Python Lists

Learn how to create, access, and manipulate lists in Python.

Lists

Lists are used to store multiple items in a single variable.

Lists are one of 4 built-in data types in Python used to store collections of data, the other 3 are Tuple, Set, and Dictionary, all with different qualities and usage.

Lists are created using square brackets:

Example

thislist = ["apple", "banana", "cherry"]
print(thislist)

List Items

List items are ordered, changeable, and allow duplicate values.

List items are indexed, the first item has index [0], the second item has index [1] etc.

Ordered

When we say that lists are ordered, it means that the items have a defined order, and that order will not change.

If you add new items to a list, the new items will be placed at the end of the list.

Changeable

The list is changeable, meaning that we can change, add, and remove items in a list after it has been created.

Allow Duplicates

Since lists are indexed, lists can have items with the same value:

Example

thislist = ["apple", "banana", "cherry", "apple", "cherry"]
print(thislist)

List Length

To determine how many items a list has, use the len() function:

Example

thislist = ["apple", "banana", "cherry"]
print(len(thislist))

List Items - Data Types

List items can be of any data type:

Example

list1 = ["apple", "banana", "cherry"]
list2 = [1, 5, 7, 9, 3]
list3 = [True, False, False]

A list can contain different data types:

Example

list1 = ["abc", 34, True, 40, "male"]

type()

From Python's perspective, lists are defined as objects with the data type 'list':

Example

mylist = ["apple", "banana", "cherry"]
print(type(mylist))

The list() Constructor

It is also possible to use the list() constructor when creating a new list.

Example

thislist = list(("apple", "banana", "cherry")) # note the double round-brackets
print(thislist)

Access List Items

List items are indexed and you can access them by referring to the index number:

Example

thislist = ["apple", "banana", "cherry"]
print(thislist[1])

Negative Indexing

Negative indexing means start from the end

-1 refers to the last item, -2 refers to the second last item etc.

Example

thislist = ["apple", "banana", "cherry"]
print(thislist[-1])

Range of Indexes

You can specify a range of indexes by specifying where to start and where to end the range.

When specifying a range, the return value will be a new list with the specified items.

Example

thislist = ["apple", "banana", "cherry", "orange", "kiwi", "melon", "mango"]
print(thislist[2:5])

Change List Items

To change the value of a specific item, refer to the index number:

Example

thislist = ["apple", "banana", "cherry"]
thislist[1] = "blackcurrant"
print(thislist)

Change a Range of Item Values

To change the value of items within a specific range, define a list with the new values, and refer to the range of index numbers where you want to insert the new values:

Example

thislist = ["apple", "banana", "cherry", "orange", "kiwi", "mango"]
thislist[1:3] = ["blackcurrant", "watermelon"]
print(thislist)

Add List Items

Append Items

To add an item to the end of the list, use the append() method:

Example

thislist = ["apple", "banana", "cherry"]
thislist.append("orange")
print(thislist)

Insert Items

To insert a list item at a specified index, use the insert() method.

Example

thislist = ["apple", "banana", "cherry"]
thislist.insert(1, "orange")
print(thislist)

Extend List

To append elements from another list to the current list, use the extend() method.

Example

thislist = ["apple", "banana", "cherry"]
tropical = ["mango", "pineapple", "papaya"]
thislist.extend(tropical)
print(thislist)

Remove List Items

Remove Specified Item

The remove() method removes the specified item.

Example

thislist = ["apple", "banana", "cherry"]
thislist.remove("banana")
print(thislist)

Remove Specified Index

The pop() method removes the specified index.

Example

thislist = ["apple", "banana", "cherry"]
thislist.pop(1)
print(thislist)

If you do not specify the index, the pop() method removes the last item.

Example

thislist = ["apple", "banana", "cherry"]
thislist.pop()
print(thislist)

The del keyword

The del keyword also removes the specified index:

Example

thislist = ["apple", "banana", "cherry"]
del thislist[0]
print(thislist)

The del keyword can also delete the list completely.

Example

thislist = ["apple", "banana", "cherry"]
del thislist

Clear the List

The clear() method empties the list. The list still remains, but it has no content.

Example

thislist = ["apple", "banana", "cherry"]
thislist.clear()
print(thislist)

List Comprehensions

A comprehension builds a list in one readable line — the Pythonic replacement for many for + append loops.

squares = [x ** 2 for x in range(5)]       # [0, 1, 4, 9, 16]
evens   = [x for x in range(10) if x % 2 == 0]   # [0, 2, 4, 6, 8]
upper   = [w.upper() for w in ["a", "b"]]  # ['A', 'B']

Common Methods

MethodDoesTime
append(x)Add to endO(1)
insert(i, x)Insert at indexO(n)
pop() / pop(i)Remove & returnO(1) / O(n)
remove(x)Delete first matchO(n)
sort()Sort in placeO(n log n)
reverse()Reverse in placeO(n)

sort() returns None (it sorts in place). Use sorted(mylist) when you want a new sorted list and keep the original.

Copying a List

a = [1, 2, 3]
b = a            # alias -> changes to b affect a
c = a[:]         # shallow copy (or a.copy())
c.append(4)
print(a)         # [1, 2, 3]  -> unaffected

Try It Yourself

Exercise 1: Build a list of the cubes of 1–5 using a comprehension.

