What advantages do NumPy arrays offer over (nested) Python lists?

Programming Language
#1

Nested Lists :

  • Python lists are useful general-purpose containers that may be used for insertion, appending, deletion, and concatenation.

  • Lists have two drawbacks: they don’t support “vectorized” operations like element-wise addition and multiplication, and the fact that they can contain objects of various types necessitates Python storing type information for each element and executing type dispatching code when operating on each element.

Numpy :

  • NumPy is more efficient and convenient since it provides a large number of vector and matrix operations for free, reducing the amount of effort and code complexity. When compared to nested loops, Numpy is also more efficient.

  • NumPy arrays are quicker and include more built-in functions for FFTs, convolutions, rapid searching, linear algebra, basic statistics, histograms, and other tasks.