They're similarly expressive, and there are some areas where Polars (taking ideas from years of Pandas development) is ahead, for example with nullable dtypes.

They're similarly expressive, and there are some areas where Polars (taking ideas from years of Pandas development) is ahead, for example with nullable dtypes. That being said, there are many, many times when I would be willing to rewrite code to make it faster or more memory efficient. Just yesterday I rewrote a method from Pandas to Polars to take advantage of that. Time might be cheap (while developing) but memory is expensive. Similarly, if you're writing data science jobs for production, you care about both.