Python:NumPy .zeros()

.zeros() is a NumPy function used to create a new array of a specified shape, filled entirely with zeros. It is commonly used to initialize arrays before assigning them meaningful data.

Syntax

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

Parameters:

• shape: An integer or tuple of integers indicating the dimensions of the array. For example, (3, 2) creates a 2D array with 3 rows and 2 columns.
• dtype: The desired data type for the array elements (default is float).
• order: Whether to store the array in row-major ('C', default) or column-major ('F') order.

Return value:

Returns a new array of the given shape, filled entirely with zeros.

Example

This example creates a 1D array of five zeros and a 2D array of zeros with shape (3, 2) and integer data type using NumPy’s .zeros() function:

import numpy as np

array1 = np.zeros(5)
print(array1)

array2 = np.zeros((3, 2), dtype=int)
print(array2)

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The output of this code will be:

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

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Codebyte Example: Initializing a Sensor Readings Matrix

In this codebyte example, .zeros() is used to initialize a 2D array to store temperature sensor readings for 7 days across 3 different locations:

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Here, .zeros() prepares a placeholder matrix to store daily sensor readings, which will be updated later as data is collected.