electricsheepeurope/europe-ilo-une-deap-sex-mts-rt-unemployment-rate-by-sex-and-marital-status

--- license: cc-by-4.0 language: - en task_categories: - tabular-classification - tabular-regression - time-series-forecasting multilinguality: monolingual size_categories: - 10K<n<100K tags: - tabular - europe - ilostat - unemployment - ilo - labour - employment pretty_name: "Unemployment rate by sex and marital status (%) | Europe (ILOSTAT)" --- # Unemployment rate by sex and marital status (%) | Europe (ILOSTAT) 🇪🇺 **14,179 observations** · **39 Europe countries** · **1983–2025** · *Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)*      ## TL;DR This dataset contains **14,179 observations** of `Unemployment` data across **39 Europe countries**, spanning **1983–2025**, covering **1 distinct indicators**. ## About the source **ILOSTAT** is the ILO's central statistics database, the 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. Coverage spans 200+ economies, with the ILO's Department of Statistics responsible for harmonisation. - **Source:** [ILOSTAT](https://www.ilo.org/shinyapps/bulkexplorer/?id=UNE_DEAP_SEX_MTS_RT) - **Publisher:** International Labour Organization (ILO) - **License:** [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/) - **Topic:** Unemployment ## Methodology Data pulled directly from the ILOSTAT REST API at `https://rplumber.ilo.org/data/indicator?id=UNE_DEAP_SEX_MTS_RT` and filtered to Europe ISO3 country codes. ILOSTAT harmonises raw survey microdata using ICLS (International Conference of Labour Statisticians) definitions; sources are flagged in the `source.label` column for traceability. ## Geographic coverage 39 Europe countries · top rows shown below, sorted by row count: | Country | Rows | First year | Last year | |---------|-----:|-----------:|----------:| | `CHE` | 948 | 1991 | 2025 | | `CZE` | 765 | 1993 | 2024 | | `GBR` | 749 | 1983 | 2025 | | `MDA` | 652 | 2000 | 2025 | | `POL` | 651 | 1997 | 2025 | | `AUT` | 607 | 1995 | 2025 | | `MKD` | 565 | 2005 | 2025 | | `FRA` | 524 | 2005 | 2024 | | `ALB` | 472 | 2002 | 2024 | | `BIH` | 465 | 2001 | 2020 | | `ESP` | 435 | 1986 | 2025 | | `RUS` | 432 | 2010 | 2025 | | `IRL` | 417 | 1983 | 2023 | | `ITA` | 378 | 1983 | 2024 | | `LUX` | 343 | 1983 | 2020 | | ... | _24 more countries_ | | | ## Indicators (sample) - `UNE_DEAP_SEX_MTS_RT` — Unemployment rate by sex and marital status (%) ## Schema | Column | Type | Description | Example | |--------|------|-------------|---------| | `ref_area` | `string` | ISO 3166-1 alpha-3 country code | `ALB` | | `ref_area.label` | `string` | Country name in English | `Albania` | | `source` | `string` | ILOSTAT source code (e.g. labour force survey) | `BA:480` | | `source.label` | `string` | Source name in English | `LFS - Labour Force Survey` | | `indicator` | `string` | ILOSTAT indicator code | `UNE_DEAP_SEX_MTS_RT` | | `indicator.label` | `string` | Indicator name in English | `Unemployment rate by sex and marital …` | | `sex` | `string` | Disaggregation by sex (SEX_T = total, SEX_M = male, SEX_F = female) | `SEX_T` | | `sex.label` | `string` | — | `Total` | | `classif1` | `string` | First classification variable (age, education, status, etc.) | `MTS_AGGREGATE_TOTAL` | | `classif1.label` | `string` | — | `Marital status (Aggregate): Total` | | `time` | `int64` | Observation year | `2024` | | `obs_value` | `float64` | Observed indicator value (unit varies — see indicator definition) | `8.431` | | `obs_status` | `string` | Observation