Developed a multi-layer features table for the napari repository, enabling users to analyze and manage features across multiple layers within a unified interface. Leveraging Python, Pandas, and Qt, the solution introduced a dedicated layer identifier column and a join-type toggle, allowing seamless switching between inner and outer joins for feature consolidation. The implementation ensured compatibility with all layer types supporting feature data, while gracefully handling layers lacking selection information. Enhanced synchronization between the user interface and viewer layer selections improved usability, and robust handling of read-only columns supported reliable data visualization and analysis. Documentation and tests were comprehensively updated.