Global Hourly Electricity Demand Dataset Segregated by Season and Day Type: Tracking Changes Across COVID-19 Lockdown Phases

This dataset provides a cross-country time series of hourly typical electricity usage designed for comparative analysis of consumption patterns before, during, and after the strictest COVID-19 lockdown periods. The dataset aggregates and normalises raw usage data to present the typical hourly demand for [Number] countries, segmented by season and day type (weekday vs. weekend). The primary utility of this data is to facilitate standardised analyses of the non-pharmaceutical intervention (NPI) impact on energy consumption globally. The data processing pipeline uses external master data, including government response metrics derived from the Oxford COVID-19 Government Response Tracker (OxCGRT), to precisely define and standardise the "strictest lockdown period" for each country. The dataset is shared in two primary formats to maximise reusability and accessibility: PostgreSQL Database Dump Files (.sql): This is the recommended format for researchers seeking to replicate the full data environment or integrate the data into an existing pipeline. The files were generated from a PostgreSQL 14.22 database. It is recommended to use the same version or higher to minimise compatibility issue. dataset_schema_only: Contains the six table definitions, including all primary keys, foreign key relationships, and constraints, but no data. This is ideal for those who wish to populate the schema with their own data. dataset_full: Contains the full schema and all underlying data. This file can be used to instantly instantiate a complete, working PostgreSQL database for immediate analysis. Comma-Separated Value Files (.csv): Six individual CSV files are provided, with each file corresponding exactly to one table in the relational schema. This format offers the most direct access to the data, allowing users to easily import the records into any statistical software or alternative database management system without requiring a PostgreSQL environment setup. The database is composed of six interrelated tables, featuring the core typical_daily_usage_patterns table and five supporting tables.本数据集提供跨国分时典型电力使用量时间序列数据，旨在用于新冠疫情最严格封控政策实施前、期间及之后的电力消费模式对比分析。数据集对原始使用量数据进行聚合与归一化处理，呈现了[Number]个国家按季节与日期类型（工作日 vs. 周末）划分的典型小时电力需求。 本数据的核心效用在于支撑全球范围内非药物干预措施（Non-pharmaceutical Intervention, NPI）对能源消费影响的标准化分析。数据处理流程依托外部主数据，包括源自牛津新冠疫情政府响应追踪器（Oxford COVID-19 Government Response Tracker, OxCGRT）的政府响应指标，以精准界定并标准化各国的“最严格封控周期”。 本数据集采用两种主要格式发布，以最大化复用性与可访问性： ### PostgreSQL 数据库转储文件（.sql） 本格式为希望复刻完整数据环境或集成数据至现有流程的研究人员推荐格式。该文件由PostgreSQL 14.22版本数据库生成，建议使用相同或更高版本以最小化兼容性问题。 - dataset_schema_only：仅包含六个表的定义，涵盖所有主键、外键关系与约束条件，但不含实际数据，适用于希望自行填充数据的用户。 - dataset_full：包含完整的数据库架构与所有底层数据，可用于快速实例化完整可用的PostgreSQL数据库以开展即时分析。 ### 逗号分隔值文件（.csv） 共提供六个独立的CSV文件，每个文件与关系型数据库架构中的一个表一一对应。 该格式为用户提供了最直接的数据访问途径，无需配置PostgreSQL环境即可轻松将记录导入任意统计软件或其他数据库管理系统。 该数据库由六个相互关联的表组成，包含核心表typical_daily_usage_patterns以及五个辅助支持表。