An Illustrated (and Musical) Guide to Map, Reduce, and Filter Array Methods

Map, reduce, and filter are three very useful array methods in JavaScript that give developers a ton of power in a short amount of space. Let’s jump right into how you can leverage (and remember how to use!) these super handy methods.

Array.map()

Array.map() updates each individual value in a given array based on a provided transformation and returns a new array of the same size. It accepts a callback function as an argument, which it uses to apply the transform.

let newArray = oldArray.map((value, index, array) => { ...
});

A mnemonic to remember this is MAP: Morph Array Piece-by-Piece.

Instead of a for-each loop to go through and apply this transformation to each value, you can use a map. This works when you want to preserve each value, but update it. We’re not potentially eliminating any values (like we would with a filter), or calculating a new output (like we would use reduce for). A map lets you morph an array piece-by-piece. Let’s take a look at an example:

[1, 4, 6, 14, 32, 78].map(val => val * 10)
// the result is: [10, 40, 60, 140, 320, 780]

In the above example, we take an initial array ([1, 4, 6, 14, 32, 78]) and map each value in it to be that value times ten (val * 10). The result is a new array with each value of the original array transformed by the equation: [10, 40, 60, 140, 320, 780].

An illustration of the code examples covered in this section.

Array.filter()

Array.filter() is a very handy shortcut when we have an array of values and want to filter those values into another array, where each value in the new array is a value that passes a specific test.

This works like a search filter. We’re filtering out values that pass the parameters we provide.

For example, if we have an array of numeric values, and want to filter them to just the values that are larger than 10, we could write:

[1, 4, 6, 14, 32, 78].filter(val => val > 10)
// the result is: [14, 32, 78]

If we were to use a map method on this array, such as in the example above, we would return an array of the same length as the original with val > 10 being the “transform,” or a test in this case. We transform each of the original values to their answer if they are greater than 10. It would look like this:

[1, 4, 6, 14, 32, 78].map(val => val > 10)
// the result is: [false, false, false, true, true, true]

A filter, however, returns only the true values. So the result is smaller than the original array or the same size if all values pass a specific test.

Think about filter like a strainer-type-of-filter. Some of the mix will pass through into the result, but some will be left behind and discarded.

An illustration of a funnel with numbers going in the top and a few coming out of the bottom next to a handwritten version of the code covered in this section.

Say we have a (very small) class of four dogs in obedience school. All of the dogs had challenges throughout obedience school and took a graded final exam. We’ll represent the doggies as an array of objects, i.e.:

const students = [ { name: "Boops", finalGrade: 80 }, { name: "Kitten", finalGrade: 45 }, { name: "Taco", finalGrade: 100 }, { name: "Lucy", finalGrade: 60 }
]

If the dogs get a score higher than 70 on their final test, they get a fancy certificate; and if they don’t, they’ll need to take the course again. In order to know how many certificates to print, we need to write a method that will return the dogs with passing grades. Instead of writing out a loop to test each object in the array, we can shorten our code with filter!

const passingDogs = students.filter((student) => { return student.finalGrade >= 70
}) /*
passingDogs = [ { name: "Boops", finalGrade: 80 }, { name: "Taco", finalGrade: 100 }
]
*/

As you can see, Boops and Taco are good dogs (actually, all dogs are good dogs), so Boops and Taco are getting certificates of achievement for passing the course! We can write this in a single line of code with our lovely implicit returns and then remove the parenthesis from our arrow function since we have single argument:

const passingDogs = students.filter(student => student.finalGrade >= 70) /*
passingDogs = [ { name: "Boops", finalGrade: 80 }, { name: "Taco", finalGrade: 100 }
]
*/

Array.reduce()

The reduce() method takes the input values of an array and returns a single value. This one is really interesting. Reduce accepts a callback function which consists of an accumulator (a value that accumulates each piece of the array, growing like a snowball), the value itself, and the index. It also takes a starting value as a second argument:

let finalVal = oldArray.reduce((accumulator, currentValue, currentIndex, array) => { ...
}), initalValue;
An illustration of a saucepan cooking ingredients next to handwritten code from the examples covered in this section.

