Polars introduces non-elementary group-by aggregations, which allow for complex queries not feasible with pandas, thus optimizing data operations.
In Pandas, expressing complex aggregation queries becomes inefficient or impossible due to limitations in its API, which hinders optimization potential.
The group-by operation in Polars enables aggregating data in innovative ways, enhancing performance due to its focus on features like lazy execution and multithreading.
While many focus on Polars' benefits like Rust and query optimization, its capability for non-elementary aggregations could significantly improve how data is processed.
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