Indexing and Selection in 2d with Numpy Arrays

Indexing and Selection in 2d with Numpy Arrays

Matrices or one of the most useful structures to use in mathematics. While numpy does have a matrix data structure, it is more common to use a 2d array using the baisc np.array method. In this article, we will see how to select items from 2d arrays in numpy.

In our example below, we start by creating a 2d array with 3 rows and 3 columns.

2d = np.array([
	[1, 2, 3],
	[4, 5, 6],
	[7, 8, 9],
])

No, we see how to select rows. We can us normal array index notation, but we will receive rows back instead of indiviual elements.

# Select the first row
print(2d[0])

# Select the second row
print(2d[1])

# Select up to the first row
print(2d[:1])

Finally, we see how to select rows and columns. The notation is similar, but we add an extra selector after a comma. We can also use the slice operator to select multiple rows and columns.

# Select the first row, second column
print(2d[0, 1])

# Select the first two rows, second and third columns
print(2d[:2, 1:])