In the course of my dissertation research, I developed a Python library for working with musical scores as Pandas dataframes, which I call music_df. You can find it on GitHub at https://github.com/malcolmsailor/music_df. With this library, you can among many other things:

  • read from a variety of formats, including MIDI, Humdrum, MusicXML, and others.
  • postprocess the scores in various ways, such as salami-slicing, quantizing, dedoubling and de-tremoloing them.
  • apply augmentations like transposition (which can be sensitive to pitch-spelling) or time-scaling (which adjusts the time signatures appropriately).
  • plot dataframes as piano-rolls or display them as scores, displaying annotations or coloring noteheads.

Everything is in a tabular format convenient for machine learning and other data science applications. Documentation is a work in progress, but can be found at https://music-df.readthedocs.io/en/latest/index.html.