Let’s set up a cook function and a list of ingredients:

// our list of ingredients in an array
const ingredients = ['wine', 'tomato', 'onion', 'mushroom'] // a cooking function
const cook = (ingredient) => { return `cooked ${ingredient}`
}

If we want to reduce the items into a sauce (pun absolutely intended), we’ll reduce them with reduce()!

const wineReduction = ingredients.reduce((sauce, item) => { return sauce += cook(item) + ', ' }, '') // wineReduction = "cooked wine, cooked tomato, cooked onion, cooked mushroom, "

That initial value ('' in our case) is important because if we don’t have it, we don’t cook the first item. It makes our output a little wonky, so it’s definitely something to watch out for. Here’s what I mean:

const wineReduction = ingredients.reduce((sauce, item) => { return sauce += cook(item) + ', ' }) // wineReduction = "winecooked tomato, cooked onion, cooked mushroom, "

Finally, to make sure we don’t have any excess spaces at the end of our new string, we can pass in the index and the array to apply our transformation:

const wineReduction = ingredients.reduce((sauce, item, index, array) => { sauce += cook(item) if (index < array.length - 1) { sauce += ', ' } return sauce }, '') // wineReduction = "cooked wine, cooked tomato, cooked onion, cooked mushroom"

Now we can write this even more concisely (in a single line!) using ternary operators, string templates, and implicit returns:

const wineReduction = ingredients.reduce((sauce, item, index, array) => { return (index < array.length - 1) ? sauce += `${cook(item)}, ` : sauce += `${cook(item)}`
}, '') // wineReduction = "cooked wine, cooked tomato, cooked onion, cooked mushroom"

A little way to remember this is to recall how you make sauce: you reduce a few ingredients down to a single item.

Sing it with me!

I wanted to end this blog post with a song, so I wrote a little diddy about array methods that might just help you to remember them:

The post An Illustrated (and Musical) Guide to Map, Reduce, and Filter Array Methods appeared first on CSS-Tricks.

Understanding the Almighty Reducer

I was recently mentoring someone who had trouble with the .reduce() method in JavaScript. Namely, how you get from this:

const nums = [1, 2, 3]
let value = 0 for (let i = 0; i < nums.length; i++) { value += nums[i]
}

…to this:

const nums = [1, 2, 3]
const value = nums.reduce((ac, next) => ac + next, 0)

They are functionally equivalent and they both sum up all the numbers in the array, but there is a bit of paradigm shift between them. Let’s explore reducers for a moment because they’re powerful, and important to have in your programming toolbox. There are literally hundreds of other articles on reducers out there, and I’ll link up some of my favorites at the end.

What is a reducer?

The first and most important thing to understand about a reducer is that it will always only return one value. The job of a reducer is to reduce. That one value can be a number, a string, an array or an object, but it will always only be one. Reducers are really great for a lot of things, but they’re especially useful for applying a bit of logic to a group of values and ending up with another single result.

That’s the other thing to mention: reducers will not, by their nature, mutate your initial value; rather they return something else. Let’s walk over that first example so you can see what’s happening here. The video below explains:

It might be helpful to watch the video to see how the progression occurs, but here’s the code we’re looking at:

const nums = [1, 2, 3]
let value = 0 for (let i = 0; i < nums.length; i++) { value += nums[i]
}

We have our array (1, 2, 3) and the first value each number in the array will be added to (0). We walk through the amount of the array and add them to the initial value.

Let’s try this a little differently:

const nums = [1, 2, 3]
const initialValue = 0 const reducer = function (acc, item) { return acc + item
} const total = nums.reduce(reducer, initialValue)

Now we have the same array, but this time we’re not mutating that first value. Instead, we have an initialValue that will only be used at the start. Next, we can make a function that takes an accumulator 
and an item. The accumulator is the collected value
 returned in the last invocation that informs the function what the next value will be added to. In this case of addition, you can think of it as a snowball rolling down a mountain that eats up each value in its path as it grows in size by every eaten value.

snowball accumulating values

We’ll use .reduce() to apply the function and start from that initial value. This can be shortened with an arrow function:

const nums = [1, 2, 3]
const initialValue = 0 const reducer = (acc, item) => { return acc + item
} const total = nums.reduce(reducer, initialValue)

And then shortened some more! Implicit returns for the win!

const nums = [1, 2, 3]
const initialValue = 0 const reducer = (acc, item) => acc + item const total = nums.reduce(reducer, initialValue)

Now we can apply the function right where we called it, and we can also plop that initial value directly in there!

const nums = [1, 2, 3] const total = nums.reduce((acc, item) => acc + item,

An accumulator can be an intimidating term, so you can think of it like the current state of the array as we’re applying the logic on the callback’s invocations.

