A simple box plot. Note that I start from a collection of "Record", and compute everything to build a collection of "BoxAndWhiskerData" containing all the statistical values (mean, max, outliers...) so I can use this directly in my chart. TL;DR: Charts.kt boxplot does not compute the statistical data itself, you need to compute them before, store them in a convenient object to use it in your chart.
Charts: Box plot
import io.data2viz.charts.*
import io.data2viz.charts.core.*
import io.data2viz.charts.core.Labelled
import io.data2viz.charts.dimension.*
import io.data2viz.charts.chart.*
import io.data2viz.charts.chart.mark.*
import io.data2viz.charts.viz.*
import io.data2viz.charts.layout.*
import io.data2viz.geom.*
import io.data2viz.color.*
import io.data2viz.random.RandomDistribution
import io.data2viz.timeFormat.*
import io.data2viz.timeFormat.TimeLocale
import io.data2viz.random.RandomGenerator
import kotlinx.datetime.*
import io.data2viz.math.*
fun main() {
val width = 450.0
val height = 300.0
val vc = newVizContainer().apply {
size = Size(width, height)
}
vc.chart(badData) {
config {
events {
zoomMode = ZoomMode.XY
panMode = PanMode.XY
}
tooltip {
fontSize = config.tooltip.fontSize + 2.0
}
cursor {
show = true
}
}
val id = discrete({ domain.name })
val candleValues = quantitative({ domain.median }) {
name = "Statistical values"
}
boxPlot(id, candleValues) {
minimum = { domain.minimum }
maximum = { domain.maximum }
upperQuartile = { domain.upperQuartile }
lowerQuartile = { domain.lowerQuartile }
outliers = { domain.outliers }
x {
bandwidthRatio = 50.pct
}
y {
start = 80.0
end = 120.0
}
}
}
}
data class Record(val index: Int, val value: Double, val timeStamp:Instant)
/**
* Data class for creating "Box And Whisker"
*/
public data class BoxAndWhiskerData(
val name: String,
val minimum: Double,
val maximum: Double,
val median: Double,
val lowerQuartile: Double,
val upperQuartile: Double,
val mean: Double,
val outliers: List<Double>
) : Labelled {
override val label: String = name
}
fun randomSamples(numSamples: Int, rng: RandomGenerator): List<Record> =
Array(numSamples) { Record(it / 20, rng(), Instant.fromEpochMilliseconds(1611150127144L + (it * 8632L))) }.toList()
val rng = io.data2viz.random.RandomDistribution(42).normal(100.0, 5.0)
val data = randomSamples(200, rng)
val recordsBySeries: List<List<Double>> = data.groupBy { it.index }.values.map { it.map { it.value } }
val badData = analyseData()
/**
* Build boxAndWhiskers data from a list of list
*/
public fun boxAndWhiskers(values: List<List<Double>>): List<BoxAndWhiskerData> =
values.mapIndexed { index, data ->
boxAndWhiskers(index, data)
}
private fun boxAndWhiskers(index: Int, values: List<Double>): BoxAndWhiskerData {
val orderedValues = values.sorted()
val median = median(orderedValues)
val lowerQuartile = median(median.lowerList)
val upperQuartile = median(median.upperList)
val IQR = upperQuartile.medianValue - lowerQuartile.medianValue
val outlierThreshold = IQR * 1.5
val outlierThresholdMin = median.medianValue - outlierThreshold
val outlierThresholdMax = median.medianValue + outlierThreshold
val outliers = orderedValues.filter { it < outlierThresholdMin || it > outlierThresholdMax }
val minimum = lowerQuartile.lowerList.first { it >= outlierThresholdMin }
val maximum = upperQuartile.upperList.last { it <= outlierThresholdMax }
val mean = orderedValues.sum() / orderedValues.size
return BoxAndWhiskerData("Sample #$index", minimum, maximum, median.medianValue, lowerQuartile.medianValue, upperQuartile.medianValue, mean, outliers)
}
public data class Median(
val medianValue: Double,
val lowerList: List<Double>,
val upperList: List<Double>
)
private fun median(values: List<Double>): Median {
val orderedValues = values.sorted()
val vs = orderedValues.size
val mid = vs / 2
val median = if (vs % 2 == 1) orderedValues[mid] else (orderedValues[mid] + orderedValues[mid + 1]) / 2.0
val listA = if (vs % 2 == 1) orderedValues.subList(0, mid) else orderedValues.subList(0, mid + 1)
val listB = orderedValues.subList(mid + 1, vs)
return Median(median, listA, listB)
}
fun analyseData(): List<BoxAndWhiskerData> {
val rng = RandomDistribution(42).normal(100.0, 5.0)
val data = randomSamples(200, rng)
val recordsBySeries: List<List<Double>> = data.groupBy { it.index }.values.map { it.map { it.value } }
val boxAndWhiskers = boxAndWhiskers(recordsBySeries)
return boxAndWhiskers
}
Sketch created by
pierre
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