NumPy: numpy.zeros() function

numpy.zeros() function

The numpy.zeros() function is used to create an array of specified shape and data type, filled with zeros.
The function is commonly used to initialize an array of a specific size and type, before filling it with actual values obtained from some calculations or data sources. It is also used as a placeholder to allocate memory for later use.

Syntax:

numpy.zeros(a, dtype=None, order='K', subok=True)

Parameters:

Return value:

[ndarray] Array of zeros with the given shape, dtype, and order.

Example: Creating a numpy array of zeros with a tuple shape

>>> import numpy as np
>>> a = (3,2)
>>> np.zeros(a)
array([[ 0.,  0.],
       [ 0.,  0.],
       [ 0.,  0.]])

In the above code a tuple (3, 2) is created and assigned to variable 'a'. The np.zeros() function is called with 'a' as its argument, which creates a numpy array of zeros with a shape of (3, 2).

Pictorial Presentation:

Example: Creating arrays of zeros using NumPy

>>> import numpy as np
>>> np.zeros(6)
array([ 0.,  0.,  0.,  0.,  0.,  0.])
>>> np.zeros((6,), dtype=int)
array([0, 0, 0, 0, 0, 0])
>>> np.zeros((3, 1))
array([[ 0.],
       [ 0.],
       [ 0.]])

In the above code the first line, np.zeros(6) creates a one-dimensional array of size 6 with all elements set to 0, and its data type is float.

In the second line, np.zeros((6,), dtype=int) creates a one-dimensional array of size 6 with all elements set to 0, and its data type is integer.

In the third line, np.zeros((3, 1)) creates a two-dimensional array of size 3x1 with all elements set to 0, and its data type is float.

Pictorial Presentation:

Example: Create a 3D array with zeros along a specified axis

Code:

import numpy as np

# Create a 3D array with zeros along the second axis
nums = np.zeros((2, 3, 4), dtype=int)
nums[:, 1, :] = 2
print(nums)

Output:

[[[0 0 0 0]
  [2 2 2 2]
  [0 0 0 0]]

 [[0 0 0 0]
  [2 2 2 2]
  [0 0 0 0]]]

In the above example, we create a 3D array with dimensions (2, 3, 4) using np.zeros() function. We then set the values of the second axis to 2, resulting in a 3D array with zeros along the first and third axis and 2's along the second axis.

Example: Create a 2D array with a custom data type and byte order

Code:

import numpy as np

# Create a 2D array of unsigned 16-bit integers with big-endian byte order
nums = np.zeros((2, 3), dtype=np.dtype('>u2'))
print(nums)

Output:

[[0 0 0]
 [0 0 0]]

In the above example, we create a 2D array with dimensions (2, 3) using np.zeros() function. Using the np.dtype() function, we specify an unsigned 16-bit integer with big-endian byte order. The resulting array has values of 0 and the specified data type and byte order.

Python - NumPy Code Editor:

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