electricsheepafrica/africa-ilo-ees-tees-sex-mjh-nb-employees-by-sex-and-multiple-job-holding-thousand

该数据集包含来自国际劳工组织（ILO）ILOSTAT数据库的雇员统计数据，专门针对非洲地区。它涵盖了47个非洲国家从1991年至2025年的2,169个观测值，核心指标为按性别和多重职业持有情况统计的雇员数量（以千计）（指标代码：EES_TEES_SEX_MJH_NB）。数据通过ILOSTAT REST API获取，并经过标准化处理，以确保符合国际劳工统计学家会议（ICLS）的定义。数据集包含多个列，如国家代码、国家名称、数据来源、指标代码、性别分类、时间年份、观测值等，支持按性别（总计、男性、女性）和多重职业持有情况进行细分。数据为年度频率，适用于表格分类、回归分析和时间序列预测等机器学习任务。数据集由Electric Sheep Africa重新打包，以提供统一的、适用于机器学习的数据格式。This dataset contains employee statistics sourced from the International Labour Organization (ILO) ILOSTAT database, specifically targeting the African region. It covers 2,169 observations from 47 African countries spanning the period from 1991 to 2025. The core indicator is the number of employees (in thousands) categorized by sex and multiple jobholding status, with the indicator code: EES_TEES_SEX_MJH_NB. The data was obtained via the ILOSTAT REST API and standardized to align with the definitions set by the International Conference of Labour Statisticians (ICLS). The dataset includes multiple columns such as country code, country name, data source, indicator code, sex classification, calendar year, and observed values, supporting disaggregation by sex (total, male, female) and multiple jobholding status. With annual frequency, the dataset is applicable to machine learning tasks including tabular classification, regression analysis and time series forecasting. This dataset was repackaged by Electric Sheep Africa to provide a unified, machine learning-ready data format.