electricsheepafrica/africa-world-bank-education-indicators-for-djibouti

--- 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-classification - tabular-regression task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - education - indicators - dji pretty_name: "Djibouti - Education" dataset_info: splits: - name: train num_examples: 9196 - name: test num_examples: 2299 --- # Djibouti - Education **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-education-indicators-for-djibouti) · **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-djibouti) on HDX. Education is one of the most powerful instruments for reducing poverty and inequality and lays a foundation for sustained economic growth. The World Bank compiles data on education inputs, participation, efficiency, and outcomes. Data on education are compiled by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics from official responses to surveys and from reports provided by education authorities in each country. Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **DJI**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Education | | **Unit of observation** | Country-level aggregates | | **Rows (total)** | 11,495 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 9,196 rows | | **Test split** | 2,299 rows | | **Geographic scope** | DJI | | **Publisher** | World Bank Group | | **HDX last updated** | 2026-03-27 | --- ## Variables **Geographic** — `country_name` (Djibouti), `country_iso3` (DJI), `year` (range 1960.0–2025.0). **Outcome / Measurement** — `value` (range 0.0–267610.0). **Identifier / Metadata** — `indicator_name` (Population ages 15-64 (% of total population), Population ages 0-14 (% of total population), Primary school starting age (years)), `indicator_code` (SP.POP.1564.TO.ZS, SP.POP.0014.TO.ZS, SE.PRM.AGES), `esa_source` (HDX), `esa_processed` (2026-04-14). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-education-indicators-for-djibouti") 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% | Djibouti | | `country_iso3` | object | 0.0% | DJI | | `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 2001.1162) | | `indicator_name` | object | 0.0% | Population ages 15-64 (% of total population), Population ages 0-14 (% of total population), Primary school starting age (years) | | `indicator_code` | object | 0.0% | SP.POP.1564.TO.ZS, SP.POP.0014.TO.ZS, SE.PRM.AGES | | `value` | float64 | 0.0% | 0.0 – 267610.0 (mean 22973.3531) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-14 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1960.0 | 2025.0 | 2001.1162 | 2002.0 | | `value` | 0.0 | 267610.0 | 22973.3531 | 7530.0 | --- ## 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-education-indicators-for-djibouti) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_education_indicators_for_djibouti, title = {Djibouti - Education}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-education-indicators-for-djibouti}, 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.*### 数据集元数据 annotations_creators: 无注释 language_creators: 现有资源采集 language: 英语 license: CC BY 4.0 multilinguality: 单语言 size_categories: 10000<n<100000 source_datasets: 原创数据集 task_categories: 表格分类、表格回归 task_ids: 无 tags: 非洲、人道主义、HDX（Humanitarian Data Exchange）、Electric Sheep Africa、教育、指标、DJI（吉布提ISO 3位国家代码） pretty_name: 吉布提 - 教育指标 dataset_info: 训练集样本数9196，测试集样本数2299 # 吉布提 - 教育指标 **发布方**：世界银行集团 · **来源**：[HDX("Humanitarian Data Exchange", HDX)](https://data.humdata.org/dataset/world-bank-education-indicators-for-djibouti) · **许可协议**：`CC BY` · **最后更新时间**：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平台还提供了[吉布提综合国家指标数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-djibouti)。 教育是减贫与缩小不平等最有效的手段之一，同时为可持续经济增长奠定坚实基础。世界银行汇总了教育投入、教育参与度、办学效率与教育产出相关数据。教育领域的统计数据由联合国教育、科学及文化组织（United Nations Educational, Scientific and Cultural Organization, UNESCO）统计研究所通过各国官方调研反馈及各国教育主管部门提交的官方报告进行汇编。 本数据集每一行代表国家层面的汇总统计结果。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：**DJI（吉布提）**。 *本数据集已由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为机器学习可用的Parquet列式存储格式。* ## 数据集特征 | 指标项 | 详情 | |---|---| | **研究领域** | 教育 | | **观测单元** | 国家层面汇总数据 | | **总数据行数** | 11495 | | **列数** | 8列（2个数值型列、6个分类型列、0个日期时间型列） | | **训练集划分** | 9196行 | | **测试集划分** | 2299行 | | **地理覆盖范围** | DJI（吉布提） | | **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：吉布提）、`country_iso3`（国家ISO 3位代码：DJI）、`year`（年份：取值范围1960.0–2025.0）。 **产出/测量类变量** — `value`（指标数值：取值范围0.0–267610.0）。 **标识符/元数据类变量** — `indicator_name`（指标名称：15-64岁人口占总人口比例、0-14岁人口占总人口比例、小学入学年龄（岁））、`indicator_code`（指标代码：SP.POP.1564.TO.ZS、SP.POP.0014.TO.ZS、SE.PRM.AGES）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-14）。 ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-education-indicators-for-djibouti") 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% | 吉布提 | | `country_iso3` | 字符串（object） | 0.0% | DJI | | `year` | 64位整型（int64） | 0.0% | 1960.0 – 2025.0（均值2001.1162） | | `indicator_name` | 字符串（object） | 0.0% | 15-64岁人口占总人口比例、0-14岁人口占总人口比例、小学入学年龄（岁） | | `indicator_code` | 字符串（object） | 0.0% | SP.POP.1564.TO.ZS、SP.POP.0014.TO.ZS、SE.PRM.AGES | | `value` | 64位浮点型（float64） | 0.0% | 0.0 – 267610.0（均值22973.3531） | | `esa_source` | 字符串（object） | 0.0% | HDX | | `esa_processed` | 字符串（object） | 0.0% | 2026-04-14 | ## 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 | 2001.1162 | 2002.0 | | `value` | 0.0 | 267610.0 | 22973.3531 | 7530.0 | ## 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列式存储格式。列名统一转换为小写并标准化为蛇形命名法（snake_case）。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。采用固定随机种子（42）将数据集按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 - 本数据集原始数据来自世界银行集团，Electric Sheep Africa未对其进行独立验证。 - 自动化清洗流程无法修正原始数据收集阶段存在的错报值、定义不一致或抽样偏差问题。 - 如需查看发布方提供的官方方法论说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-education-indicators-for-djibouti)。 ## 引用格式 bibtex @dataset{hdx_africa_world_bank_education_indicators_for_djibouti, title = {Djibouti - Education}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-education-indicators-for-djibouti}, 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。*