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

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Nested Lists:

Python lists are efficient general-purpose containers that support efficient operations like insertion,appending,deletion and concatenation.

The limitations of lists are that they don’t support “vectorized” operations like element wise addition and multiplication, and the fact that they can contain objects of differing types mean that Python must store type information for every element, and must execute type dispatching code when operating on each element.

Numpy:

NumPy is more efficient and more convenient as you get a lot of vector and matrix operations for free, which helps to avoid unnecessary work and complexity of the code.Numpy is also efficiently implemented when compared to nested

NumPy array is faster and contains a lot of built-in functions which will help in FFTs, convolutions, fast searching, linear algebra,basic statistics, histograms,etc.

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