Mischos Stavros, Gkalinikis Nikolaos Virtsionis, Manolopoulou Aikaterini, Dalagdi Eleana, Zaikis Dimitrios, Lazaridis Aristotelis, Vlachava Danai, Lagouvardos Kostantinos, Vrakas Dimitrios
Aristotle University of Thessaloniki, School of Informatics, Greece.
Information Technologies Institute, Centre of Research & Technology-Hellas, Greece.
Data Brief. 2023 May 12;48:109232. doi: 10.1016/j.dib.2023.109232. eCollection 2023 Jun.
The electricity consumption of a residence depends on many factors such as the habits and economical status of the occupants, the properties of the household and many more. To shed more light on the subject a data set for households was created. The data were collected in Greece through an anonymous survey that comprises 26 questions, resulting in 188 data points from 104 households from different time periods. Each data point contains attributes that are divided into four categories. In the first category, the information is about the household data such as the type and properties of the residence. Next, occupants' socio-economic features are gathered. In this category information for the number and type of the occupants, the employment status and the total income of the residents is included. The third category of attributes is about the energy-related occupants' behavior. Finally, the location of the household was provided from the users to estimate the weather conditions for the provided time. Data augmentation was performed to discover non-trivial relationships between the data points. Thus, a secondary set of features was computed based on the raw attributes and is also included. The provided data set can be used to extract insights that could be valuable during the imminent energy crisis.
住宅的用电量取决于许多因素，如居住者的习惯和经济状况、家庭财产等等。为了更深入地了解这个问题，创建了一个家庭数据集。这些数据是在希腊通过一项包含26个问题的匿名调查收集的，来自104个家庭不同时间段的188个数据点。每个数据点包含分为四类的属性。在第一类中，信息是关于家庭数据，如住宅的类型和属性。接下来，收集居住者的社会经济特征。在这一类中，包括居住者的数量和类型、就业状况以及居民的总收入信息。第三类属性是关于与能源相关的居住者行为。最后，用户提供了家庭位置以估计所提供时间的天气状况。进行了数据增强以发现数据点之间的重要关系。因此，基于原始属性计算了一组辅助特征，并且也包括在内。所提供的数据集可用于提取在即将到来的能源危机期间可能有价值的见解。