The Call Stack

In case it’s not clear what’s happening, let’s log out what’s going on for each iteration. The reduce is using a callback function that will run for each item in the array. IThe following demo will help to make this more clear. I’ve also used a different array ([1, 3, 6]) because having the numbers be the same as the index could be confusing.

See the Pen showing acc, item, return by Sarah Drasner (@sdras) on CodePen.

When we run this, we’ll see this output in the console:

"Acc: 0, Item: 1, Return value: 1" "Acc: 1, Item: 3, Return value: 4" "Acc: 4, Item: 6, Return value: 10"

Here’s a more visual breakdown:

  1. It shows that the accumulator is starting at our initial value, 0
  2. Then we have the first item, which is 1, so our return value is 1 (0 + 1 = 1)
  3. 1 becomes the accumulator on the next invocation
  4. Now we have 1 as the accumulator and 3 is the item aince it is next in the array.
  5. The returned value becomes 4 (1 + 3 = 4)
  6. That, in turn, becomes the accumulator and the next item at invocation is 6
  7. That results in 10 (4 + 6 = 10) and is our final value since 6 is the last number in the array

Simple Examples

Now that we’ve got that under our belt, let’s look at some common and useful things reducers can do.

How many of X do we have?

Let’s say you have an array of numbers and you want to return an object that reports the number of times those numbers occur in the array. Note that this could just as easily apply to strings.

const nums = [3, 5, 6, 82, 1, 4, 3, 5, 82] const result = nums.reduce((tally, amt) => { tally[amt] ? tally[amt]++ : tally[amt] = 1 return tally
}, {}) console.log(result)

See the Pen simplified reduce by Sarah Drasner (@sdras) on CodePen.

Wait, what did we just do?

Initially, we have an array and the object we’re going to put its contents into. In our reducer, we ask: does this item exist? If so, let’s increment it. If not, add it and set it to 1. At the end, please return the tally count of each item. Then, we run the reduce function, passing in both the reducer and the initial value.

Take an array and turn it into an object that shows some conditions

Let’s say we have an array and we want to create an object based on a set of conditions. Reduce can be great for this! Here, we want to create an object out of any instance of a number contained in the array and show both an odd and even version of this number. If the number is already even or odd, then that’s what we’ll have in the object.

const nums = [3, 5, 6, 82, 1, 4, 3, 5, 82] // we're going to make an object from an even and odd
// version of each instance of a number
const result = nums.reduce((acc, item) => { acc[item] = { odd: item % 2 ? item : item - 1, even: item % 2 ? item + 1 : item } return acc
}, {}) console.log(result)

See the Pen simplified reduce by Sarah Drasner (@sdras) on CodePen.

This will shoot out the following output in the console:

1:{odd: 1, even: 2}
3:{odd: 3, even: 4}
4:{odd: 3, even: 4}
5:{odd: 5, even: 6}
6:{odd: 5, even: 6}
82:{odd: 81, even: 82}

OK, so what’s happening?

As we’re going through every item in the array, we create a property for even and odd, and based on an inline condition with a modulus operator, we’ll either store the number or increment it by 1. The modulus operator is really good for this because it can quickly check for even or odd — if it’s divisible by two, it’s even, if not, it’s odd.

Other resources

At the top, I mentioned other posts out there that are handy resources to get more familiar with the role of reducers. Here are a few of my favorites:

  • The MDN documentation is wonderful for this. Seriously, it’s one of their best posts, IMO. They also describe in a bit more detail what happens if you don’t provide an initial value, which we didn’t cover in this post.
  • Daniel Shiffman is always amazing at explaining things on Coding Train.
  • A Drip of JavaScript does a good job, too.

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