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# Combine filter() and map()

**00:00**
In this lesson, you’ll be learning what the `map()`

function does and how you can combine it with `filter()`

. The `map()`

function is a Python built-in function, which means you can use it right away without the need to import any libraries to use it.

**00:17**
The `map()`

function is used when you need to apply a function to each element of an iterable object and generate a new iterable with the results.

**00:27**
If this sounds a bit abstract, don’t worry. You’ll be using `map()`

shortly.

**00:34**
The `map()`

function takes in two arguments, `function`

and `iterable`

. In the `map()`

function, you pass in a function that will be applied to each element of the iterable.

**00:46**
And as a reminder, an iterable is any object that can be looped over, such as a list, a tuple, or a string. In the `map()`

function, you pass an `iterable`

object that will have the function applied to each of its elements.

**01:02**
Let’s explore an example where you’ll use `map()`

to square all the numbers inside of a list. In this example, you’ll use `map()`

to square all the numbers inside of a list.

**01:15**
`numbers = [1, 2, 3, 4, 5]`

.

**01:22**
Now what you are trying to do is to square all these numbers. To do that, you’ll need a function. Let’s name this function `square()`

. It should take a number as an input, and it should return the square of this number. Thankfully, Python has a built-in operator for exponentiation, which is `**`

, so `number ** 2`

is `number`

to the power of `2`

.

**01:49**
Then it’s time to use `map()`

to apply the `square()`

function you just created to each number in the `numbers`

list. As a reminder, `map()`

returns an iterator object, so you’ll need to call the `list()`

function on the result to be able to see it.

**02:05**
Let’s store the results in a variable named `squares`

. `list(map())`

. As its function argument, let’s put in `square`

—of course, here you need a function object, not a function call, so no parentheses—and `numbers`

as its iterable.

**02:29**
You get `1`

, `4`

, `9`

, `16`

, and `25`

, which are `1`

, `2`

, `3`

, `4`

, and `5`

squared. You did it.

**02:38**
What happened here is that the `map()`

function applied the `square()`

function to every single number in `numbers`

. For example, it put in `2`

from the `numbers`

list inside of the `square()`

function, and `2`

to the power of `2`

is `4`

, so the `square()`

function returned `4`

, and `map()`

stored it.

**02:55**
This happened to every single number in the `numbers`

list.

**03:03**
Great, now you know how the `map()`

function works and how you can use it to square every number of a list. It’s time to explore how you can combine `map()`

with `filter()`

.

**03:14**
Your goal is extracting the even numbers of an iterable using `filter()`

and then squaring them all using `map()`

.

**03:24**
Let’s start by creating a list of integers and naming it `numbers`

. `numbers = [1, 3, 10, 45, 6, 50]`

.

**03:37**
Next, let’s extract the even numbers of this list using `filter()`

. You’ve done this a couple of times by now. For the predicate function, let’s create a function named `is_even`

, which checks whether a number is even or not by computing is remainder when you divide it by two.

**03:55**
def `is_even()`

, `number`

as an input, `return`

`number % 2 == 0`

. So `is_even()`

will return `True`

if `number % 2`

is `0`

.

**04:10**
Or, in other words, when you divide `number`

by `2`

, it doesn’t have any remainders.

**04:16**
Now it’s time to use the `filter()`

function with `is_even`

as its predicate function and `numbers`

as its iterable argument and store its results in a list named `even_numbers`

.

**04:28**
`even_numbers = list(filter())`

, `is_even`

as the predicate function and `numbers`

as the iterable. Let’s see the results. `10`

, `6`

, and `50`

, so it means you filtered out the odd numbers, `1`

, `3`

, and `45`

. It worked. Now that you have your even numbers, it’s time for the interesting part: combining all of this with `map()`

.

**04:57**
In the first example that you used `map()`

to square all the numbers inside of a list, you created a function named `square()`

to take in a number and then return the square of it. Here, let’s try a lambda function as map’s function argument that does the same, and make sure you’re converting the results into a list.

**05:18**
`list(map)`

. As map’s function argument, let’s create a lambda function that takes in a number and then squares it. `lambda`

keyword, `n`

as an input and for the `return`

statement, `n ** 2`

, or `n`

the power of `2`

.

**05:36**
And as map’s iterable argument, let’s put in `even_numbers`

.

**05:41**
What you expect to happen here is that all the even numbers—`10`

, `6`

, and `50`

—to be squared. So you expect `100`

, `36`

, and `2500`

.

**05:54**
Let’s see if it worked. And it did. The result is a list: `100`

, which is `10`

squared; `36`

, which is the square of `6`

; and `2500`

, which is the square of `50`

.

**06:09**
So far, you’ve used `filter()`

to filter out the odd numbers, which you stored in a variable named `even_numbers`

, and then you used `map()`

to apply a lambda function to each number in `even_numbers`

and squared them all, but this looks a bit long, right?

**06:26**
How do you think you can make this code shorter? Since the results of `filter()`

is an iterator itself, you can just directly use it as map’s iterable argument instead of `even_numbers`

.

**06:38**
Let’s do that right now. `list(map())`

. As the function argument for `map()`

, let’s reuse the same lambda function to square each input number.

**06:50**
Now, as the iterable argument for `map()`

, let’s just directly use `filter()`

. `filter()`

, `is_even`

as the predicate function, and `numbers`

as the iterable you’re filtering odd numbers from. Everything stayed the same, but instead of creating a new list, like `even_numbers`

, you’re directly using filter’s results as map’s iterator argument.

**07:14**
Let’s see the results. It remained the same: `100`

, `36`

, and `2500`

, which are `10`

, `6`

, and `50`

squared, just like you wanted, but this time you did it with a one-liner.

**07:27**
What’s happening here is that the `filter()`

function filters out the odd numbers of `numbers`

and keeps the even numbers `10`

, `6`

, and `50`

.

**07:37**
Then `map()`

is applying the lambda function on every number in the iterator that’s made by filter, so it takes `10`

, squares it, takes `6`

, squares it, and then takes `50`

and squares it.

**07:50**
That’s why you got `100`

, `36`

, and `2500`

.

**07:55**
Congrats, you just learned how to combine `map()`

and `filter()`

!

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