Are magic commands equivalent to Complexity analysis of algorithm?

What is the complexity analysis of exploiting the vectorization operations to solve the problems? Although we saw the varying difference in execution time using magic commands such as for typical loops, map function and NumPy operations, can this be perceived as equivalent to the complexity analysis that’s crucial in data structures and algorithm? Will the complexity remains within O(1) and O(N) or does it increases to O(N^2), O(N^3), etc… when we choose NumPy operations over typical use of loops for high dimensional data?

Hi @4deep.prk,
Thanks again for asking such a wonderful question.
Hope you can get your answer here : “Is there a list of big O complexities for the numpy library? - Stack Overflow”


Thank you once again :smiley: