numpy.zeros() function creates a new array of specified shapes and types, filled with zeros. It is beneficial when you need a placeholder array to initialize variables or store intermediate results. We can create 1D array using numpy.zeros().

Let's understand with the help of an example:

import numpy as np

#Create 1D array
arr = np.zeros(5)
print(arr)

[0. 0. 0. 0. 0.]

Syntax of numpy.zeros()

numpy.zeros(shape, dtype = None, order = 'C')

Parameters:

• shape: integer or sequence of integers – Defines the shape of the new array. Can be a single integer or a tuple.
• dtype: optional, default is float – The data type of the returned array. If not specified, the default is float.
• order: {‘C’, ‘F’} – Specifies the memory layout order:
  • C-order: C-contiguous order means the last index varies the fastest. It is optimal for row-wise operations.
  • F-order: FORTRAN-contiguous order means the first index varies the fastest. It is optimal for column-wise operations.

Return Value

• numpy.zeros() returns a new array filled with zeros, based on the specified shape and type.

Creating 2D Array

by using NumPy, we can easily create a 2D array filled with zeros using the numpy.zeros() function.

import numpy as np

# Creating a 2D array with 3 rows and 4 columns
arr = np.zeros((3, 4))

print(arr)

[[0. 0. 0. 0.]
 [0. 0. 0. 0.]
 [0. 0. 0. 0.]]

Specifying Data Type (dtype)

dtype parameter in numpy.zeros() defines the type of data stored in the array.

import numpy as np 

# Create an array of tuples with zeros
d = np.zeros((2, 2), dtype=[('f', 'f4'), ('i', 'i4')])
print(d)

[[(0., 0) (0., 0)]
 [(0., 0) (0., 0)]]

C vs F Order

Choosing the right memory layout can significantly improve performance, depending on our specific operations. If your operations are row-wise, use C-order. If they are column-wise, use F-order.

import numpy as np 
# Create a 2x3 array in C-order
e = np.zeros((2, 3), order='C')
print("C-order array:", e)

# Create a 2x3 array in F-order
f = np.zeros((2, 3), order='F')
print("F-order array:", f)

C-order array: [[0. 0. 0.]
 [0. 0. 0.]]
F-order array: [[0. 0. 0.]
 [0. 0. 0.]]