Python filter function (Filters each item in a sequence)

filter function filters each element of an iterable (such as lists or strings) based on a function passed as an argument to the filter function.

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Using filter() function, you can take a list and apply a filtering function (such as if x < y^2 True).

In this case, you will end up with a filtered list that only has values that pass your criteria.

This is particularly useful when you match it up with other functions such as map(). By doing that, you can apply functions to each item in a sequence based on a filtering criteria.

I.e.: Imagine a Python dictionary of animals going extinct with remaining amounts in the wild. You can by combining map and filter you can end up with a dictionary which divides these values by half only if the animal number is below 1000 to start with. Latter part of the sentence is achieved by using filter function.

We have plenty of exercises to make this concept clear for you and help you understand it better below.

Used Where?

filter function allows filtering items based on a criteria passed as argument. It often comes very handy.

The fact that you can pass any logical function as an argument creates a high freedom of applications.

You might want to filter your elements based on, but not limited to, below criteria:

  • length of the items
  • Numerical value
    • above zero
    • below zero
    • odd number
    • even number
    • division remainder equals zero
    • absolute value
    • etc.
  • includes certain letter or not
  • alphabetic order
  • reverse alphabetic order

Syntax do(s)

1) inside filter function's parenthesis type your function followed by a comma

2) then the name of a list, tuple, dictionary or string i.e.: filter(f, iterable)

Syntax don't(s)

1) Don't print filter function directly, you will only get a unique memory address

2) Don't forget to put your filter function inside a list() function if you'd like to create meaningful results that are readable by the user.

Example 1: Positive numbers

>>> a = lambda x: x>=0
>>> lst = [-3, 4, 71, -555, -0.02, 0]
>>> lst_filtered = filter(a, lst)
>>> print(list(lst_filtered))

[4, 71, 0]

  • We created a function with lambda and logical expression: greater or equal (<=) and assigned to letter a.
  • We passed our function to the filter() function
  • Using list() function we converted our result to a readable list.

Example 2:

>>> a = lambda x: print(x*3)
>>> print(a(3))


Example 3: Even numbers

Let’s create a function that checks for even numbers and then use it in filter() function.

>>> a = lambda x: x%2==0
>>> lst = [75, 4, 55, 65, 22]
>>> lst = filter(a, lst)
>>> print(list(lst))

[4, 22]

This time we assigned the filtered result to the original list named <lst>

Example 4: Odd numbers

Let’s create a function that checks for odd numbers this time and then apply it to filter() function.

>>> a = lambda x: x%2==1
>>> lst = [75, 4, 55, 65, 22]
>>> lst = filter(a, lst)
>>> print(list(lst))

[75, 55, 65]

Printing the function object

You might at some point encounter a strange output when you’re learning Python. This happens when you try to print function objects directly without without calling it with any value.

What you get will be the id of your function as a memory address rather than any meaningful value to the user.

Example 5: Any vowels?

>>> t = “Winter Olympics”
>>> a = lambda x: True if x in “a,e,i,o,u,A,E,I,O,U” else False

>>> t_filtered = list(filter(a, t))
>>> print(t_filtered)

[‘i’, ‘e’, ‘O’, ‘i’]

You can filter all the vowels in a text.

Example 6: Capital letters

>>> t = “Winter Olympics”
>>> a = lambda x: True if x.lower() in “a,e,i,o,u” else False

>>> t_filtered = list(filter(a, t))
>>> print(t_filtered)

[‘i’, ‘e’, ‘O’, ‘i’]

Here is a classier solution to the previous example’s capital letter problem. We have seen .lower() method for strings previously. By adding that to your variable you can check if lowercase versions of all the letters are in the list and filter them based on that.


1- Sometimes it can be confusing to understand functions with logical expressions vs functions that return a numerical value.

A function with logical expression as below, will return a True or False value based on the criteria and this is what the filter() function needs to filter its iterable’s (list or other) elements.:

a = lambda x: x>=0



Versus when we use the map() function, we generate functions that actually change the value of the given variable instead, for instance:

a = lambda x: x^2

input: a(5)
output: 25

Example 7:

.sort() is a list method that sorts the list’s elements directly.

>>> lst = [1, 5, 66, 7]
>>> lst.sort(key=lambda x: x)


if you’d like to use a function as an argument in .sort() you need to use it with “key=” keyword.

Advanced Concepts (Optional)

1- filter() and map() can have a completing relation.

If you’d like to map the elements of your list to specific values, but also only do this to the elements that pass the filter, you get filter() inside map().

This operation will give same results as map() inside filter(). We also have that version of this example at the end of map() function’s lesson here.

  • filter() function will produce your filtered iterable inside map() function as below:
  • map(function, iterable)
    • where function will be the mapping function
    • where iterable will be: filter(function, iterable)
      • where function will be logical expression criteria
      • and iterable will be the actual iterable list or other.

Let’s see an example.

Example 8: map with filter

Inside map() function, first part tells what function to map values to, second part is the iterable which is filtered with filter function.

>>> lst = [1, 4, 9, 11, 400]
>>> a = map(lambda x: x**2, filter(lambda x: x<10, lst))
>>> print(list(a))

[1, 16, 81]

  • When you’re using a filter, map or zip function as an iterable in a loop or another function you don’t have to use the list() function to make them look readable and pretty. You can directly iterate on them.

Next Lesson:

sorted() function


Joseph Wright

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