Data and Code for: Quantifying Stylistic Evolution in Western Art Music: A Computational Framework from Bach to Debussy

This repository contains the replication data and custom Python code used in the study: "Quantifying Stylistic Evolution in Western Art Music: A Computational Framework from Bach to Debussy." It provides the necessary files to reproduce the statistical analyses (ANOVA, Tukey HSD, Difference-in-Differences, and Permutation Tests) and dimensionality reduction (PCA) visualizations presented in the paper.Contents of the Archive:src/: The complete suite of Python scripts used for feature extraction, statistical testing, embedding generation, and plot rendering.data/curated/: Metadata containing the list of the 144 solo piano scores analyzed in this study.data/features/: The pre-computed feature matrices (Harmonic, Melodic, and Rhythmic CSVs) extracted using music21.data/stats/: Tabular outputs of the statistical scripts, including ANOVA results, PCA component loadings, and evolutionary difference-in-differences (DD) coefficients.Note: To comply with data sharing best practices without duplicating massive external databases, this repository contains the pre-processed numerical matrices rather than the raw symbolic scores. The original raw MusicXML files are publicly available via the PDMX dataset (Long et al., 2024).