pandas remains the default choice for notebooks, exploratory analysis, visualization, and machine learning workflows. Polars focus on fast, memory-efficient DataFrame processing, while DuckDB brings a SQL-first approach for querying local files and embedded analytics. Each tool fits a different kind of local data workflow. In this article, we compare pandas, Polars, and DuckDB across performance, […]The post Pandas vs Polars vs DuckDB: Which Library Should You Choose? appeared first on Analytics Vidhya.