Count how many zeros you have in array

You will learn how to count the number of zeros in an array using two different Python methods: count_nonzero and where.

Numpy count zeros

Using the count_nonzero Method

The count_nonzero function is used inversely to count the number of non-zero elements, but with a logical inversion, it effectively counts zeros. To use this method, you pass the array to the count_nonzero function. The function will return the number of elements in the array that are not equal to zero.

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For example, the following code counts the number of zeros in the array my_array:

import numpy as np

my_array = np.array([[1, 0, 5],
                    [5, 3, 0],
                    [0, 0, 2]])

zeros_frequency = np.count_nonzero(my_array == 0)
print(f"Count of zeroes in my array: \n{zeros_frequency}")

This code outputs the following:

Numpy count zeros

The output shows the count of zeros in the array as determined by the count_nonzero function.

Using the where Method

The where method is a more versatile method that can be used to count the number of zeros in an array, as well as other conditions. To use this method, you pass a Boolean expression to the where function. The function will return an array of the elements in the original array that satisfy the Boolean expression.

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For example, the following code uses the where method to count the number of zeros in the array my_array:

import numpy as np

my_array = np.array([[1, 0, 5],
                    [5, 3, 0],
                    [0, 0, 2]])

zeros_frequency = my_array[np.where(my_array == 0)].size
print(f"There are {zeros_frequency} zeros in my array.")

In this approach, zeros_frequency captures the size of the array filtered by the condition, directly indicating the number of zeros.

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This code outputs the same output as the previous example.

There are 4 zeros in my array.