What is the difference between internal BlockManager and ArrayManager in modern Pandas?

BlockManager groups columns by dtype; ArrayManager stores each column independently.

BlockManager is the older internal structure where columns of the same dtype are grouped into contiguous memory blocks. ArrayManager is a newer approach where each column is stored as a separate array, improving predictability and reducing fragmentation issues. ArrayManager simplifies memory handling and aligns Pandas more closely with NumPy-like semantics.