Python `map()` and `filter()`

Overview

Both return a special iterable object (not a list directly) — convert with list() if needed.

map()

Applies a function to every element of an iterable and returns a new iterable with the transformed values.

Syntax

map(function, iterable)

Basic Example — squaring values

lst = [1, 2, 3, 4, 5]
new_lst = list(map(lambda x: x ** 2, lst))
print(new_lst)   # [1, 4, 9, 16, 25]

Using a named function instead of lambda

def square(x):
    return x ** 2

new_lst = list(map(square, lst))

Other examples

import math

# Square roots
list(map(lambda x: math.sqrt(x), [1, 4, 9, 16]))   # [1.0, 2.0, 3.0, 4.0]

# Sum of nested lists
lst = [[1, 2, 3], [4, 5, 6], [3, 3], [3, 4]]
list(map(lambda x: sum(x), lst))   # [6, 15, 6, 7]

The map object

result = map(lambda x: x ** 2, lst)
print(result)          # <map object at 0x...>  — not a list yet
print(list(result))    # [1, 4, 9, 16, 25]

# Can also loop through it directly without converting
for el in result:
    print(el)

filter()

Keeps only elements for which the function returns True.

Syntax

filter(function, iterable)

Basic Example — keep nested lists with sum > 6

lst = [[1, 2, 3], [4, 5, 6], [3, 3], [3, 4]]
new_lst = list(filter(lambda x: sum(x) > 6, lst))
print(new_lst)   # [[4, 5, 6], [3, 4]]

Other examples

# Keep lists with more than 2 elements
list(filter(lambda x: len(x) > 2, lst))   # [[1, 2, 3], [4, 5, 6]]

# Return True → keep all items
list(filter(lambda x: True, lst))    # all items kept

# Return False → keep nothing
list(filter(lambda x: False, lst))   # []

The filter object

result = filter(lambda x: sum(x) > 6, lst)
print(result)          # <filter object at 0x...>
print(list(result))    # [[4, 5, 6], [3, 4]]

Using map() and filter() Together

Pass the result of map() directly into filter() (or vice versa):

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

# Step 1: map each sublist to its sum  →  [6, 15, 6, 7]
# Step 2: filter to keep only even sums  →  [6, 6]

new_lst = list(filter(
    lambda y: y % 2 == 0,
    map(lambda x: sum(x), lst)
))

print(new_lst)   # [6, 6]

Step-by-step walkthrough: 1. map produces sums: [6, 15, 6, 7] 2. filter keeps only even values: 6 % 2 == 0 ✅, 15 % 2 == 0 ❌, 6 % 2 == 0 ✅, 7 % 2 == 0 ❌ 3. Result: [6, 6]

Key Takeaways & Recap