List mutability in Python

Introduction

Lists can be changed after they are created. This helps us update, add, or remove items easily.

When you want to keep a collection of items that can change over time.

When you need to update a value in a list without making a new list.

When you want to add or remove items from a list during a program.

When you want to sort or reorder items in a list.

When you want to share a list between parts of a program and have changes seen everywhere.

Syntax

Python

my_list = [1, 2, 3]
my_list[0] = 10  # Change first item
my_list.append(4)  # Add new item
my_list.remove(2)  # Remove item with value 2

Lists use square brackets [] and can hold any type of items.

You can change items by their position (index) or use methods like append() and remove().

Examples

Start with an empty list and add one item.

Python

my_list = []
my_list.append(5)
print(my_list)

Change the only item in a list.

Python

my_list = [10]
my_list[0] = 20
print(my_list)

Change the last item in a list.

Python

my_list = [1, 2, 3]
my_list[2] = 30
print(my_list)

Remove an item by value.

Python

my_list = [1, 2, 3]
my_list.remove(2)
print(my_list)

Sample Program

This program shows how to change, add, and remove items in a list. It prints the list before and after each change.

Python

def print_list_state(description, some_list):
    print(f"{description}: {some_list}")

my_list = [5, 10, 15]
print_list_state("Original list", my_list)

# Change the first item
my_list[0] = 50
print_list_state("After changing first item", my_list)

# Add a new item
my_list.append(20)
print_list_state("After adding new item", my_list)

# Remove an item
my_list.remove(10)
print_list_state("After removing an item", my_list)

Important Notes

Changing an item by index is very fast (constant time).

Adding or removing items can take longer if the list is big.

Remember, if you assign a list to another variable, both variables point to the same list. Changing one changes the other.

Use list mutability when you want to update data without making a new list each time.

Summary

Lists can be changed after creation; this is called mutability.

You can update items by position, add new items, or remove items.

Mutability helps keep your program flexible and efficient.

Practice

1. Which of the following statements about Python lists is true?

easy

A. Lists cannot be changed once created.

B. Lists can be changed after they are created.

C. Lists are immutable like strings.

D. Lists can only store numbers.

Solution

1. Step 1: Understand list mutability

   Python lists are mutable, meaning you can change their contents after creation.

2. Step 2: Compare options

   Lists can be changed after they are created. ("Lists can be changed after they are created.") correctly states that lists are mutable. Options A and C incorrectly claim lists cannot be changed or are immutable like strings. Lists can only store numbers. is wrong because lists can store any data type.

3. Final Answer:

   Lists can be changed after they are created. -> Option B

4. Quick Check:

   List mutability = True [OK]

Hint: Remember: lists are like clay, easy to reshape [OK]

Common Mistakes:

• Confusing lists with strings (immutable)
• Thinking lists only hold numbers
• Believing lists cannot be changed

2. Which of the following is the correct way to change the first item of a list my_list to 10?

easy

A. my_list[0] = 10

B. my_list(0) = 10

C. my_list{0} = 10

D. my_list.set(0, 10)

Solution

1. Step 1: Recall list item assignment syntax

   In Python, list items are accessed and assigned using square brackets and index, like my_list[0].

2. Step 2: Check each option

   my_list[0] = 10 uses correct syntax. Options B and C use wrong brackets. my_list.set(0, 10) uses a method that does not exist for lists.

3. Final Answer:

   my_list[0] = 10 -> Option A

4. Quick Check:

   Use square brackets for list item assignment [OK]

Hint: Use square brackets [] to access or change list items [OK]

Common Mistakes:

• Using parentheses instead of brackets
• Trying to use curly braces for indexing
• Assuming lists have a set() method

3. What will be the output of this code?

numbers = [1, 2, 3]
numbers[1] = 5
print(numbers)

medium

A. [1, 5, 3]

B. [1, 2, 3]

C. [5, 2, 3]

D. Error

Solution

1. Step 1: Understand list item update

   The code changes the item at index 1 (second item) from 2 to 5.

2. Step 2: Check the final list

   After update, the list becomes [1, 5, 3]. The print statement outputs this list.

3. Final Answer:

   [1, 5, 3] -> Option A

4. Quick Check:

   Updated list = [1, 5, 3] [OK]

Hint: Index 1 means second item in list [OK]

Common Mistakes:

• Thinking index 1 is first item
• Expecting original list unchanged
• Assuming code causes error

4. Find the error in this code that tries to change a list item:

my_list = [10, 20, 30]
my_list(1) = 15
print(my_list)

medium

A. Missing colon after assignment

B. List cannot be changed after creation

C. Using parentheses instead of square brackets for indexing

D. print statement syntax error

Solution

1. Step 1: Identify indexing syntax error

   The code uses parentheses () instead of square brackets [] to access list item.

2. Step 2: Confirm correct syntax

   List items must be accessed with square brackets, so my_list[1] = 15 is correct.

3. Final Answer:

   Using parentheses instead of square brackets for indexing -> Option C

4. Quick Check:

   Use [] not () for list indexing [OK]

Hint: Remember: () calls functions, [] accesses list items [OK]

Common Mistakes:

• Using () instead of [] for list indexing
• Thinking lists are immutable
• Looking for syntax errors elsewhere

5. Given the list data = [5, 10, 15, 20], which code snippet correctly doubles each item in the list using mutability?

hard

A. data = [item * 2 for item in data]
print(data)

B. for item in data:
item = item * 2
print(data)

C. data.map(lambda x: x*2)
print(data)

D. for i in range(len(data)):
data[i] = data[i] * 2
print(data)

Solution

1. Step 1: Understand mutability and iteration

   To change items in place, we must assign new values to each index in the list.

2. Step 2: Analyze each option

   for i in range(len(data)): data[i] = data[i] * 2 print(data) updates each item by index, correctly doubling values in place.
   for item in data: item = item * 2 print(data) changes only the loop variable, not the list.
   data = [item * 2 for item in data] print(data) creates a new list and assigns it to data (not in-place mutation).
   data.map(lambda x: x*2) print(data) uses map which returns an iterator and does not modify list in place.

3. Final Answer:

   for i in range(len(data)): data[i] = data[i] * 2 print(data) -> Option D

4. Quick Check:

   In-place update requires index assignment [OK]

Hint: Use index to update list items for true mutability [OK]

Common Mistakes:

• Modifying loop variable instead of list items
• Using map without converting result
• Replacing list instead of mutating it