status flag (e.g. provisional, unreliable) | `U` | | `obs_status.label` | `string` | — | `Unreliable` | | `note_indicator` | `string` | — | `I11:264` | | `note_indicator.label` | `string` | — | `Break in series: Methodology revised` | | `note_source` | `string` | — | `R1:3513` | | `note_source.label` | `string` | — | `Repository: ILO-STATISTICS - Micro da…` | ## Disaggregation dimensions The following columns provide disaggregation dimensions: - **`sex`** (3 unique values): `SEX_T`, `SEX_M`, `SEX_F` ## Data quality & caveats - Data is annual frequency. Some indicators also publish monthly or quarterly series — those are not included here. - When an indicator has multiple sources for the same country×year, the ILO-selected 'best source' is used. - Disaggregation columns (`sex`, `classif1`, `classif2`) are non-null only when the indicator publishes that breakdown. ## Usage ```python from datasets import load_dataset ds = load_dataset("electricsheepeurope/europe-ilo-une-deap-sex-mts-rt-unemployment-rate-by-sex-and-marital-status") df = ds["train"].to_pandas() print(df.head()) ``` ### Filter to one country ```python germany = df[df["ref_area"] == "DEU"] ``` ### Time-series for a single indicator ```python sample = (df[df["indicator"] == "UNE_DEAP_SEX_MTS_RT"] .sort_values("time")) sample.plot(x="time", y="obs_value", title="UNE_DEAP_SEX_MTS_RT") ``` ### Pivot to country × year matrix ```python matrix = (df[df["indicator"] == "UNE_DEAP_SEX_MTS_RT"] .pivot_table(index="time", columns="ref_area", values="obs_value")) print(matrix.tail()) ``` ## Citation ```bibtex @misc{europe_ilo_une_deap_sex_mts_rt_unemployment_rate_by_sex_and_marital_status_2025, title = {Unemployment rate by sex and marital status (%) | Europe (ILOSTAT)}, author = {International Labour Organization (ILO)}, year = {2025}, url = {https://www.ilo.org/shinyapps/bulkexplorer/?id=UNE_DEAP_SEX_MTS_RT}, publisher = {HuggingFace Datasets, repackaged by Electric Sheep Europe}, howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-ilo-une-deap-sex-mts-rt-unemployment-rate-by-sex-and-marital-status}} } ``` ## License Released under [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/). Original data © International Labour Organization (ILO). When using this dataset, please cite both the original source above and the Electric Sheep Europe repackaging. ## About Electric Sheep Electric Sheep Europe is part of the Electric Sheep mission: a unified, ML-ready data layer for Europe on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use `load_dataset()` to start working in seconds. Browse the full collection: [huggingface.co/electricsheepeurope](https://huggingface.co/electricsheepeurope) --- _Provenance: ingested 2026-05-27 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=UNE_DEAP_SEX_MTS_RT_This dataset contains unemployment rate statistics for Europe from the International Labour Organization (ILO) ILOSTAT database, specifically the indicator for unemployment rate by sex and marital status (%). It covers 39 European countries from 1983 to 2025, with 14,179 observations. Repackaged by Electric Sheep Europe, the data is provided in tabular format, including columns for country codes, year, sex disaggregation, marital status classification, observed values, and data sources, suitable for tasks such as tabular classification, regression, and time-series forecasting. Data is published at annual frequency and includes quality annotations such as observation status flags and series break notes.

