List filtering
List filtering means creating a result that contains only the items that satisfy a condition.
Python list filtering exercises
Python list filtering exercises for keeping only the values that match.
Use this page when you want list-filtering practice specifically. The sequence starts with reading and counting lists, then moves into keeping even numbers, skipping blanks, transforming items, and preserving order.
Focused intent
Python list filtering exercises
Practice count
8 ordered exercises
Examples
Each prompt includes sample input and expected output
Next click
Open matching lessons or public teaser pages
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Reviewed educational content from PySchool.ai curriculum team
Long-tail practice clusters are curated from the public curriculum, lesson teaser pages, and topic hubs so learners can compare a focused sequence before opening an interactive exercise.
- Editorial owner
- PySchool.ai curriculum team
- Review scope
- Python practice cluster
- Last updated
- May 3, 2026
See the PySchool.ai editorial policy for how practice content is generated, reviewed, tested, and updated.
Direct answer
What is the best way to use Python list filtering exercises?
Python list filtering exercises ask you to loop through values and keep only the items that pass a condition. Beginners should first practice reading, counting, and summing lists, then build a new result list for filters. Good filters test empty lists, all-matching lists, no-matching lists, and repeated values.
Predicate
A predicate is a true-or-false condition used to decide whether an item belongs in the result.
Result list
A result list starts empty and collects matching items as the loop checks each value.
Best exercises
Best exercises to solve first
Common mistakes
Common mistakes to avoid
Modifying the same list while looping
Build a new list unless the task explicitly asks for in-place changes.
Appending outside the if statement
Append only when the item passes the filter condition.
Forgetting the no-match case
Return an empty list when no values pass the condition.
Learner questions
Quick answers for learners comparing practice paths
What is the easiest Python list filtering exercise?
Filtering even numbers is usually the easiest because each number either passes or fails one clear condition.
Should I use list comprehensions first?
Beginners should write the full loop first, then convert it to a list comprehension after the logic is clear.
What edge cases should I test for filters?
Test empty lists, lists where every item matches, and lists where no item matches.
How is filtering different from transforming?
Filtering decides which items to keep. Transforming changes each item into a new value.
Ordered practice
Solve these exercises in order.
This page is narrower than the broader python lists practice. It is built for learners who already know the topic they want to practice and need a concrete sequence with examples, expected output, and common mistakes before opening the editor.
1. Warmup - List traversal
Read each list item
Loop over every item before trying to keep or discard values.
Example
[4, 7, 10]
Expected output
4 7 10
Why it matters: Filtering starts with visiting every item reliably.
2. Warmup - Counting
Count list elements
Return how many values are present before adding a condition.
Example
[4, 7, 10]
Expected output
3
Why it matters: Counting proves the loop sees each value once.
3. Core - Modulo filter
Keep only even numbers
Return a new list containing only even numbers.
Example
[1, 2, 3, 4]
Expected output
[2, 4]
Why it matters: This is the core list-filtering pattern.
4. Core - Condition checks
Filter even numbers
Keep the numbers where number % 2 == 0.
Example
[8, 9, 10]
Expected output
[8, 10]
Why it matters: Repeating the same filter with new values strengthens the condition habit.
5. Core - Truthy text
Skip empty strings
Return only strings that are not empty.
Example
["py", "", "school"]
Expected output
["py", "school"]
Why it matters: Filtering text introduces blank values and exact output.
6. Core - Filter vs map
Transform each item in a list
Apply one operation to every item after you understand filtering.
Example
[1, 2, 3]
Expected output
[2, 4, 6]
Why it matters: Comparing filtering and transforming prevents mixing the two patterns.
7. Stretch - Seen set
Extract unique elements while keeping order
Return first appearances only, preserving order.
Example
[3, 1, 3, 2, 1]
Expected output
[3, 1, 2]
Why it matters: Uniqueness adds memory to the basic filter pattern.
8. Stretch - Scanning
Find maximum value
Track the best value seen while looping through the list.
Example
[5, 2, 9, 1]
Expected output
9
Why it matters: Scanning is a related list skill used before harder DSA.
Practice order
Suggested routine before moving on.
- 1. Loop through the list before writing any condition.
- 2. Create an empty result list before the loop.
- 3. Append only inside the condition that keeps an item.
- 4. Test empty, all-match, and no-match inputs before moving on.
Continue practicing
Use the broader hubs when this cluster feels comfortable.
Python lists practice
Practice indexing, scanning, filtering, transforming, and list edge cases.
Python loops practice
Practice loop patterns before moving into mixed collection problems.
Python practice hub
Use the main Python practice hub for beginner, topic, DSA, and interview paths.
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