1 | 138.52 | 35.1805 | 24.654 | --- ## 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-social-development-indicators-for-somalia-fed-rep) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_social_development_indicators_for_somalia_fed_rep, title = {Somalia, Fed. Rep. - Social Development}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-social-development-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.*
annotations_creators: - 无注释 language_creators: - 资源获取型 language: - en license: cc-by-4.0 multilinguality: - 单语言 size_categories: - n<1K source_datasets: - 原始数据集 task_categories: - 表格分类 task_ids: [] tags: - 非洲 - 人道主义 - HDX - electric-sheep-africa - 发展 - 指标 - som pretty_name: "索马里联邦共和国——社会发展" dataset_info: splits: - name: train num_examples: 617 - name: test num_examples: 154 # 索马里联邦共和国——社会发展 **发布方**：世界银行集团 · **数据来源**：[人道主义数据交换平台（HDX）](https://data.humdata.org/dataset/world-bank-social-development-indicators-for-somalia-fed-rep) · **许可证**：`cc-by` · **最后更新时间**：2026-03-27 --- ## 摘要 本数据集数据源自世界银行[官方数据门户](http://data.worldbank.org/)。HDX平台上另有一份[索马里联邦共和国综合国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-somalia-fed-rep)。 本数据集涵盖童工、性别平等、难民及寻求庇护者相关数据。全球多国儿童长期参与有偿劳动，常需兼顾学业与工作。相关有偿劳动数据源自国际劳工组织（International Labour Organization, ILO）、联合国儿童基金会（United Nations Children's Fund, UNICEF）、世界银行及各国统计机构开展的住户调查。性别差距通过教育、健康、劳动力参与率及政治参与等核心议题的整合数据进行衡量。难民相关数据源自联合国难民署（United Nations High Commissioner for Refugees），并辅以联合国近东巴勒斯坦难民救济和工程处职责范围内的巴勒斯坦难民统计数据。 本数据集每行数据均为国家层面的汇总统计值。数据最后于2026-03-27在HDX平台更新。地理覆盖范围：**SOM**。 *本数据集已由[非洲电羊团队（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)整理为可供机器学习使用的Parquet格式。* --- ## 数据集特征 | | | |---|---| | **领域** | 公共卫生 | | **观测单元** | 国家层面汇总数据 | | **总样本行数** | 772 | | **列数** | 8（2个数值型，6个分类型，0个日期时间型） | | **训练集样本数** | 617 | | **测试集样本数** | 154 | | **地理覆盖范围** | SOM | | **发布方** | 世界银行集团 | | **HDX平台最后更新时间** | 2026-03-27 | --- ## 变量 **地理类变量** — `country_name`（索马里联邦共和国）、`country_iso3`（SOM）、`year`（取值范围1960.0–2025.0）。 **结果/测量类变量** — `value`（取值范围0.1–138.52）。 **标识符/元数据类变量** — `indicator_name`（出生时预期寿命，男性（年）、出生时预期寿命，女性（年）、青少年生育率（每1000名15-19岁女性的活产数））、`indicator_code`（SP.DYN.LE00.MA.IN、SP.DYN.LE00.FE.IN、SP.ADO.TFRT）、`esa_source`（HDX）、`esa_processed`（2026-04-09）。 --- ## 快速入门 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-social-development-indicators-for-somalia-fed-rep") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) 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` | 对象型 | 0.0% | 索马里联邦共和国 | | `country_iso3` | 对象型 | 0.0% | SOM | | `year` | 64位整数型 | 0.0% | 1960.0 – 2025.0（均值2001.9184） | | `indicator_name` | 对象型 | 0.0% | 出生时预期寿命，男性（年）、出生时预期寿命，女性（年）、青少年生育率（每1000名15-19岁女性的活产数） | | `indicator_code` | 对象型 | 0.0% | SP.DYN.LE00.MA.IN、SP.DYN.LE00.FE.IN、SP.ADO.TFRT | | `value` | 64位浮点型 | 0.0% | 0.1 – 138.52（均值35.1805） | | `esa_source` | 对象型 | 0.0% | HDX | | `esa_processed` | 对象型 | 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 | 2025.0 | 2001.9184 | 2004.0 | | `value` | 0.1 | 138.52 | 35.1805 | 24.654 | --- ## 数据整理说明 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。将常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。本数据集以固定随机种子（42）按80/20比例划分为训练集与测试集，并保存为Snappy压缩的Parquet格式。 --- ## 数据集局限性 - 数据源自世界银行集团，未经过非洲电羊团队的独立验证。 - 自动化清洗无法修正原始数据收集过程中存在的错报、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注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-social-development-indicators-for-somalia-fed-rep)。 --- ## 引用格式 bibtex @dataset{hdx_africa_world_bank_social_development_indicators_for_somalia_fed_rep, title = {Somalia, Fed. Rep. - Social Development}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-social-development-indicators-for-somalia-fed-rep}, note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)} } --- *[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，尼日利亚拉各斯。*