搜集汇总

数据集介绍

构建方式

该数据集源自国际劳工组织（ILO）下属ILOSTAT数据库，通过其REST API直接提取劳动力统计指标，原始数据基于国家劳动力调查、家庭收入调查等官方来源，并依据国际劳工统计学家会议定义进行统一整合。构建过程中，数据被筛选至39个欧洲国家的地理范围，涵盖了自1983年至2025年间的年度观测值。为确保数据的可靠性与可追溯性，每条记录均保留了来源代码与标签，同时剔除了同一国家与年份中非最优来源的重复数据，最终形成包含14,179条记录的规范化时间序列表格。

特点

该数据集的核心特点在于其围绕性别与婚姻状况两个维度对失业率进行了精细的分解，提供了总人口、男性和女性三个性别分组下的失业率百分比数值。数据汇集了39个欧洲国家的长期年度时序，时间跨度超过四十年，为跨国的纵向比较研究提供了丰富的素材。此外，数据集附带了详尽的元数据，包括数据来源、观测状态标志以及可能的序列中断注释，有助于用户评估数据质量与潜在偏差，体现了高度的透明性与学术严谨性。

使用方法

用户可通过HuggingFace的`datasets`库轻松加载该数据集，以一行代码`load_dataset`即可获取并转换为Pandas DataFrame，便于后续分析。针对特定需求，数据集支持按国家代码进行筛选，例如选取德国（DEU）的条目进行单独研究。在时间序列分析场景中，用户可按指示变量排序并绘制`obs_value`随时间变化的曲线。同时，该表格结构支持通过数据透视操作，将数据重塑为国家与年份的矩阵形式，便于进行面板数据分析或构建机器学习模型的特征矩阵。

背景与挑战

背景概述

该数据集由国际劳工组织（ILO）旗下ILOSTAT数据库整理，并由Electric Sheep Europe于2025年重新打包发布，聚焦欧洲39个国家1983至2025年间按性别和婚姻状况划分的失业率数据。作为全球劳动统计的核心权威来源，ILOSTAT基于各国劳动力调查等官方数据，遵循国际劳工统计学家会议（ICLS）定义进行标准化处理。该数据集提供了14,179条年度观测记录，覆盖单一指标（UNE_DEAP_SEX_MTS_RT），并包含性别、婚姻状况等细分维度，为研究欧洲劳动力市场中性别与婚姻状态对失业影响的动态演变提供了宝贵的时间序列资料，对劳动经济学、社会政策分析及跨国比较研究具有重要支撑作用。

当前挑战

该数据集所解决的领域问题在于欧洲劳动力市场中，按性别和婚姻状况划分的失业率精确测量与跨时空可比性分析。传统上，各国统计口径与调查方法的差异导致数据碎片化，难以进行跨国趋势比较。构建过程中，ILOSTAT面临多重挑战：需从200多个经济体不同的劳动调查（如劳动力调查、家计调查）中提取并统一指标定义，确保符合ICLS标准；处理因方法论修订（如数据中断标记‘Break in series’）导致的序列不一致性；甄别多来源数据中由ILO选定的‘最佳来源’，以保证同一国家年份的单一性；同时须妥善标注观测状态（如不可靠标志‘U’）和来源注解，以实现数据质量的可追溯性。

常用场景

经典使用场景

该数据集收录了1983至2025年间39个欧洲国家按性别与婚姻状况分列的失业率数据，共计14179条观测记录，是劳动经济学与跨国家比较研究中不可多得的高质量面板数据。研究者常利用其时间跨度长、地理覆盖广、细粒度拆分维度丰富的特性，构建国家-年度-性别-婚姻状况的全维数据结构，进而运用面板回归、固定效应模型或分层贝叶斯框架，剖析失业率在性别和婚姻群体间的动态差异，并探究经济周期、政策干预或社会结构变迁对特定亚群的异质性冲击。数据集提供了经ILO标准化的统一指标定义，有效缓解了跨国比较中常见的测算口径不一致问题，使其成为宏观劳动市场建模与性别不平等研究的经典资源。

实际应用

在实际应用领域，该数据集为国际组织、政府统计部门及智库机构开展劳动力市场监测与政策评估提供了坚实的数据底座。各国劳动与社会保障部门可借助该数据定期追踪本国不同性别和婚姻状况群体的失业率演变趋势，精准识别就业脆弱性显著上升的目标人群，并据此调整职业培训资源配置、定向就业援助计划或育儿与照护支持政策。欧盟委员会等超国家机构在制定《欧洲就业战略》与《性别平等战略》过程中，常将此数据集作为跨国基准比对的核心依据，以检验成员国在缩小就业性别差距和改善单亲家庭劳动参与方面的政策实效。此外，研究机构在构建早期预警系统和就业景气指数时，亦广泛采用该数据作为输入变量，提升宏观决策的前瞻性和针对性。

衍生相关工作

该数据集所衍生的经典工作主要沿着两条清晰的技术路径展开。其一，在时序预测领域，研究者基于该面板数据训练了一系列面向区域-亚群维度的失业率预测模型，包括季节性差分自回归移动平均模型（SARIMA）与长短期记忆网络（LSTM），以及将国家与婚姻性别组合视为分层结构的分层时间序列预测方法（HTS），显著提升了短期失业态势的推演精度。其二，在因果推断与政策评估方向上，学者们利用该数据的长期跨度和细粒度拆解，构建了合成控制法（SCM）和双重差分（DID）框架，系统评估了2008年全球金融危机、欧债危机与新冠疫情爆发对欧洲各国不同性别婚姻群体的非对称失业冲击。这些衍生工作不仅丰富了劳动经济学的方法论工具箱，也为后续研究提供了可复现的基准实验与比较框架。