A data workflow optimized in Pandas from 61 seconds to 0.31 seconds was rewritten in Polars, achieving a 0.20-second runtime using lazy evaluation. This demonstrates Polars' inherent architectural advantages and automatic query optimization capabilities for high-performance data pipelines.
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