标题： Niimpy：行为数据分析工具箱 显示英文标题

标题： Niimpy: a toolbox for behavioral data analysis

摘要： 使用个人数字设备的行为研究通常会产生丰富的时间序列数据集，包含多种数据类型。这些数据提供了用户在实时和自然环境中的行为信息。分析这些数据需要跨学科的专业知识和专用软件。目前，在Python科学计算生态系统中，尚不存在通用的、与设备无关的、免费可用的软件来预处理和分析此类数据。本文介绍了一个Python包Niimpy，用于分析数字行为数据。Niimpy工具箱是一个用户友好的开源包，可以快速扩展并适应特定的研究需求。该工具箱通过提供预处理、特征提取和数据探索的工具，促进了分析阶段。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将随着核心小组、新用户和开发人员开发的额外数据分析功能而扩展。Niimpy可以帮助越来越多的来自不同背景的研究人员，他们从个人和消费类数字设备中收集数据，以系统且高效地分析数据并提取有用信息。这种新颖的信息对于回答医学、心理学、社会学等各个领域的研究问题至关重要。 显示英文摘要

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.