electricsheepafrica/africa-unesco-data-for-united-republic-of-tanzania
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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-classification - tabular-regression task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - demographics - education - indicators - socioeconomics - sustainable-development - sustainable-development-goals-sdg - tza pretty_name: "United Republic of Tanzania - Education Indicators" dataset_info: splits: - name: train num_examples: 5420 - name: test num_examples: 1355 --- # United Republic of Tanzania - Education Indicators **Publisher:** UNESCO · **Source:** [HDX](https://data.humdata.org/dataset/unesco-data-for-united-republic-of-tanzania) · **License:** `cc-by-igo` · **Updated:** 2026-03-03 --- ## Abstract Education indicators for United Republic of Tanzania. Contains data from the UNESCO Institute for Statistics [bulk data service](http://data.uis.unesco.org) covering the following categories: SDG 4 Global and Thematic (made 2026 February), Other Policy Relevant Indicators (made 2026 February), Demographic and Socio-economic (made 2026 February) Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-03. Geographic scope: **TZA**. *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)** | 6,775 | | **Columns** | 6 (2 numeric, 4 categorical, 0 datetime) | | **Train split** | 5,420 rows | | **Test split** | 1,355 rows | | **Geographic scope** | TZA | | **Publisher** | UNESCO | | **HDX last updated** | 2026-03-03 | --- ## Variables **Geographic** — `country_id` (TZA), `year` (range 1970.0–2025.0). **Outcome / Measurement** — `value` (range 0.0–8459309.0). **Identifier / Metadata** — `indicator_id` (GER.5T8, CR.MOD.1.F, CR.MOD.1), `esa_source` (HDX), `esa_processed` (2026-04-05). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-unesco-data-for-united-republic-of-tanzania") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `indicator_id` | object | 0.0% | GER.5T8, CR.MOD.1.F, CR.MOD.1 | | `country_id` | object | 0.0% | TZA | | `year` | int64 | 0.0% | 1970.0 – 2025.0 (mean 2011.2683) | | `value` | float64 | 0.0% | 0.0 – 8459309.0 (mean 15577.8713) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-05 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1970.0 | 2025.0 | 2011.2683 | 2012.0 | | `value` | 0.0 | 8459309.0 | 15577.8713 | 8.17 | --- ## 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`. 2 column(s) with >80% missing values were removed: `magnitude`, `qualifier`. 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 UNESCO 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/unesco-data-for-united-republic-of-tanzania) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_unesco_data_for_united_republic_of_tanzania, title = {United Republic of Tanzania - Education Indicators}, author = {UNESCO}, year = {2026}, url = {https://data.humdata.org/dataset/unesco-data-for-united-republic-of-tanzania}, 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 语言创建方式: - 公开资源获取 语言: - 英语 许可证: - 知识共享署名4.0国际许可协议（CC BY 4.0） 多语言属性: - 单语言 数据规模类别: - 1000 < 样本数 < 10000 源数据集: - 原始数据集 任务类别: - 表格分类 - 表格回归 任务子类别: - 无 标签: - 非洲 - 人道主义 - HDX - Electric Sheep Africa - 人口统计 - 教育 - 指标 - 社会经济 - 可持续发展 - 可持续发展目标（SDG） - TZA 展示名称: "坦桑尼亚联合共和国——教育指标数据集" 数据集信息: 划分方式: - 名称: 训练集（train） 样本数: 5420 - 名称: 测试集（test） 样本数: 1355 --- # 坦桑尼亚联合共和国——教育指标数据集 **发布方：** 联合国教科文组织（UNESCO） · **来源：** [人道主义数据交换（Humanitarian Data Exchange，HDX）](https://data.humdata.org/dataset/unesco-data-for-united-republic-of-tanzania) · **许可证：** `cc-by-igo` · **最后更新：** 2026-03-03 --- ## 摘要 本数据集收录坦桑尼亚联合共和国的教育指标数据。数据源自联合国教科文组织统计研究所（UNESCO Institute for Statistics）的[批量数据服务](http://data.uis.unesco.org)，涵盖以下类别：2026年2月生成的可持续发展目标4（SDG 4）全球与专题指标、2026年2月生成的其他政策相关指标、2026年2月生成的人口与社会经济指标。 本数据集的每一行均代表国家级汇总数据。数据最后于2026-03-03在HDX平台更新。地理覆盖范围：**TZA（坦桑尼亚联合共和国ISO 3166-1代码）**。 *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 | | | |---|---| | **领域** | 教育 | | **观测单元** | 国家级汇总数据 | | **总数据行数** | 6775 | | **列数** | 6（2个数值型、4个分类型、0个日期时间型） | | **训练集样本数** | 5420 | | **测试集样本数** | 1355 | | **地理覆盖范围** | TZA | | **发布方** | 联合国教科文组织 | | **HDX平台最后更新时间** | 2026-03-03 | --- ## 变量说明 **地理变量** — `country_id`（取值为TZA）、`year`（取值范围1970.0–2025.0）。 **结果/测量变量** — `value`（取值范围0.0–8459309.0）。 **标识符/元数据变量** — `indicator_id`（示例值：GER.5T8、CR.MOD.1.F、CR.MOD.1）、`esa_source`（取值为HDX）、`esa_processed`（取值为2026-04-05）。 --- ## 快速上手示例 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-unesco-data-for-united-republic-of-tanzania") 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 | |---|---|---|---| | `indicator_id` | 字符串（object） | 0.0% | GER.5T8、CR.MOD.1.F、CR.MOD.1 | | `country_id` | 字符串（object） | 0.0% | TZA | | `year` | 64位整型（int64） | 0.0% | 1970.0 – 2025.0（均值2011.2683） | | `value` | 64位浮点型（float64） | 0.0% | 0.0 – 8459309.0（均值15577.8713） | | `esa_source` | 字符串（object） | 0.0% | HDX | | `esa_processed` | 字符串（object） | 0.0% | 2026-04-05 | --- ## 数值型变量统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `year` | 1970.0 | 2025.0 | 2011.2683 | 2012.0 | | `value` | 0.0 | 8459309.0 | 15577.8713 | 8.17 | --- ## 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。列名统一转换为小写并采用蛇形命名法（snake_case）进行标准化。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。移除了2个缺失值占比超过80%的列：`magnitude`与`qualifier`。本数据集使用固定随机种子（42）按照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 - 本数据源自联合国教科文组织，未由Electric Sheep Africa进行独立验证。 - 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[原始HDX数据集页面](https://data.humdata.org/dataset/unesco-data-for-united-republic-of-tanzania)。 --- ## 引用格式 bibtex @dataset{hdx_africa_unesco_data_for_united_republic_of_tanzania, title = {United Republic of Tanzania - Education Indicators}, author = {UNESCO}, year = {2026}, url = {https://data.humdata.org/dataset/unesco-data-for-united-republic-of-tanzania}, 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，尼日利亚拉各斯。*
