What is the difference between ndarray and array in numpy?

Question

What is the difference between ndarray and array in Numpy? And where can I find the implementations in the numpy source code?

Answer 1

numpy.ndarray() is a class, while numpy.array() is a method / function to create ndarray.

In numpy docs if you want to create an array from ndarray class you can do it with 2 ways as quoted:

1- using array(), zeros() or empty() methods: Arrays should be constructed using array, zeros or empty (refer to the See Also section below). The parameters given here refer to a low-level method (ndarray(…)) for instantiating an array.

2- from ndarray class directly: There are two modes of creating an array using __new__: If buffer is None, then only shape, dtype, and order are used. If buffer is an object exposing the buffer interface, then all keywords are interpreted.

The example below gives a random array because we didn't assign buffer value:

np.ndarray(shape=(2,2), dtype=float, order='F', buffer=None)

array([[ -1.13698227e+002,   4.25087011e-303],
       [  2.88528414e-306,   3.27025015e-309]])         #random

another example is to assign array object to the buffer example:

>>> np.ndarray((2,), buffer=np.array([1,2,3]),
...            offset=np.int_().itemsize,
...            dtype=int) # offset = 1*itemsize, i.e. skip first element
array([2, 3])

from above example we notice that we can't assign a list to "buffer" and we had to use numpy.array() to return ndarray object for the buffer

Conclusion: use numpy.array() if you want to make a numpy.ndarray() object"