How does Pandas optimize memory usage using internal block consolidation?

Pandas reduces memory fragmentation by merging compatible memory blocks internally.

Internally, Pandas stores columns in memory blocks grouped by dtype. When many operations like column insertion or deletion occur, memory becomes fragmented into many small blocks. Block consolidation merges these blocks into fewer contiguous arrays, improving cache efficiency and reducing overhead during computations.