De-identified dataset and analysis script for: Multimodal assessment of affective and restorative responses in memorial transition spaces using navigable, interactive virtual reality

De-identified per-participant dataset (N=12, coded P01–P12) and a dependency-free Python analysis script accompanying the pilot feasibility paper submitted to Building and Environment. Contents: merged_subj_eeg_deid_en.csv: self-report scales (PANAS, STAI-S, PRS), EEG-derived indices, session duration, demographics (30 columns) eeg_per_subject_deid.csv: EEG-derived indices and duration (18 columns) P01–P12 trajectory CSVs: head-position trajectories (~10 Hz) for locomotion visualization analysis.py: stdlib-only Python script reproducing all reported effect sizes, correlations, and power analyses README.md: data dictionary and de-identification notes Note: EEG indices are vendor-derived from a consumer-grade wearable headband; construct validity not independently verified. Age is binned into 5-year bands for privacy. No significance testing is reported (n=4 per group); effect sizes serve as planning inputs for a future powered study.