A = np.array([
[-1, 3],
[3, 2]
], dtype=np.dtype(float))
b = np.array([7, 1], dtype=np.dtype(float))
print(f"Shape of A: {A.shape}")
print(f"Shape of b: {b.shape}")
Gives the following output :
Shape of A: (2, 2)
Shape of b: (2,)
I was expecting shape of b to be (1,2) which is one row and two columns, why is it (2,) ?
Your assumption is incorrect, b only has one dimension, not two.
b.ndim
# 1
To have a 2D array you would have needed an extra set of square brackets:
b = np.array([[7, 1]], dtype=np.dtype(float))
b.shape
# (1, 2)
b.ndim
# 2
Similarly for a 3D array:
b = np.array([[[7, 1]]], dtype=np.dtype(float))
b.shape
# (1, 1, 2)
b.ndim
# 3
Note that you can transform your original b into a 2D array with:
b = np.array([7, 1], dtype=np.dtype(float))
b.shape = (1, 2)
b
# array([[7., 1.]])
Or:
b = np.array([7, 1], dtype=np.dtype(float))[None]
b.shape
# (1, 2)
b
# array([[7., 1.]])