Analyzing sleep EEG often requires combining multiple tools, creating a fragmented and error-prone workflow that slows research and limits reproducibility. To address this, we developed SleepEEGpy – an open-source Python package that unifies key steps in sleep EEG preprocessing and analysis into one streamlined, user-friendly framework. SleepEEGpy supports data cleaning, ICA, event detection, spectral analysis, and visualization, and includes an interactive dashboard for rapid data inspection. By standardizing common workflows and lowering the entry barrier for new researchers, SleepEEGpy promotes faster learning, better reproducibility, and easier collaboration across labs. We demonstrate its utility using overnight high-density EEG data, revealing typical brain dynamics across sleep stages.
SleepEEGpy: a Python-based software integration package to organize preprocessing, analysis, and visualization of sleep EEG data
