Data aesthetics
summary
Code written in Python reads Postgres data directory and uses relation forks to pull raw row-and-column bytes, then writes binary as BMP by assigning dimensions so any byte stream becomes pixels. Resulting images show horizontal bands from rows and vertical textures from columns; examples demonstrate recognizable patterns and a few surprisingly clear motifs. Next steps are to apply ML filters to enhance visual structure and to map byte sequences into notes so the same files produce music.
AI-written summary · about
related talks
31mMaking Data Dance
51mArt of Effective Visualization of Multi-dimensional Data
26mPython Data Sonification for Science and Discovery
50mUnearthing the Past with PostgreSQL...
31mPicasso, Geometry, Jupyter
33mMaking Data Dance
03h 07mData of Unusual Size: Interactive Visualization
01h 04mVisualising Data through Pandas
