Niimpy：行为数据分析工具箱
Niimpy: a toolbox for behavioral data analysis
摘要：
使用个人数字设备的行为研究通常产生混合数据类型的丰富纵向数据集。这些数据提供关于这些设备的用户在用户的自然环境中的实时行为的信息。分析数据需要多学科专业知识和专用软件。目前，Python科学计算生态系统中还没有可推广的、与设备无关的、免费可用的软件来预处理和分析这些数据。本文介绍了一个用于分析数字行为数据的Python软件包Niimpy。Niimpy工具箱是一个用户友好的开源软件包，可以快速扩展并适应特定的研究要求。该工具箱通过提供用于预处理、提取特征和探索数据的工具来促进分析阶段。它还旨在教育用户进行行为数据分析，并促进开放科学实践。随着时间的推移，Niimpy将通过核心团队、新用户和开发人员开发的额外数据分析功能进行扩展。Niimpy可以帮助快速增长的具有不同背景的研究人员从个人和消费者数字设备中收集数据，以系统有效地分析数据并提取有用的信息。这些新颖的信息对于回答从医学到心理学、社会学等各个领域的研究问题至关重要。
英文摘要：
Behavioral studies using personal digital devices typically produce rich longitudinal datasets of mixed data types. These data provide information about the behavior of users of these devices in real-time and in the users' natural environments. Analyzing the data requires multidisciplinary expertise and dedicated software. Currently, no generalizable, device-agnostic, freely available software exists within Python scientific computing ecosystem to preprocess and analyze such data. This paper introduces a Python package, Niimpy, for analyzing digital behavioral data. The Niimpy toolbox is a user-friendly open-source package that can quickly be expanded and adapted to specific research requirements. The toolbox facilitates the analysis phase by offering tools for preprocessing, extracting features, and exploring the data. It also aims to educate the user on behavioral data analysis and promotes open science practices. Over time, Niimpy will expand with extra data analysis features developed by the core group, new users, and developers. Niimpy can help the fast-growing number of researchers with diverse backgrounds who collect data from personal and consumer digital devices to systematically and efficiently analyze the data and extract useful information. This novel information is vital for answering research questions in various fields, from medicine to psychology, sociology, and others.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
