Beyond Performance: Why Polars Represents a Paradigm Shift from pandas
(source: Pandas vs Polars: Is It Time to Rethink Python’s Trusted DataFrame Library?) Introduction After four years of writing production data science code with pandas, I thought I understood data manipulation in Python. I had memorized the subtle differences between .apply(), .transform(), and .agg(). I knew when to use .loc[] versus .iloc[], when to chain methods versus create intermediate variables, and how to navigate the maze of groupby operations that seemed to change behavior depending on context. ...