Niimpy emerges as a versatile, open-source framework designed to address the complexities of analyzing rich, longitudinal behavioral datasets from personal digital devices like smartphones and fitness trackers. Catering primarily to researchers proficient in Python and scientific computing, Niimpy simplifies data preprocessing, feature extraction, and exploratory analysis, integrating smoothly into the Python ecosystem. Beyond its technical capabilities, Niimpy champions open science, offering extensive documentation and real-data examples to guide users. While it demands some programming acumen, it empowers researchers across disciplines like medicine, psychology, and sociology to delve deep into their digital data, ensuring systematic, effective analysis. With its commitment to continual enhancement and community-driven development, Niimpy stands poised to become an indispensable tool in behavioral research.