electricsheepasia/asia-ilo-pop-xwap-sex-edu-mts-nb-working-age-population-by-sex-education-and-marita

该数据集名为按性别、教育程度和婚姻状况划分的劳动年龄人口（千）| 亚洲（ILOSTAT），包含124,605个观测值，覆盖亚洲34个国家从1970年至2025年的数据。数据集的核心指标是POP_XWAP_SEX_EDU_MTS_NB，即按性别、教育程度和婚姻状况划分的劳动年龄人口（以千计）。数据来源于国际劳工组织（ILO）的ILOSTAT数据库，这是一个全球领先的劳动统计数据源，通过整合国家劳动力调查、家庭收入调查、企业调查和行政记录等数据，提供就业、失业、工资、工作时间、童工、非正规经济、社会保障、职业伤害和可持续发展目标体面工作指标等信息。数据集经过ILO的统计部门统一处理，确保定义的一致性（基于国际劳工统计学家会议定义）。数据以表格形式组织，包含列如国家代码（ref_area）、国家名称（ref_area.label）、指标代码（indicator）、指标名称（indicator.label）、性别（sex）、教育分类（classif1）、婚姻状况分类（classif2）、年份（time）、观测值（obs_value）等，并包含数据来源和质量标志（如obs_status表示观测状态）。数据集主要用于表格分类、回归和时间序列预测等任务，支持对亚洲劳动年龄人口结构的分析和建模。数据由Electric Sheep Asia重新打包，以Parquet格式发布，便于机器学习使用。This dataset is titled Working-age population by sex, education and marital status (thousands) | Asia (ILOSTAT) and contains 124,605 observations covering 34 Asian countries from 1970 to 2025. The core indicator is POP_XWAP_SEX_EDU_MTS_NB, which represents the working-age population disaggregated by sex, education, and marital status (in thousands). The data is sourced from ILOSTAT, the International Labour Organizations (ILO) central statistics database, a leading global source for labour statistics. It compiles indicators across employment, unemployment, wages, working time, child labour, informal economy, social protection, occupational injuries, and SDG decent work targets, drawing on national labour force surveys, household income surveys, establishment surveys, and administrative records. The data is harmonized by the ILOs Department of Statistics using International Conference of Labour Statisticians (ICLS) definitions. The dataset is structured in tabular format with columns such as country code (ref_area), country name (ref_area.label), indicator code (indicator), indicator name (indicator.label), sex (sex), education classification (classif1), marital status classification (classif2), year (time), observed value (obs_value), and includes source and quality flags (e.g., obs_status for observation status). It is intended for tasks like tabular classification, regression, and time-series forecasting, supporting analysis and modeling of working-age population structures in Asia. The data is repackaged by Electric Sheep Asia in Parquet format for machine learning readiness.