Let's start with a single array, like:

Copylet raceResult = ["one", "two", "four"]

If we want to combine each element with an offset counting from 0, we can use Array.enumerated(), along with map.

Copylet numberedRaceResult = raceResult
    .enumerated()
    .map { offset, element in "\(offset). \(element)" }

for numberedResult in numberedRaceResult {
    print(numberedResult)
}

// Prints:
// 0. one
// 1. two
// 2. four

You can see that I didn't call print inside the closure passed to map. You can do this, but it kind of defeats the purpose of map (which is to create an equal-sized output array from the transformed elements of the input array), because the result would be unused. In that case, it makes more sense to just use a for loop or a call to forEach, like @Sh_Khan showed.

To handle a nested array, it's much the same. We can use the same logic as for one array, but apply it to each sub-array.

Copylet raceResults = [
    ["one", "two", "four"],
    ["two", "one", "five", "six"],
    ["two", "one", "four", "ten"],
    ["one", "two", "four"],
]

let numberedRaceResults = raceResults
    .enumerated()
    .flatMap { outterOffset, raceResult in
        raceResult
            .enumerated()
            .map { innerOffset, element in "\(outterOffset).\(innerOffset). \(element)" }
    }

for numberedResult in numberedRaceResults {
    print(numberedResult)
}

// Prints:
// 0.0. one
// 0.1. two
// 0.2. four
// 1.0. two
// 1.1. one
// 1.2. five
// 1.3. six
// 2.0. two
// 2.1. one
// 2.2. four
// 2.3. ten
// 3.0. one
// 3.1. two
// 3.2. four

You'll notice that I used flatMap on the outter array, instead of a simple map. You can change it back and forth and compare the result. In short, flatMap gives you a single flat array of string results, rather than an array of sub-arrays of strings.

There are 2 similar key functions which perform similar operations, the basic purpose of which is to take an array and build another array from it:

func map(transform:(R)->T) -> [T] --- Map takes an array of elements of one type and converts it to an array of elements of (potentially) another type, by calling a transform function on each element in turn. So you can convert an array of Int's to an array of strings:

[1, 2, 3, 4].map { "\($0)" } // --> ["1", "2", "3", "4"]

func filter(predicate:(T)->Boolean) -> [T] -- Filter takes an array of elements and converts it to an array of elements of the same type, but only includes those elements for which predicate returns true. So you can filter an array of ints to leave only the even numbers:

[1, 2, 3, 4].filter { $0 % 2 == 0 } // --> [ 2, 4]

There are other variants, such as flatMap which takes [[T]] and turns it into [T] by iterating over the input and array and appending the contents of each array to an output array:

[ [1, 2], [3, 4]].flatMap() // --> [1, 2, 3, 4]

It's also worth nothing that the concept behind map is that, in simplistic terms, it can be used to map any input type to an output type, so you can define:

func <R, T> map(in:R?, transform:(R)->T) -> T?

for example, which would translate any optional input type into an optional output type given a function that translates the base type.

Since Swift 4 you can do @Tj3n's approach more cleanly and efficiently using the into version of reduce It gets rid of the temporary dictionary and the return value so it is faster and easier to read.

Sample code setup:

struct Person { 
    let name: String
    let position: Int
}
let myArray = [Person(name:"h", position: 0), Person(name:"b", position:4), Person(name:"c", position:2)]

Into parameter is passed empty dictionary of result type:

let myDict = myArray.reduce(into: [Int: String]()) {
    $0[$1.position] = $1.name
}

Directly returns a dictionary of the type passed in into:

print(myDict) // [2: "c", 0: "h", 4: "b"]