How to Create a List of Zeros in Python

Initializing a list with a specific size and a default value, such as zero, is a common programming task. It is often used to pre-allocate space for a data structure or to create a baseline for numerical operations. Python provides a particularly concise and readable syntax for this using the multiplication (*) operator.

This guide will demonstrate the most Pythonic way to create a list of zeros and will also cover alternatives like list comprehensions. Additionally, we will discuss the powerful numpy.zeros() function for numerical computing and highlight a critical pitfall to avoid when using this technique with mutable objects.

Method 1: Using the Multiplication Operator * (Recommended)

The simplest and most direct way to create a list of zeros is to multiply a list containing a single zero ([0]) by the desired length.

Solution:

# Create a list containing 5 zeros
length = 5
list_of_zeros = [0] * length

print(list_of_zeros)

# Create a list containing 10 zeros
another_list = [0] * 10
print(another_list)

Output:

[0, 0, 0, 0, 0]
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

This syntax is clean, expressive, and perfectly safe for immutable objects like integers, strings, or floats. You can easily wrap this logic in a function for reusability.

def create_list_of_zeros(length):
    return [0] * length

my_list = create_list_of_zeros(3)
print(my_list)

Output:

[0, 0, 0]

Method 2: Using a List Comprehension

A list comprehension provides a more verbose but also more flexible way to create a list of zeros. This pattern is useful when the initial value is more complex or when you want your code to be more explicit about the creation of each element.

Solution:

length = 5

# Create a list of 5 zeros using a list comprehension
list_of_zeros = [0 for _ in range(length)]

print(list_of_zeros)

Output:

[0, 0, 0, 0, 0]

note

We use an underscore (_) as the loop variable because we don't need to use the value from range()—we only need to repeat the action length times. This is a common convention in Python.

For Numerical Computing: Using numpy.zeros()

If you are performing numerical or scientific computing, the NumPy library is the standard tool. It provides a highly optimized numpy.zeros() function for creating arrays of zeros, which are far more efficient for mathematical operations than standard Python lists.

First, ensure you have NumPy installed: pip install numpy

Solution:

import numpy as np

# Create a 1D NumPy array (vector) of 5 zeros
# The default dtype is float64
vector_of_zeros = np.zeros(5)
print(f"1D float array:\n{vector_of_zeros}")

# Create a 2D NumPy array (matrix) of integers
matrix_of_zeros = np.zeros((3, 4), dtype=int)
print(f"\n2D integer array (matrix):\n{matrix_of_zeros}")

Output:

1D float array:
[0. 0. 0. 0. 0.]

2D integer array (matrix):
[[0 0 0 0]
 [0 0 0 0]
 [0 0 0 0]]

Important Warning: Avoid Multiplying Mutable Objects

The multiplication method ([item] * n) has a major pitfall when the item is a mutable object, such as a list or a dictionary. This is because the multiplication creates n copies of the reference to the same object, not n new, independent objects.

Example of the common pitfall:

# Incorrect way to create a list of lists (nested list)
# This creates three references to the SAME inner list.
nested_list = [[]] * 3
print(f"Initial list: {nested_list}")

# Modify the first inner list
nested_list[0].append(99)

# The change is reflected in ALL inner lists, because they are the same object.
print(f"List after modification: {nested_list}")

Output:

Initial list: [[], [], []]
List after modification: [[99], [99], [99]]

warning

This unexpected behavior is a common source of bugs. The correct way to create a list of mutable objects is with a list comprehension, which ensures a new object is created in each iteration.

The Correct Way for Mutable Objects:

# Correct: Use a list comprehension to create a list of independent lists
correct_nested_list = [[] for _ in range(3)]
print(f"Initial list: {correct_nested_list}")

# Modify the first inner list
correct_nested_list[0].append(99)

# Only the first inner list is changed.
print(f"List after modification: {correct_nested_list}")

Output:

Initial list: [[], [], []]
List after modification: [[99], [], []]

Conclusion

If your goal is to...	The best solution is...	Example
Create a list of zeros or other immutable values	The multiplication operator (*)	[0] * 5
Create a list of mutable objects (like lists or dicts)	A list comprehension	[{} for _ in range(5)]
Perform numerical computing or create multi-dimensional arrays	NumPy's np.zeros()	np.zeros((2, 3))

By understanding these methods and their specific use cases—especially the critical distinction for mutable objects—you can choose the most appropriate and safest way to initialize lists in your Python projects.