Python Sorting Lists

In the last lesson you learned about Nested Lists. That is a list that holds other lists inside it. Now we have a different need. You have a list of items. You want them in order. Names from A to Z. Prices from low to high. Scores from high to low. Python gives you two clean ways to do that. This lesson shows you both.

🤔 Why Sort a List?

Picture a list of scores. You collected them one by one as players finished a game. They came in random order. Now you want a leaderboard with the highest score first. Reading through an unsorted list and putting it in order by hand is slow. It is also easy to get wrong.

Sorting fixes that. You hand Python the list. It puts the items in order for you. Python gives you two tools for this. The difference between them matters a lot.

⚖️ sort() vs sorted() — The Key Difference

Here is the one idea people most often get wrong. So let’s make it clear right away.

sort() is a method you call on the list. It changes the original list in place. It returns nothing.

sorted() is a built-in function. It leaves the original list untouched. It gives you back a brand new sorted list.

This small table makes the difference easy to remember.

Let’s see both side by side. This code sorts the same list two ways. You can watch what happens to the original.

scores = [50, 90, 30, 70]

# sort() changes scores itself and gives back nothing
result = scores.sort()
print("After sort():", scores)
print("sort() returned:", result)

# sorted() works on a fresh list so we can see the difference
ages = [50, 90, 30, 70]
new_list = sorted(ages)
print("sorted() returned:", new_list)
print("ages is unchanged:", ages)

After sort(): [30, 50, 70, 90]
sort() returned: None
sorted() returned: [30, 50, 70, 90]
ages is unchanged: [50, 90, 30, 70]

Walk through what each line did:

• scores.sort() reordered scores itself. Now scores is [30, 50, 70, 90].
• The value it gave back was None. That is why result printed as None.
• sorted(ages) built a new list and put it in new_list.
• ages stayed exactly as it was. sorted() never touches the original.

So which one do you use? If you are happy changing the list you have, use sort(). If you need to keep the original as it was and also have a sorted copy, use sorted().

⬆️ Ascending and Descending Order

By default both tools sort in ascending order. That means smallest to largest for numbers, and A to Z for text. Most of the time that is exactly what you want.

When you want the other direction, you add reverse=True. That flips it to descending. So largest first, or Z to A.

This example builds that leaderboard we talked about, with the highest score first.

scores = [50, 90, 30, 70]

scores.sort(reverse=True)
print("Leaderboard:", scores)

Leaderboard: [90, 70, 50, 30]

The same reverse=True works with sorted() too, when you want a new list instead.

prices = [12, 5, 20, 8]
highest_first = sorted(prices, reverse=True)

print("New sorted list:", highest_first)
print("Original prices:", prices)

New sorted list: [20, 12, 8, 5]
Original prices: [12, 5, 20, 8]

🔤 Sorting Numbers and Strings

Sorting numbers is easy. Python already knows that 30 comes before 50.

Strings sort in alphabetical order. Well, almost. Python actually sorts text by character codes. Every uppercase letter comes before every lowercase letter. So "Zoe" sorts before "alex". That surprises people the first time.

This example sorts a list of names. It shows that uppercase-first behavior.

names = ["Riya", "alex", "Arjun", "bina"]
print(sorted(names))

['Arjun', 'Riya', 'alex', 'bina']

See how both capitalized names landed first? If you want a sort that ignores case, you can tell Python to compare the lowercase version of each name. That is where a key function comes in, which is next.

🔑 Sorting with a key Function

Sometimes plain order is not what you want. Maybe you want the shortest word first. Or you want to sort people by their age, not their name. For that you pass a key.

A key is a function. Python runs it on each item. It sorts by whatever that function gives back. The items themselves stay the same. Only the comparison value changes.

Say you want words sorted by how long they are. You give key=len, because len returns the length of each word.

words = ["banana", "kiwi", "apple", "fig"]
words.sort(key=len)
print(words)

['fig', 'kiwi', 'apple', 'banana']

Python called len on every word. "fig" is 3 letters. "kiwi" is 4, and so on. So it ordered them shortest to longest.

For sorting by a field, a list of tuples is the common case. Imagine each tuple is a person as (name, age). You want them ordered youngest first. You point the key at the second item of each tuple.

people = [("Riya", 30), ("Arjun", 22), ("Alex", 27)]
people.sort(key=lambda person: person[1])

for name, age in people:
    print(f"{name} is {age}")

Arjun is 22
Alex is 27
Riya is 30

Here lambda person: person[1] is a tiny one-line function. It takes one person tuple and returns person[1], which is the age. So Python sorts the list by age. The names follow along with their ages. If you wanted oldest first, you would add reverse=True next to the key.

And remember that case-insensitive name sort from earlier? You fix it with key=str.lower, so Python compares everything in lowercase.

names = ["Riya", "alex", "Arjun", "bina"]
print(sorted(names, key=str.lower))

['alex', 'Arjun', 'bina', 'Riya']

⚠️ Common Mistakes

A few slip-ups come up again and again. Watch for these.

• Reassigning the result of sort(). It returns None, so you lose your data.

# ❌ Avoid: numbers becomes None
numbers = [3, 1, 2]
numbers = numbers.sort()

# ✅ Good: sort in place, then use numbers
numbers = [3, 1, 2]
numbers.sort()

• Calling the key function instead of passing it. Pass the name, do not add parentheses.

# ❌ Avoid: this calls len() with no argument and crashes
words.sort(key=len())

# ✅ Good: pass len itself, Python calls it for you
words.sort(key=len)

• Trying to sort mixed types like numbers and strings together. Python raises a TypeError. Keep the items the same kind.

✅ Best Practices

• Reach for sorted() when you still need the original list. Use sort() only when you truly want to change the list in place.
• Let key do the work for “sort by something”. Sort by length, by a field, or by lowercase, instead of rearranging the data yourself.
• Add reverse=True for descending order rather than sorting and then reversing the list by hand.
• Keep every item in the list the same type, so the comparison always makes sense.

🧩 What You’ve Learned

• ✅ sort() orders the list in place and returns None, while sorted() returns a new list and leaves the original alone.
• ✅ Both sort ascending by default, and reverse=True switches them to descending.
• ✅ Numbers sort by value, and strings sort alphabetically with uppercase letters coming before lowercase.
• ✅ A key function lets you sort by length, by a tuple field, or case-insensitively.
• ✅ Reassigning sort(), calling the key with parentheses, and mixing types are the usual mistakes to avoid.

🚀 What’s Next?

You now know how to put list items in order. Next we look at a tricky part of lists that surprises many people. It is how to make a real copy of a list instead of accidentally sharing the same one.

Copying Lists