Why is my Python script's memory usage skyrocketing with large dataframes?

I'm processing several large Pandas DataFrames (each 1GB+) in a Python script, performing various transformations and aggregations. Despite deleting intermediate DataFrames with `del` and running `gc.collect()`, my script's memory consumption continuously increases, eventually leading to a `MemoryError`. Is there a common pitfall I'm missing with large data processing in Python, or a specific strategy for better memory management with Pandas?