How to Filter a List in Python

Filtering a list means keeping only the items that match a rule.

For example, you might want to:

• keep only even numbers
• keep only names longer than 4 letters
• remove empty strings
• keep only dictionaries where age >= 18

In Python, the most common way to do this is with a list comprehension. You can also use the built-in filter() function.

Quick answer #

numbers = [1, 2, 3, 4, 5, 6]
even_numbers = [n for n in numbers if n % 2 == 0]
print(even_numbers)
# Output: [2, 4, 6]

Use a list comprehension when you want to build a new list by keeping only items that match a condition.

What filtering a list means #

Filtering means:

• keeping some items
• leaving out other items
• creating a new list based on a condition

For example, if you only want numbers greater than 10, you check each item and keep the ones that match.

In most cases, the original list stays unchanged.

numbers = [5, 12, 8, 20]
filtered = [n for n in numbers if n > 10]

print(numbers)
print(filtered)

Output:

[5, 12, 8, 20]
[12, 20]

If you need a refresher on lists first, see Python lists explained for beginners.

Filter a list with a list comprehension #

A list comprehension is the most common Python way to filter a list.

The basic pattern is:

[item for item in items if condition]

Here:

• item is the current value
• items is the original list
• if condition decides whether the item is kept

Example: keep only even numbers.

numbers = [1, 2, 3, 4, 5, 6]
even_numbers = [n for n in numbers if n % 2 == 0]

print(even_numbers)

Output:

[2, 4, 6]

How this works #

Python checks each number one by one:

• 1 % 2 == 0 → False → leave it out
• 2 % 2 == 0 → True → keep it
• 3 % 2 == 0 → False → leave it out

If you want more practice with this syntax, see how to use list comprehensions in Python.

Filter strings from a list #

You can also filter text values.

Keep names longer than 4 letters #

names = ["Sam", "Olivia", "Liam", "Emily", "Noah"]
long_names = [name for name in names if len(name) > 4]

print(long_names)

Output:

['Olivia', 'Emily']

The condition is len(name) > 4, so only names with more than 4 letters are kept.

Keep words starting with a specific letter #

words = ["apple", "banana", "avocado", "grape"]
a_words = [word for word in words if word.startswith("a")]

print(a_words)

Output:

['apple', 'avocado']

Here, startswith("a") checks each word one by one.

Filter a list with filter() #

Python also has a built-in function called filter().

It needs:

• a function that returns True or False
• a list or other iterable to check

Example:

numbers = [1, 2, 3, 4, 5, 6]

def is_even(n):
    return n % 2 == 0

result = filter(is_even, numbers)
even_numbers = list(result)

print(even_numbers)

Output:

[2, 4, 6]

Important: filter() does not return a list #

filter() returns a filter object, not a normal list.

That is why beginners usually wrap it with list():

numbers = [1, 2, 3, 4]
result = filter(lambda n: n > 2, numbers)

print(result)
print(list(result))

Possible output:

<filter object at 0x...>
[3, 4]

For simple cases, list comprehensions are usually easier to read. If you want to learn more about this built-in function, see the Python filter() function explained.

Filter out empty values #

A very common task is removing empty strings.

items = ["", "apple", "", "banana", "orange", ""]
filtered = [item for item in items if item]

print(filtered)

Output:

['apple', 'banana', 'orange']

Why if item works #

In Python:

• an empty string "" is treated as False
• a non-empty string like "apple" is treated as True

So if item keeps only the non-empty values.

You can do the same with filter():

items = ["", "apple", "", "banana"]
filtered = list(filter(None, items))

print(filtered)

Output:

['apple', 'banana']

This is short and useful, but the list comprehension version is often easier for beginners to understand.

Filter a list of dictionaries #

Filtering a list of dictionaries is also common.

Example: keep only people who are age 18 or older.

people = [
    {"name": "Anna", "age": 17},
    {"name": "Ben", "age": 21},
    {"name": "Cara", "age": 18}
]

adults = [person for person in people if person["age"] >= 18]

print(adults)

Output:

[{'name': 'Ben', 'age': 21}, {'name': 'Cara', 'age': 18}]

How it works #

Inside the condition, person["age"] gets the age value from each dictionary.

If that value is 18 or more, the dictionary is kept.

Watch out for missing keys #

This will fail if one dictionary does not have an "age" key.

people = [
    {"name": "Anna", "age": 17},
    {"name": "Ben"},
    {"name": "Cara", "age": 18}
]

adults = [person for person in people if person["age"] >= 18]

This raises a KeyError.

A safer version uses .get():

people = [
    {"name": "Anna", "age": 17},
    {"name": "Ben"},
    {"name": "Cara", "age": 18}
]

adults = [person for person in people if person.get("age", 0) >= 18]

print(adults)

Output:

[{'name': 'Cara', 'age': 18}]

If you run into this problem, see KeyError in Python: causes and fixes.

Common beginner mistakes when filtering #

Here are some common problems beginners run into.

Expecting the original list to change #

Filtering usually creates a new list.

numbers = [1, 2, 3, 4]
filtered = [n for n in numbers if n > 2]

print(numbers)   # original list
print(filtered)  # new filtered list

Using = instead of == #

Use == when comparing values.

Wrong:

# This is invalid Python
# [n for n in numbers if n = 2]

Correct:

numbers = [1, 2, 3, 2]
twos = [n for n in numbers if n == 2]

print(twos)

Output:

[2, 2]

Forgetting that filter() returns an iterable #

This can be confusing:

numbers = [1, 2, 3, 4]
result = filter(lambda n: n > 2, numbers)

print(type(result))

Output:

<class 'filter'>

If you want a list, convert it:

filtered = list(result)
print(filtered)

Writing a condition that does not behave as expected #

Sometimes the condition is not checking what you think it is.

For example:

numbers = [0, 1, 2, 3]
filtered = [n for n in numbers if n]

print(filtered)

Output:

[1, 2, 3]

This removes 0 because 0 is treated as False in Python.

Removing items from a list while looping over it #

This often causes skipped values or unexpected results.

Avoid this:

numbers = [1, 2, 3, 4, 5]

for n in numbers:
    if n % 2 == 0:
        numbers.remove(n)

print(numbers)

Instead, create a new filtered list:

numbers = [1, 2, 3, 4, 5]
odd_numbers = [n for n in numbers if n % 2 != 0]

print(odd_numbers)

If you are practicing list loops, see how to loop through a list in Python.

When to use each approach #

Use a list comprehension when:

• the condition is simple
• you want the result as a list
• you want code that is easy to read

Use filter() when:

• you already have a function that checks each item
• you want to reuse that function
• the code reads clearly with that function

In general:

• choose the version that is easiest to understand
• avoid very complex one-line conditions
• prefer readability over clever code

FAQ #

Does filtering change the original list? #

Usually no. Most filtering examples create a new list and leave the original list unchanged.

Should I use list comprehension or filter()? #

For beginners, list comprehensions are usually easier to read and more common in everyday Python code.

Can I filter numbers, strings, and dictionaries? #

Yes. You can filter any list as long as you can write a condition that checks each item.

Why does filter() not print a normal list? #

Because filter() returns a filter object. Wrap it in list() if you want a list.

See also #

• Python lists explained for beginners
• How to check if a value exists in a list in Python
• How to loop through a list in Python
• How to use list comprehensions in Python
• Python filter() function explained
• KeyError in Python: causes and fixes