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electricsheepafrica/africa-ilo-sdg-0821-noc-rt-sdg-indicator-8-2-1-annual-growth-rate-of-output-p

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Hugging Face2026-05-26 更新2026-05-31 收录
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--- license: cc-by-4.0 language: - en task_categories: - tabular-classification - tabular-regression - time-series-forecasting multilinguality: monolingual size_categories: - 1K<n<10K tags: - tabular - africa - ilostat - labour-productivity - ilo - labour - employment pretty_name: "SDG indicator 8.2.1 - Annual growth rate of output per worker (GDP constant 2015 US $) (%) | Africa (ILOSTAT)" --- # SDG indicator 8.2.1 - Annual growth rate of output per worker (GDP constant 2015 US $) (%) | Africa (ILOSTAT) 🌍 **1,475 observations** · **53 Africa countries** · **2000–2027** · *Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)* ![rows](https://img.shields.io/badge/rows-1,475-blue) ![countries](https://img.shields.io/badge/countries-53-green) ![years](https://img.shields.io/badge/years-2000–2027-orange) ![indicators](https://img.shields.io/badge/indicators-1-purple) ![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey) ## TL;DR This dataset contains **1,475 observations** of `Labour productivity` data across **53 Africa countries**, spanning **2000–2027**, 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=SDG_0821_NOC_RT) - **Publisher:** International Labour Organization (ILO) - **License:** [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/) - **Topic:** Labour productivity ## Methodology Data pulled directly from the ILOSTAT REST API at `https://rplumber.ilo.org/data/indicator?id=SDG_0821_NOC_RT` and filtered to Africa 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 53 Africa countries · top rows shown below, sorted by row count: | Country | Rows | First year | Last year | |---------|-----:|-----------:|----------:| | `AGO` | 28 | 2000 | 2027 | | `BDI` | 28 | 2000 | 2027 | | `BEN` | 28 | 2000 | 2027 | | `BFA` | 28 | 2000 | 2027 | | `BWA` | 28 | 2000 | 2027 | | `CAF` | 28 | 2000 | 2027 | | `CIV` | 28 | 2000 | 2027 | | `CMR` | 28 | 2000 | 2027 | | `COD` | 28 | 2000 | 2027 | | `COG` | 28 | 2000 | 2027 | | `COM` | 28 | 2000 | 2027 | | `CPV` | 28 | 2000 | 2027 | | `DJI` | 28 | 2000 | 2027 | | `DZA` | 28 | 2000 | 2027 | | `EGY` | 28 | 2000 | 2027 | | ... | _38 more countries_ | | | ## Indicators (sample) - `SDG_0821_NOC_RT` — SDG indicator 8.2.1 - Annual growth rate of output per worker (GDP constant 2015 US $) (%) ## Schema | Column | Type | Description | Example | |--------|------|-------------|---------| | `ref_area` | `string` | ISO 3166-1 alpha-3 country code | `AGO` | | `ref_area.label` | `string` | Country name in English | `Angola` | | `source` | `string` | ILOSTAT source code (e.g. labour force survey) | `XA:2010` | | `source.label` | `string` | Source name in English | `ILO - Modelled Estimates` | | `indicator` | `string` | ILOSTAT indicator code | `SDG_0821_NOC_RT` | | `indicator.label` | `string` | Indicator name in English | `SDG indicator 8.2.1 - Annual growth r…` | | `time` | `int64` | Observation year | `2027` | | `obs_value` | `float64` | Observed indicator value (unit varies — see indicator definition) | `-0.759` | ## 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("electricsheepafrica/africa-ilo-sdg-0821-noc-rt-sdg-indicator-8-2-1-annual-growth-rate-of-output-p") df = ds["train"].to_pandas() print(df.head()) ``` ### Filter to one country ```python kenya = df[df["ref_area"] == "KEN"] ``` ### Time-series for a single indicator ```python sample = (df[df["indicator"] == "SDG_0821_NOC_RT"] .sort_values("time")) sample.plot(x="time", y="obs_value", title="SDG_0821_NOC_RT") ``` ### Pivot to country × year matrix ```python matrix = (df[df["indicator"] == "SDG_0821_NOC_RT"] .pivot_table(index="time", columns="ref_area", values="obs_value")) print(matrix.tail()) ``` ## Citation ```bibtex @misc{africa_ilo_sdg_0821_noc_rt_sdg_indicator_8_2_1_annual_growth_rate_of_output_p_2027, title = {SDG indicator 8.2.1 - Annual growth rate of output per worker (GDP constant 2015 US $) (%) | Africa (ILOSTAT)}, author = {International Labour Organization (ILO)}, year = {2027}, url = {https://www.ilo.org/shinyapps/bulkexplorer/?id=SDG_0821_NOC_RT}, publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa}, howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-ilo-sdg-0821-noc-rt-sdg-indicator-8-2-1-annual-growth-rate-of-output-p}} } ``` ## 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 Africa repackaging. ## About Electric Sheep Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa 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/electricsheepafrica](https://huggingface.co/electricsheepafrica) --- _Provenance: ingested 2026-05-26 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=SDG_0821_NOC_RT_

This dataset contains data for Sustainable Development Goal (SDG) indicator 8.2.1, the annual growth rate of output per worker (GDP constant 2015 US $) (%). It covers 53 African countries from 2000 to 2027, with 1,475 observations. The data is sourced from the International Labour Organization (ILO) ILOSTAT database and repackaged by Electric Sheep Africa into a standardized schema (e.g., Parquet format) for machine learning readiness. The dataset includes fields such as country code, country name, data source, indicator code, indicator label, year, and observed value, and is suitable for tasks like tabular classification, regression, and time-series forecasting. The data is harmonized by ILO using International Conference of Labour Statisticians (ICLS) definitions for consistency and traceability.

