NumPy efficiently handles large datasets because it uses fixed-type arrays that use less memory than lists. Its calculations run across the entire memory block without repeated checks, thanks to its C and Fortran base. Vectorised operations mean no need to code for loops. With memory-mapped files, NumPy loads only the parts needed into memory, helping with very large datasets.
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