Python by Example: Map and Filter

map() applies a function to every element of an iterable; filter() keeps only elements for which a function returns True. Both return iterators—wrap them in list() to materialize the result. List comprehensions often read more clearly, but map and filter appear frequently in existing Python code.

What you'll learn:

• map() to transform elements
• filter() to select elements
• Equivalent list comprehensions

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

doubled = list(map(lambda x: x * 2, numbers))
print(doubled)

evens = list(filter(lambda x: x % 2 == 0, numbers))
print(evens)


def square(x):
    return x ** 2


print(list(map(square, numbers)))

# Equivalent list comprehensions
print([x * 2 for x in numbers])
print([x for x in numbers if x % 2 == 0])

map(f, iterable) is equivalent to (f(x) for x in iterable). filter(f, iterable) is equivalent to (x for x in iterable if f(x)). Named functions work just as well as lambdas.

To run this program:

$ python source/map-and-filter.py
[2, 4, 6, 8, 10]
[2, 4]
[1, 4, 9, 16, 25]
[2, 4, 6, 8, 10]
[2, 4]

Tip: Prefer list comprehensions when the logic is simple—they're more readable. Use map/filter when you already have a named function and don't want to repeat it in a comprehension.

Try it: Use map() to convert a list of strings to integers.

Source: map-and-filter.py

Next: Closures