# Scala articles

## Sequence averages in Scala

I’ve been learning Scala and decided to put together a C# to Scala cheat sheet. All is going pretty well but then I got stuck on the equivalent of Average.

Enumerable.Average in .NET calculates a mean average from your sequence by summing up all the values and counting them in a single pass then returning the sum divided by the count in a floating point format (or decimal).

### The problem

Given that Scala has nothing built-in there are more than a few suggestions online that boil down to:

`val average = seq.sum / seq.length`

This has a few problems:

- Visiting a sequence twice can be inefficient
- Sum can overflow as it is the same type as the sequence
- Applied to an integer without casting it returns an integer average

### A solution

Scala provides a useful high-order function called foldLeft. Its job is to take an initial state and a function then keep applying the function with each value to the state. So one more efficient solution to the problem is:

`val average = seq.foldLeft((0.0, 1)) ((acc, i) => ((acc._1 + (i - acc._1) / acc._2), acc._2 + 1))._1`

### How does this work?

What we do here is calculate an average as we go, adding the new weighted average each time.

It achieves this by setting up a tuple to contain our initial state with **(0.0, 1)**. This specifies our starting average of 0.0 and our starting position of 1.

The next part specifies the function that takes that state as **acc** (for accumulator) and the next value in the sequence as **i** and calculates our rolling average for each value and increases the position as it goes along.

Finally at the end of our call we specify **._1** which tells the compiler we want the first value from the tuple – the average – as we no longer care about the position.

If you wanted to make this function more reusable you could do this:

`def average(s: Seq[Int]): Double = s.foldLeft((0.0, 1)) ((acc, i) => ((acc._1 + (i - acc._1) / acc._2), acc._2 + 1))._1`

Be aware you might need multiple overloads for each numeric sequence type you want to be able to average given the lack of a common numeric trait that allows for the subtraction and division.

### Precision and rounding

There is some slight variance in results between this approach and the total / count due to rounding precision. If you wanted to preserve that you could always add and then divide at the end still in a single pass much like .NET does but with Scala’s foldLeft rather than a foreach.

`def average(s: Seq[Int]): Double = { val t = s.foldLeft((0.0, 0)) ((acc, i) => (acc._1 + i, acc._2 + 1)); t._1 / t._2 }`

*[)amien*