CODEWITHSUNDEEP
scalastatisticssummary
Georg Heiler
Georg Heiler

Reputation: 17676

summary statistics in scala

How can I elegantly calculate summary statistics (e.g. mean variance) elegantly in scala per group here in this example per each different metric(name)?

case class MeasureUnit(name: String, value: Double)

Seq(MeasureUnit("metric1", 0.04), MeasureUnit("metric1", 0.09),
  MeasureUnit("metric2", 0.64), MeasureUnit("metric2", 0.34), MeasureUnit("metric2", 0.84))

An excellent example how to calculate mean /variance per property is https://chrisbissell.wordpress.com/2011/05/23/a-simple-but-very-flexible-statistics-library-in-scala/ but that does not cover the grouping.

Upvotes: 0

Views: 1139

Answers (1)

Ramón J Romero y Vigil
Ramón J Romero y Vigil

Reputation: 17933

You can use Seq#groupBy

val measureSeq : Seq[MeasureUnit] = ???

type Name = String

// "metric1" -> Seq(0.04, 0.09), "metric2" -> Seq(0.64, 0.34, 0.84)
val groupedMeasures : Map[Name, Seq[Double]] = 
  measureSeq
    .groupBy(_.name)
    .mapValues(_ map (_.value))

The groupings can then be used to calculate your summary statistics:

type Mean = Double

val meanMapping : Map[Name, Mean] = 
  groupedMeasures mapValues { v => mean(v) }

type Variance = Double

val varianceMapping : Map[Name, Variance] = 
  groupedMeasures mapValues { v => variance(v) }

Or you can map each name to a tuple of statistics:

type Summary = Tuple2[Mean, Variance]

val summaryMapping : Map[Name, Summary] = 
  groupedMeasures mapValues {s => (mean(s), variance(s)) }

Upvotes: 2

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