electricsheepafrica/africa-ilo-emp-temp-sex-skn-ifl-nb-employment-by-sex-educational-mismatch-normative-a

该数据集名为“按性别、教育不匹配——规范方法和工作性质（非正式/正式）划分的就业情况 | 非洲（ILOSTAT）”，包含7,405个观测值，覆盖42个非洲国家，时间跨度为2001年至2025年。数据集专注于技能不匹配主题，主要指标为“EMP_TEMP_SEX_SKN_IFL_NB”，表示按性别、教育不匹配（规范方法）和工作性质（非正式/正式）划分的就业人数（以千计）。数据来源于国际劳工组织（ILO）的ILOSTAT数据库，通过REST API获取并过滤非洲国家代码。数据集包括列如国家代码、国家名称、数据来源、指标代码、性别分类、分类变量、观测年份、观测值、观测状态和相关注释。数据以年度频率发布，提供性别维度的细分（总计、男性、女性），并包含数据质量注意事项，如使用ILO选择的“最佳来源”和处理缺失值。该数据集由Electric Sheep Africa重新打包，旨在为非洲提供统一的、适合机器学习的数据库层，便于研究人员和开发者使用。This dataset, titled Employment by sex, educational mismatch - normative approach and nature of job (informal / | Africa (ILOSTAT), contains 7,405 observations across 42 African countries, spanning the years 2001 to 2025. It focuses on the topic of skills mismatch, with the primary indicator being EMP_TEMP_SEX_SKN_IFL_NB, which measures employment by sex, educational mismatch using a normative approach, and the nature of job (informal/formal) in thousands. The data is sourced from the International Labour Organizations (ILO) ILOSTAT database, retrieved via the REST API and filtered for African country codes. The dataset includes columns such as country code, country name, data source, indicator code, sex disaggregation, classification variables, observation year, observed value, observation status, and related notes. Data is published at an annual frequency, with disaggregation by sex (total, male, female), and includes caveats on data quality, such as the use of ILO-selected best sources and handling of missing values. Repackaged by Electric Sheep Africa, this dataset is part of a mission to provide a unified, ML-ready data layer for Africa, facilitating easy access for researchers and developers.