#NumPy

NumPy Fundamentals: Why Arrays Beat Python Lists, and How to Use Them

NumPy, the foundation of Python data work, from first principles: the memory layout that makes Python lists inherently slow and how ndarray fixes it, vectorized operations that eliminate loops, the broadcasting rules that let differently-shaped arrays compute together, the trap of slices being views rather than copies, reading aggregations through the axis concept, and the cases where NumPy is the wrong tool.