You can use the following methods to sort the rows of a NumPy array by column values:

Method 1: Sort by Column Values Ascending

x_sorted_asc = x[x[:, 1].argsort()]

Method 2: Sort by Column Values Descending

x_sorted_desc = x[x[:, 1].argsort()[::-1]]

The following examples show how to use each method in practice.

Example 1: Sort Numpy Array by Column Values Ascending

Suppose we have the following NumPy array:

import numpy as np

#create array
x = np.array([14, 12, 8, 10, 5, 7, 11, 9, 2]).reshape(3,3)

#view array
print(x)

[[14 12  8]
 [10  5  7]
 [11  9  2]]

We can use the following code to sort the rows of the NumPy array in ascending order based on the values in the second column:

#define new matrix with rows sorted in ascending order by values in second column
x_sorted_asc = x[x[:, 1].argsort()]

#view sorted matrix
print(x_sorted_asc)

[[10  5  7]
 [11  9  2]
 [14 12  8]]

Notice that the rows are now sorted in ascending order (smallest to largest) based on the values in the second column.

Example 2: Sort Numpy Array by Column Values Descending

Suppose we have the following NumPy array:

import numpy as np

#create array
x = np.array([14, 12, 8, 10, 5, 7, 11, 9, 2]).reshape(3,3)

#view array
print(x)

[[14 12  8]
 [10  5  7]
 [11  9  2]]

We can use the following code to sort the rows of the NumPy array in descending order based on the values in the second column:

#define new matrix with rows sorted in descending order by values in second column
x_sorted_desc = x[x[:, 1].argsort()[::-1]]

#view sorted matrix
print(x_sorted_desc)

[[14 12  8]
 [11  9  2]
 [10  5  7]]

Additional Resources

The following tutorials explain how to perform other common operations in Python: