Polars vs. Pandas: Rewriting a Real Data Workflow
Refactoring a real data workflow from Pandas to Polars reveals a massive performance gap. Learn how lazy execution, predicate pushdown, and Apache Arrow memory models can cut your processing time by 95%. This guide explains the mental shift required to move from eager to lazy evaluation for high-performance data pipelines.