electricsheepafrica/africa-world-bank-gender-indicators-for-kenya

--- 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 - gender - indicators - ken pretty_name: "Kenya - Gender" dataset_info: splits: - name: train num_examples: 3561 - name: test num_examples: 890 --- # Kenya - Gender **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-gender-indicators-for-kenya) · **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-kenya) on HDX. Gender equality is a core development objective in its own right. It is also smart development policy and sound business practice. It is integral to economic growth, business growth and good development outcomes. Gender equality can boost productivity, enhance prospects for the next generation, build resilience, and make institutions more representative and effective. In December 2015, the World Bank Group Board discussed our new Gender Equality Strategy 2016-2023, which aims to address persistent gaps and proposed a sharpened focus on more and better gender data. The Bank Group is continually scaling up commitments and expanding partnerships to fill significant gaps in gender data. The database hosts the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency. Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **KEN**. *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)** | 4,452 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 3,561 rows | | **Test split** | 890 rows | | **Geographic scope** | KEN | | **Publisher** | World Bank Group | | **HDX last updated** | 2026-03-27 | --- ## Variables **Geographic** — `country_name` (Kenya), `country_iso3` (KEN), `year` (range 1960.0–2025.0). **Outcome / Measurement** — `value` (range 0.0–11711348.0). **Identifier / Metadata** — `indicator_name` (Age population, age 00, male, Age population, age 03, female, Age population, age 04, female), `indicator_code` (SP.POP.AG00.MA.IN, SP.POP.AG03.FE.IN, SP.POP.AG04.FE.IN), `esa_source` (HDX), `esa_processed` (2026-04-09). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-gender-indicators-for-kenya") 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% | Kenya | | `country_iso3` | object | 0.0% | KEN | | `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 2000.3924) | | `indicator_name` | object | 0.0% | Age population, age 00, male, Age population, age 03, female, Age population, age 04, female | | `indicator_code` | object | 0.0% | SP.POP.AG00.MA.IN, SP.POP.AG03.FE.IN, SP.POP.AG04.FE.IN | | `value` | float64 | 0.0% | 0.0 – 11711348.0 (mean 146438.7407) | | `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 | 2000.3924 | 2003.0 | | `value` | 0.0 | 11711348.0 | 146438.7407 | 49.5648 | --- ## 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-gender-indicators-for-kenya) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_gender_indicators_for_kenya, title = {Kenya - Gender}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-gender-indicators-for-kenya}, 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: - 公开采集 language: - 英语（en） license: cc-by-4.0 multilinguality: - 单语言 size_categories: - 1000<n<10000 source_datasets: - 原始数据集 task_categories: - 表格分类 - 表格回归 task_ids: [] tags: - 非洲 - 人道主义 - HDX（Humanitarian Data Exchange） - Electric Sheep Africa - 性别 - 指标 - 肯尼亚（KEN） pretty_name: "肯尼亚——性别指标数据集" dataset_info: splits: - name: train num_examples: 3561 - name: test num_examples: 890 --- # 肯尼亚——性别指标数据集 **发布方**：世界银行集团（World Bank Group） · **来源**：[HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/world-bank-gender-indicators-for-kenya) · **授权协议**：`cc-by` · **最后更新**：2026-03-27 --- ## 摘要 本数据集的数据源自世界银行集团[数据门户](http://data.worldbank.org/)，HDX平台上另有一份[肯尼亚综合国家指标数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-kenya)可供获取。 性别平等本身就是核心发展目标，同时也是明智的发展政策与稳健的商业实践。它与经济增长、商业发展及优质发展成果密不可分。性别平等能够提升生产力、改善下一代的发展前景、增强韧性，并让各类机构更具代表性与实效性。2015年12月，世界银行集团董事会审议通过了《2016-2023年性别平等战略》，该战略旨在解决长期存在的性别数据缺口，并提出进一步聚焦获取更多、更优质的性别数据。世行集团正持续加大投入、拓展合作，以填补性别数据领域的重大缺口。本数据库收录了最新的分性别统计数据与性别指标，涵盖人口统计、教育、健康、经济机会获取、公共生活与决策参与以及个人自主权等多个领域。 本数据集的每一行均代表国家级汇总数据。HDX平台上的本数据集最后更新时间为2026-03-27，地理覆盖范围：**肯尼亚（KEN）**。 *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 | 指标项 | 详情 | |---|---| | **领域** | 公共卫生 | | **观测单元** | 国家级汇总数据 | | **总样本行数** | 4452 | | **列数** | 8列（2列数值型、6列分类型、0列日期时间型） | | **训练集样本数** | 3561行 | | **测试集样本数** | 890行 | | **地理覆盖范围** | 肯尼亚（KEN） | | **发布方** | 世界银行集团（World Bank Group） | | **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：肯尼亚）、`country_iso3`（国家ISO3代码：KEN）、`year`（年份：取值范围1960.0–2025.0）。 ### 结果/测量类变量 `value`（指标数值：取值范围0.0–11711348.0）。 ### 标识/元数据类变量 `indicator_name`（指标名称，示例：00岁男性人口数、03岁女性人口数、04岁女性人口数）、`indicator_code`（指标代码，示例：SP.POP.AG00.MA.IN、SP.POP.AG03.FE.IN、SP.POP.AG04.FE.IN）、`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-gender-indicators-for-kenya") 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` | 字符串型 | 0.0% | 肯尼亚 | | `country_iso3` | 字符串型 | 0.0% | KEN | | `year` | 64位整型 | 0.0% | 1960.0 – 2025.0（均值2000.3924） | | `indicator_name` | 字符串型 | 0.0% | 00岁男性人口数、03岁女性人口数、04岁女性人口数（示例） | | `indicator_code` | 字符串型 | 0.0% | SP.POP.AG00.MA.IN、SP.POP.AG03.FE.IN、SP.POP.AG04.FE.IN（示例） | | `value` | 64位浮点型 | 0.0% | 0.0 – 11711348.0（均值146438.7407） | | `esa_source` | 字符串型 | 0.0% | HDX | | `esa_processed` | 字符串型 | 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 | 2000.3924 | 2003.0 | | `value` | 0.0 | 11711348.0 | 146438.7407 | 49.5648 | --- ## 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。所有列名均转为小写并标准化为蛇形命名法（snake_case）。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，并以Snappy压缩的Parquet格式存储。 --- ## 数据集局限性 - 本数据集源自世界银行集团，未由Electric Sheep Africa（ESA）进行独立验证。 - 自动化清洗流程无法修正原始数据中的错报值、定义不一致问题或采样偏差。 - 如需查看发布方的方法说明与免责条款，请参阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/world-bank-gender-indicators-for-kenya)。 --- ## 引用格式 bibtex @dataset{hdx_africa_world_bank_gender_indicators_for_kenya, title = {Kenya - Gender}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-gender-indicators-for-kenya}, 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。*