Python | Check if list is Matrix

Index of Non-Zero Elements in Python list

Last Updated : 05 Feb, 2025

We are given a list we need to find all indexes of Non-Zero elements. For example, a = [0, 3, 0, 5, 8, 0, 2] we need to return all indexes of non-zero elements so that output should be [1, 3, 4, 6].

Using List Comprehension

List comprehension can be used to find the indices of non-zero elements by iterating through the list with enumerate(). It collects indices where element is not zero into a new list.

Python

a = [0, 3, 0, 5, 8, 0, 2]

# Use list comprehension with enumerate() to get indices of non-zero elements
ind = [i for i, val in enumerate(a) if val != 0]
print(ind)

Output

[1, 3, 4, 6]

Explanation:

enumerate(a) provides both index and value, and list comprehension filters indices where the value is non-zero.
Result is a list of indices of non-zero elements.

Using a Loop

We can use a loop with enumerate() to iterate through the list and check for non-zero values. If a value is non-zero we append its index to a separate list.

Python

a = [0, 3, 0, 5, 8, 0, 2]
ind = []
for i in range(len(a)):
    # If the element is non-zero, append its index to the list
    if a[i] != 0:
        ind.append(i)
print(ind)

Output

[1, 3, 4, 6]

Using NumPy

NumPy provides numpy.nonzero() function which returns indices of non-zero elements in an array. Converting a list to a NumPy array allows efficient retrieval of these indices.

Python

import numpy as np
a = [0, 3, 0, 5, 8, 0, 2]

# Use np.nonzero() to get indices of non-zero elements and convert to a list
ind = np.nonzero(a)[0].tolist()
print(ind)

Output

[1, 3, 4, 6]

Explanation:

np.nonzero(a) returns a tuple containing an array of indices where elements in a are non-zero, and [0] extracts the first element (the indices array).
.tolist() converts the NumPy array of indices into a regular Python list.

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