How does Pandas optimize memory during filtering operations?

Filtering creates boolean masks but avoids copying full datasets until necessary.

When filtering, Pandas generates a boolean mask using vectorized operations. The mask itself is lightweight compared to the dataset. Only the resulting subset is materialized, reducing unnecessary memory duplication. However, repeated filtering can create multiple intermediate objects.