How does Pandas optimize memory usage during large DataFrame concatenation?

Pandas tries to preallocate output buffers and minimize intermediate copies during concat.

When concatenating DataFrames, Pandas attempts to align columns and allocate a final result buffer to avoid repeated reallocations. However, if schemas differ significantly, it falls back to copying and reindexing, increasing memory usage.