73 lines
3.1 KiB
Markdown
Vendored
73 lines
3.1 KiB
Markdown
Vendored
[//]: # (title: median)
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<!---IMPORT org.jetbrains.kotlinx.dataframe.samples.api.Analyze-->
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Computes the [median](https://en.wikipedia.org/wiki/Median) of values.
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This is also called the "middle" of a sorted list, the "50th [percentile](percentile.md)", or
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the 2-[quantile](https://en.wikipedia.org/wiki/Quantile).
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`null` values in the input are ignored.
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The operations either throw an exception when the input is empty (after filtering `null` or `NaN` values),
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or they return `null` when using the `-orNull` overloads.
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All primitive numeric types are supported: `Byte`, `Short`, `Int`, `Long`, `Float`, and `Double`,
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but no mix of different number types.
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In these cases, the return type is always `Double?`.
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When the number of values is even, the median is the average of the two middle values.
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The operation is also available for self-comparable columns
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(so columns of type `T : Comparable<T>`, whose values are mutually comparable, like `DateTime`, `String`, etc.)
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In this case, the return type remains `T?`.
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When the number of values is even, the median is the low of the two middle values.
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NOTE: This logic also applies to other self-comparable `Number` types, like `BigDecimal`.
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They will not be interpolated.
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All operations on `Double`/`Float` have the `skipNaN` option, which is
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set to `false` by default. This means that if a `NaN` is present in the input, it will be propagated to the result.
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When it's set to `true`, `NaN` values are ignored.
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<!---FUN medianModes-->
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```kotlin
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df.median() // median of values for every column with mutually comparable values
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df.median { age and weight } // median of all values in `age` and `weight`
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df.medianFor(skipNaN = true) { age and name.firstName } // median of values per `age` and `firstName` separately
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df.medianOf { (weight ?: 0) / age } // median of expression evaluated for every row
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df.medianBy { age } // DataRow where the median age lies (lower-median for an even number of values)
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```
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<!---END-->
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<!---FUN medianAggregations-->
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```kotlin
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df.median()
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df.age.median()
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df.groupBy { city }.median()
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df.pivot { city }.median()
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df.pivot { city }.groupBy { name.lastName }.median()
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```
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<!---END-->
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See [statistics](summaryStatistics.md#groupby-statistics) for details on complex data aggregations.
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See [column selectors](ColumnSelectors.md) for how to select the columns for this operation.
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### Type Conversion
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The following automatic type conversions are performed for the `median` operation.
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(Note that `null` only appears in the return type when using `-orNull` overloads).
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| Conversion | Result for Empty Input |
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|----------------------------------|------------------------|
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| T -> T where T : Comparable\<T\> | null |
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| Int -> Double | null |
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| Byte -> Double | null |
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| Short -> Double | null |
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| Long -> Double | null |
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| Double -> Double | null |
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| Float -> Double | null |
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| Nothing -> Nothing | null |
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