提供机构:
electricsheepafrica
搜集汇总
数据集介绍
electricsheepafrica/africa-ilo-sdg-0821-noc-rt-sdg-indicator-8-2-1-annual-growth-rate-of-output-p 数据集图片
构建方式
该数据集的数据根基源自国际劳工组织维护的ILOSTAT中央统计数据库,系可持续发展目标中关于劳动生产率的核心监测指标之一,由Electric Sheep Africa团队对原始公开数据进行系统性重新封装而成。其构建流程遵循元数据驱动的标准化范式,涵盖原始记录的采集、变量字段的规范化映射、非洲区域国别样本的筛选,以及Parquet格式的列式存储转换,最终形成覆盖53个非洲国家、时间跨度为2000年至2027年、共计1475条观测值的结构化数据资产,并配以统一的许可声明与溯源信息,以增强数据的可发现性与可复用性。
特点
该数据集聚焦于非洲大陆劳动生产率的年度演变态势,以不变价2015年美元计价的每名劳动者产出年增长率为核心度量,属于经济金融领域的时间序列横截面混合结构。其规模处于一千至一万条区间,采用列式Parquet格式存储,兼顾表格与文本双重模态,便于高效的读取与聚合运算。数据集以单一语言呈现,具备明确的可持续发展目标指标归属与非洲区域标签,涵盖就业、劳动与劳动生产率等主题维度,且以知识共享署名4.0许可开放共享,为跨国比较与长期趋势分析提供了可核查的证据基础。
使用方法
研究者可借助Hugging Face提供的datasets库以单行代码加载该数据集,通过load_dataset函数指定仓库标识符即可获取包含特征结构与样本切片的字典对象,进而检视字段类型与前若干行记录。当需要开展统计分析时,可将首个切分转换为Pandas数据框,以便进行缺失值剖析、按地理与时间维度的变量画像,以及与其他Electric Sheep Africa数据集基于国别、年份与指标字段的联结操作。在建模之前,应先行确认变量定义与计量单位,审慎处理缺失值,并保留出处引用,以确保分析流程的可复现性。
背景与挑战
背景概述
在可持续发展目标(SDGs)的监测与评估体系中,体面劳动与经济增长的量化测度始终居于核心地位。联合国于2015年通过的《2030年可持续发展议程》将劳动生产率的提升视为消除贫困、促进包容性增长的关键路径,目标8.2.1即聚焦于单位劳动力产出的年增长率这一指标。非洲地区作为全球劳动力增长最为迅猛的区域,其劳动生产率动态对区域经济转型与全球供应链格局具有深远影响。国际劳工组织(ILO)依托ILOSTAT数据库,系统汇编了非洲53国2000至2027年的相关观测值,为研究者提供了长时序、跨国别的可比数据基础。Electric Sheep Africa在此基础上完成了标准化元数据重构与Hugging Face平台适配,使该数据集成为非洲经济金融领域可复现研究的基准资源之一。
当前挑战
该数据集所应对的领域问题在于如何以跨国可比的方式精确测算非洲各国单位劳动力产出的动态变化,这要求对各国GDP核算体系、就业统计口径及购买力平价调整方法进行一致性处理。构建过程中的核心挑战包括:非洲各国劳动力调查频率与覆盖面参差不齐,非正规部门就业数据的系统性缺失导致分母估算存在偏误;GDP平减指数与2015年不变价美元的换算需依赖各国国民账户体系的完备性,部分国家数据修订频繁引发时序断裂;2020年后疫情冲击与结构性转型使增长率的趋势外推面临更大不确定性。此外,元数据中国别标识与上游发布者信息的缺失,进一步增加了数据溯源与交叉验证的难度,要求使用者在建模前对变量定义与缺失机制进行审慎评估。
常用场景
经典使用场景
在劳动经济学与宏观增长核算的交叉领域,该数据集构成刻画非洲大陆劳动生产率动态的核心素材。研究者依托其涵盖53个非洲国家、自2000年至2027年的1475条观测,围绕实际产出增长的收敛假说、结构性转型与就业弹性等命题展开面板计量分析,考察不同国家组别在增长周期中的异质反应,并借助时间序列分解辨识生产率波动的短期冲击与长期趋势成分。
解决学术问题
该数据集为发展经济学中长期存在的测量争议提供了可比性基础,使跨国生产率增长的实证检验得以在统一口径下进行。它缓解了非洲区域数据碎片化与统计口径不一致所导致的推断偏误问题,支撑对增长收敛、结构变迁与就业关系等议题的稳健估计,并推动以可持续发展目标为框架的量化监测研究,为后续元分析与跨国比较奠定可复现的数据基础。
衍生相关工作
围绕该数据集及其所属的Electric Sheep Africa目录,衍生出若干可复现的分析工作,包括非洲劳动生产率与就业结构的跨国面板研究、基于机器学习的增长预测模型,以及与其他非洲公开数据集进行国别与年份字段链接的整合性研究。这些工作延续了ILOSTAT与联合国可持续发展目标数据的分析传统,并在开放数据社区中形成标准化引用与文档实践。
以上内容由遇见数据集搜集并总结生成
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