How to use numpy.zeros() in Python

How to use numpy.zeros() in Python

In Python, numpy.zeros() is a function that is used to create a new NumPy array filled with zeros.

This function is often used to create arrays with a specific shape and size that can be used in mathematical and scientific calculations.

Syntax

Here is the syntax for numpy.zeros():

numpy.zeros(shape, dtype=float, order='C')

This function takes the following arguments:

• shape: The shape of the array. This is specified as a tuple of integers, where each integer specifies the size of the corresponding array dimension. For example, a shape of (3, 4) would create a two-dimensional array with 3 rows and 4 columns.
• dtype (optional): The data type of the array. This specifies the type of the array elements. The default is float, which creates an array of floating-point numbers. You can also specify other data types, such as int for integer arrays or complex for complex-valued arrays.
• order (optional): The order in which the array elements are stored in memory. The default is 'C', which means that the elements will be stored in a row-major order (i.e., the last index will vary the fastest). You can also specify 'F' to store the array elements in a column-major order (i.e., the first index will vary the fastest).

Examples

Here is an example of how you might use numpy.zeros() to create a new NumPy array filled with zeros. Suppose you want to create a two-dimensional array with 3 rows and 4 columns, like this:

import numpy as np

a = np.zeros((3, 4))

This will create a new array with the specified shape, filled with zeros. The resulting array will look like this:

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

You can also specify the dtype and order arguments to numpy.zeros() to control the data type and memory layout of the array. For example, you can create an integer array with a column-major memory layout like this:

a = np.zeros((3, 4), dtype=int, order='F')

This will create the following array:

array([[0, 0, 0, 0],
       [0, 0, 0, 0],
       [0, 0, 0, 0]])