electricsheepafrica/africa-ilo-emp-nifl-sex-edu-nb-informal-employment-by-sex-and-education-thousands

该数据集包含非洲45个国家从1999年至2025年的非正规就业数据，按性别和教育程度分类（以千人为单位）。数据集共有8,259个观测值，核心指标为EMP_NIFL_SEX_EDU_NB，表示按性别和教育程度划分的非正规就业人数（千）。数据来源于国际劳工组织（ILO）的ILOSTAT数据库，通过API获取并过滤为非洲国家，遵循国际劳工统计学家会议（ICLS）定义进行标准化处理。数据集结构包括国家代码（ref_area）、来源（source）、指标（indicator）、性别（sex）、教育分类（classif1）、年份（time）、观测值（obs_value）等列，并包含数据质量标志和注释。数据集以表格形式组织，适用于表格分类、回归和时间序列预测任务，支持机器学习应用。数据以CC-BY-4.0许可证发布，由Electric Sheep Africa重新打包，旨在为非洲提供统一的、机器学习就绪的数据层。This dataset contains informal employment data for 45 African countries from 1999 to 2025, disaggregated by sex and education (in thousands). It comprises 8,259 observations, with the core indicator EMP_NIFL_SEX_EDU_NB representing informal employment by sex and education (thousands). The data is sourced from the International Labour Organization (ILO)s ILOSTAT database, retrieved via API and filtered to African country codes, harmonized using International Conference of Labour Statisticians (ICLS) definitions. The schema includes columns such as country code (ref_area), source (source), indicator (indicator), sex (sex), education classification (classif1), year (time), observed value (obs_value), along with data quality flags and notes. Organized in tabular format, it is suitable for tabular classification, regression, and time-series forecasting tasks, supporting machine learning applications. Released under the CC-BY-4.0 license, the dataset is repackaged by Electric Sheep Africa as part of a unified, ML-ready data layer for Africa on HuggingFace.