>>> import numpy as np>>> x = np.array ([1, 2, 3])>>> xarray ([1, 2, 3])>>> y = np.arange (10)>>> yarray ([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

>>> a = np.array ([1, 2, 3, 6])>>> b = np.linspace (0, 2, 4)>>> c = a - b>>> carray ([ 1.        ,  1.33333333,  1.66666667,  4.        ])>>> a**2array ([ 1,  4,  9, 36])

>>> a = np.linspace (-np.pi, np.pi, 100) >>> b = np.sin (a)>>> c = np.cos (a)

>>> from numpy.random import rand>>> from numpy.linalg import solve, inv>>> a = np.array ([[1, 2, 3], [3, 4, 6.7], [5, 9.0, 5]])>>> a.transpose ()array ([[1. , 3. ,  5. ],       [ 2. ,  4. ,  9. ],       [ 3. ,  6.7,  5. ]])>>> inv (a)array ([[-2.27683616, 0.96045198,  0.07909605],       [ 1.04519774, -0.56497175,  0.1299435 ],       [ 0.39548023,  0.05649718, -0.11299435]])>>> b =  array ([3, 2, 1])>>> solve (a, b)  # résout ax = barray ([-4.83050847,  2.13559322,  1.18644068])>>> c = rand (3, 3)  # crée une matrice 3x3 au hasard>>> carray ([[ 3.98732789, 2.47702609,   4.71167924],       [  9.24410671,   5.5240412 ,  10.6468792 ],       [ 10.38136661,   8.44968437,  15.17639591]])>>> np.dot (a, c)  # multiplication de matricesarray ([[ 53.61964114, 38.8741616 ,   71.53462537],       [ 118.4935668 ,   86.14012835,  158.40440712],       [ 155.04043289,  104.3499231 ,  195.26228855]])>>> a @ c  # depuis Python 3.5 et นัมไพ 1.10, équivalent à np.dot (a, c) array ([[ 53.61964114, 38.8741616 ,   71.53462537],       [ 118.4935668 ,   86.14012835,  158.40440712],       [ 155.04043289,  104.3499231 ,  195.26228855]])