3.1. Numpy take() Method#

To take elements from a NumPy array at specific indices, we use the take() function of the NumPy library.

Syntax: numpy.take(array, indeices, axis, out, mode)

Parameters:

  1. array: Input array

  2. indices: The indices of the values to extract

  3. axis: The axis over which to select values. By default, the flattened input array is used.

  4. out: A location into which the result is stored. If provided, it must have a shape that the indices along axis.

  5. mode: {‘raise’, ‘wrap’, ‘clip’}, optional, Specifies how out-of-bounds indices will behave.

    1. ‘raise’ – raise an error (default)

    2. ‘wrap’ – wrap around

    3. ‘clip’ – clip to the range

  6. Returns: The returned array has the same type as array.

3.1.1. NumPy take()#

# Example: NumPy take()
import numpy as np
a = np.array([4, 3, 5, 7, 6, 8])
indices = [0, 1, 4]
np.take(a, indices)

array([4, 3, 6])

3.1.2. NumPy take() along an axis#

# Example: NumPy take() along an axis 1
a = np.array([[4, 3, 5], 
                [7, 6, 8]])

indices = [1]

np.take(a, indices, axis=1)

array([[3],
       [6]])

# Example: NumPy take() along an axis 0
a = np.array([[4, 3, 5],
                [7, 6, 8]])

indices = [1]

np.take(a, indices, axis=0)

array([[7, 6, 8]])