Selecting elements from a 2-d array is very similar to selecting them from a 1-d array, we just have two indices to select from. The syntax for selecting from a 2-d array is
a is the array.
It’s important to note that when we work with arrays that have more than one dimension, the relationship between the interior arrays is defined in terms of axes. A two-dimensional array has two axes: axis 0 represents the values that share the same indexical position (are in the same column), and axis 1 represents the values that share an array (are in the same row). This is illustrated below.
Consider the array
a = np.array([[32, 15, 6, 9, 14], [12, 10, 5, 23, 1], [2, 16, 13, 40, 37]])
We can select specific elements using their indices:
>>> a[2,1] 16
Let’s say we wanted to select an entire column, we can insert
: as the row index:
# selects the first column >>> a[:,0] array([32, 12, 2])
The same works if we want to select an entire row:
# selects the second row >>> a[1,:] array([12, 10, 5, 23, 1])
We can further narrow it down and select a range from a specific row:
# selects the first three elements of the first row >>> a[0,0:3] array([32, 15, 6])
Our students’ test scores are now stored in the 2-d array
student_scores. The first row stores the scores of the first test, the second row the second test, and the third row the third test, as shown in the following table:
Tanya wants to know how well she did on third test. Select her score from the array and save it to
You have a parent teacher conference with Cody’s parents coming up and would like to have all of his test scores handy.
Select all of Cody’s test scores and save them to a new array