What is a rank 1 array in Numpy

Question

Consider the following vector:

import numpy as np

u = np.random.randn(5)
print(u)

[-0.30153275 -1.48236907 -1.09808763 -0.10543421 -1.49627068]

When we print its shape:

print(u.shape)
(5,)

I was told this is neither a column vector nor a row vector. So what is essentially this shape is in numpy (m,) ?

Answer 1

# one-dimensional array (rank 1 array)
# array([ 0.202421  ,  1.04496629, -0.28473552,  0.22865349,  0.49918827])
a = np.random.randn(5,) # or b = np.random.randn(5)

# column vector (5 x 1)
# array([[-0.52259951],
#       [-0.2200037 ],
#       [-1.07033914],
#       [ 0.9890279 ],
#       [ 0.38434068]])
c = np.random.randn(5,1)

# row vector (1 x 5)
# array([[ 0.42688689, -0.80472245, -0.86294221,  0.28738552, -0.86776229]])
d = np.random.randn(1,5)

For example (see docs):

numpy.dot(a, b)

• If both a and b are 1-D arrays, it is inner product of vectors (without complex conjugation).
• If both a and b are 2-D arrays, it is matrix multiplication