Get a Row from Numpy Array
To get specific row of elements, access the numpy array with all the specific index values for other dimensions and
: for the row of elements you would like to get. It is special case of array slicing in Python.
For example, consider that we have a 3D numpy array of shape (m, n, p). And we would like to get the row of elements at ith element along axis=0, and kth element along axis=2. Use the following syntax to get this desired row of elements.
row = ndarray[i, :, k]
Example 1: Access a specific row of elements
In the following example, we will initialize a 3D array and access a specific row of elements present at index=0 along axis=0, and index=1 along axis=2.
import numpy as np #initialize an array arr = np.array([[[11, 11, 9, 9], [11, 0, 2, 0]], [[10, 14, 9, 14], [0, 1, 11, 11]]]) # print shape of array print('Array Shape: ',arr.shape) # get the desired row row = arr[0, :, 1] print('Desired Row of Elements: ', row)
Array Shape: (2, 2, 4) Desired Row of Elements: [11 0]
Example 2: Access a Specific Row or Column in 2D Numpy Array
In the following example, we will initialize a 2D array and access a row and column using array slicing.
import numpy as np #initialize an array arr = np.array([[11, 11, 9, 9], [11, 0, 2, 0]]) print('Array\n',arr) # get index=1 along axis=0 - this means a row in 2D row = arr[1, :] print('arr[1, :] : ', row) # get index=2 along axis=1 - this means a column in 2D row = arr[:, 2] print('arr[:, 2] : ', row)
Array [[11 11 9 9] [11 0 2 0]] arr[1, :] : [11 0 2 0] arr[:, 2] : [9 2]