Using Python's filter() Function: Scenarios and Example Code

filter() is a built‑in higher‑order function in Python that filters elements of an iterable, keeping only those for which the provided function returns True . Unlike map() , filter() focuses on selecting data based on conditions rather than transforming it. Below are common usage scenarios and example code.

Usage scenarios

Data cleaning: remove entries that do not satisfy specific conditions.

Conditional filtering: filter list elements based on complex logic.

List deduplication (with lambda and set ): remove duplicate elements.

Find matches: locate all items that meet a particular condition.

Data preprocessing: filter out valid or required data before further analysis.

Preparation before pattern recognition: discard irrelevant data points prior to analysis.

Text processing: e.g., filter words that are all uppercase or contain specific characters.

Data validation: check which elements satisfy certain validation rules.

Computation optimization: exclude unnecessary elements before expensive operations.

Data slicing: split a large dataset into smaller parts that meet specific criteria.

Example code

1. Filter even numbers

numbers = [1, 2, 3, 4, 5, 6]
even_numbers = list(filter(lambda x: x % 2 == 0, numbers))
print(even_numbers)  # 输出: [2, 4, 6]

2. Filter elements greater than 10

data = [5, 15, 20, 3, 7]
greater_than_ten = list(filter(lambda x: x > 10, data))
print(greater_than_ten)  # 输出: [15, 20]

3. Filter non‑empty strings

strings = ["apple", "", "banana", " ", "cherry"]
non_empty_strings = list(filter(None, strings))  # or use lambda x: bool(x) and strip()
print(non_empty_strings)  # 输出: ['apple', 'banana', ' ', 'cherry']

4. Filter words with length greater than 5

words = ["hello", "world", "python", "code"]
long_words = list(filter(lambda w: len(w) > 5, words))
print(long_words)  # 输出: ['python']

5. Filter prime numbers

from math import isqrt
def is_prime(n):
if n < 2:
return False
for i in range(2, isqrt(n) + 1):
if n % i == 0:
return False
return True
numbers = [2, 3, 4, 5, 6, 7, 8, 9, 10]
primes = list(filter(is_prime, numbers))
print(primes)  # 输出: [2, 3, 5, 7]

6. Deduplicate (using set and lambda)

items = [1, 2, 2, 3, 4, 4, 5]
unique_items = list(filter(lambda x: items.count(x) == 1, items))
print(unique_items)  # 注意：此方法效率不高，通常直接使用 set(items) 较好

7. Filter strings containing a specific substring

sentences = ["I love Python", "Python is fun", "Fun with C++"]
contains_python = list(filter(lambda s: "Python" in s, sentences))
print(contains_python)  # 输出: ['I love Python', 'Python is fun']

8. Filter positive numbers

mixed_numbers = [-2, 3, 0, -1, 4, -5]
positive_numbers = list(filter(lambda x: x > 0, mixed_numbers))
print(positive_numbers)  # 输出: [3, 4]

9. Filter words with a capitalized first letter

words_mixed_case = ["Apple", "banana", "Cherry", "date"]
capitalized_words = list(filter(lambda w: w[0].isupper(), words_mixed_case))
print(capitalized_words)  # 输出: ['Apple', 'Cherry']

10. Filter non‑empty dictionaries

dict_list = [{}, {'key': 'value'}, {}, {'another_key': 42}]
non_empty_dicts = list(filter(None, dict_list))  # 空字典在布尔上下文中为False
print(non_empty_dicts)  # 输出: [{'key': 'value'}, {'another_key': 42}]