Niimpy: a toolbox for behavioral data analysis
A. Ik\"aheimonen, A.M. Triana, N. Luong, A. Ziaei, J. Rantaharju, R., Darst, and T. Aledavood

TL;DR
Niimpy is an open-source Python toolbox designed to facilitate preprocessing, feature extraction, and exploration of behavioral data from personal digital devices, promoting open science and interdisciplinary research.
Contribution
This paper introduces Niimpy, the first generalizable, device-agnostic Python software for behavioral data analysis, expanding research capabilities across multiple disciplines.
Findings
Provides a user-friendly, expandable toolkit for behavioral data analysis.
Supports preprocessing, feature extraction, and data exploration.
Promotes open science and interdisciplinary research.
Abstract
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…
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Taxonomy
TopicsDigital Mental Health Interventions · Green IT and Sustainability
