The NumPy array interface is, on a shallow level, similar to that of Python lists. NumPy arrays can be indexed using integers and iterated using a for loop:
A = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8]) A[0] # Result: # 0 [a for a in A] # Result: # [0, 1, 2, 3, 4, 5, 6, 7, 8]
In NumPy, array elements and sub-arrays can be conveniently accessed by using multiple values separated by commas inside the subscript operator, []. If we take a (3,3) array (an array containing three triplets), and we access the element with index 0, we obtain the first row, as follows:
A = np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]]) A[0] # Result: # array([0, 1, 2])
We can index the row again by adding another index separated by a comma. To get ...
