How to calculate the rank of a matrix in NumPy (Python)

Using linalg module in numpy, the rank of a matrix is easily calculated.

import numpy as np
from numpy import linalg

A = np.array([[1, 2], [3, 4]])
B = np.array([[1, 2], [1, 2]])
C = np.array([[0, 0], [0, 0]])
D = np.array([[0, 0, 1], [1, 0, 0]])

a = linalg.matrix_rank(A)
b = linalg.matrix_rank(B)
c = linalg.matrix_rank(C)
d = linalg.matrix_rank(D)

print(a)  # 2
print(b)  # 1
print(c)  # 0
print(d)  # 2

The rank of a matrix is equal to the dimension of the linear spaces generated by the matrix's rows (or columns).

The rank of B is 1 because (1, 2) and (1, 2) generate 1 dimension space (line).