Show solution
print([x ** 3 for x in range(1, 6)])   # [1, 8, 27, 64, 125]

Exercise 2: From [3, 1, 2] produce a NEW sorted list without changing the original.

Show solution
nums = [3, 1, 2]
print(sorted(nums))   # [1, 2, 3]
print(nums)           # [3, 1, 2]  -> unchanged

Exercise 3: Remove duplicates from [1, 2, 2, 3, 3, 3] while keeping it a list.

Show solution
print(list(set([1, 2, 2, 3, 3, 3])))   # [1, 2, 3] (order may vary)

Key Takeaways

  • Lists are ordered, mutable, and allow duplicates.
  • Comprehensions replace many loops in one clear line.
  • sort() mutates and returns None; sorted() returns a new list.
  • Copy with [:] or .copy() to avoid aliasing.
← Previous: OperatorsNext: Access List Items →

📘 Real-World Deep Dive

Lists are Python's default ordered, mutable, heterogeneous collection. You reach for them so often that list-fluency (iteration, comprehensions, slicing, mutating methods) is the single biggest speed-up on daily coding tasks.

Real-Life Scenario

A shopping cart with line items — constant mutation (add/remove/update), ordering preserved, and frequent iteration to compute the total.

Real-Life Example

from dataclasses import dataclass, field
from typing import Iterable

@dataclass
class LineItem:
    sku: str
    qty: int
    price: float

@dataclass
class Cart:
    items: list[LineItem] = field(default_factory=list)
    currency: str = "USD"

    def add(self, sku: str, qty: int, price: float) -> None:
        existing = next((it for it in self.items if it.sku == sku), None)
        if existing:
            existing.qty += qty
        else:
            self.items.append(LineItem(sku, qty, price))

    def remove(self, sku: str) -> None:
        self.items[:] = [it for it in self.items if it.sku != sku]

    def subtotal(self, tax_rate: float = 0.0) -> float:
        raw = sum(it.qty * it.price for it in self.items)
        return round(raw * (1 + tax_rate), 2)

cart = Cart()
for sku, qty, price in [("SKU-1", 2, 9.99), ("SKU-2", 1, 24.50), ("SKU-1", 1, 9.99)]:
    cart.add(sku, qty, price)
cart.remove("SKU-2")
print("lines     :", len(cart.items))
print("subtotal  :", cart.subtotal(tax_rate=0.0875))
print("most-expensive:", max(cart.items, key=lambda it: it.price * it.qty))

Expected Output

lines     : 1
subtotal  : 32.83
most-expensive: LineItem(sku='SKU-1', qty=3, price=9.99)

Common mistakes

  • Mutating a list while iterating it skips or repeats elements — iterate over a copy (for x in xs[:]) or build a new list.
  • Using lst = lst + [...] creates a brand-new list every call (O(n)); use lst.append or lst.extend for hot loops.
  • A list passed to a function keeps living if the function mutates it — defensively copy with list(xs) or use a tuple.

🚀 Performance & Best Practices

  • collections.deque beats list for left-end pop/append (O(1) vs O(n)).
  • Search inside a list is O(n); wrap the membership check in a set for big collections.
  • "".join(parts) is far faster than += for building long strings from a list of fragments.

🧪 Try It Yourself

  1. Add a discount_codes: dict[str, float] field to Cart and apply the largest one that applies.
  2. Replace remove with a "soft delete" that hides items behind a flag and writes them to removed_history.
  3. Profile subtotal() with 1 M line items and time list-sum vs. math.fsum.

FAQ: Python Lists

Common questions about this page.

What is Python Lists?

Python Lists is a Python Tutorial lesson that explains python lists in Python. Learn how to create, access, and manipulate lists in Python. Copy the samples and run them in the Python editor. It is written for beginners who want a clear definition and working examples.

Should I run python lists examples locally for better learning?

Yes. Use the browser editor on StudyGrid for a quick check, then Download the example and run it on your computer. Local runs show real errors and the real toolchain, which is one of the fastest ways to learn python lists in this Python Tutorial Python lesson (Python Lists).

How do I use python lists in Python?

To use python lists in Python, follow the examples on this StudyGrid page. Copy a snippet, run it in the browser, then Download and run it locally for better learning. Change the values and compare the output.

What is the syntax of python lists?

This Python Lists tutorial shows python lists syntax with short Python examples. Use the code blocks in this lesson for the exact statements, then try them in your editor.

Python Lists example for beginners

Yes. This page includes a beginner python lists example you can copy and run. It is designed for searches such as "python lists for beginners", "python lists example", and "how to use python lists".

What are common mistakes with python lists?

Common python lists mistakes include wrong syntax, mixing types, and skipping practice. Work through this Python Tutorial chapter in order, run every example, and check the output before moving on.

Why should I learn python lists?

Python Lists is used in real Python work. Learning python lists helps you write clearer programs and continue the Python Tutorial tutorial on StudyGrid.

Is Python Lists free to learn online?

Yes. You can learn python lists free on StudyGrid (studygrid.in). This chapter is part of the Python Tutorial path and includes examples, syntax, and next-step links.