Polars is built from the ground up for high performance, executing common operations 5-10 times faster than pandas, with significantly lower memory requirements. It can handle larger datasets before facing out-of-memory errors, making it one of the fastest DataFrame libraries overall.
Polars' speed is attributed to being written in Rust, a low-level language, designed for performance efficiency, enabling it to achieve exceptional results on a single machine.
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