Splits list-like values in the specified columns of this DataRow and spreads them vertically — that is, it adds a separate row for each element (one value per row) and combines them into a new DataFrame. Values in all other columns are duplicated to preserve row context.

fun <T, C> DataRow<T>.~~explode~~(vararg columns: KProperty<C>, dropEmpty: Boolean = true): DataFrame<T>

fun <T, C> DataRow<T>.~~explode~~(vararg columns: ColumnReference<C>, dropEmpty: Boolean = true): DataFrame<T>

forwardIterable

open fun forwardIterable(): Iterable<DataRow<T>>

get

open operator fun <R> get(expression: RowExpression<T, R>): R

open operator fun <R> ~~get~~(columns: List<ColumnReference<R>>): List<R>

open operator fun <R> ~~get~~(property: KProperty<R>): R

open operator fun get(path: ColumnPath): Any?

open operator fun String.get(vararg path: String): ColumnPath

open operator fun get(first: String, vararg other: String): DataRow<T>

open operator fun ~~get~~(first: ColumnReference<*>, vararg other: ColumnReference<*>): DataRow<T>

open operator override fun get(columnIndex: Int): Any?

open operator override fun get(name: String): Any?

open operator override fun <R> get(column: ColumnReference<R>): R

getColumnGroup

open fun getColumnGroup(columnName: String): AnyRow

getFrameColumn

open fun getFrameColumn(columnName: String): AnyFrame

getOrNull

open override fun getOrNull(name: String): Any?

getRow

fun <T> DataRow<T>.~~getRow~~(index: Int): DataRow<T>

getRowOrNull

fun <T> DataRow<T>.~~getRowOrNull~~(index: Int): DataRow<T>?

getRows

fun <T> DataRow<T>.~~getRows~~(indices: Iterable<Int>): DataFrame<T>

fun <T> DataRow<T>.~~getRows~~(indices: IntRange): DataFrame<T>

getValue

fun <T> DataRow<*>.getValue(columnName: String): T

fun <T> DataRow<*>.~~getValue~~(column: KProperty<T>): T

fun <T> DataRow<*>.~~getValue~~(column: ColumnReference<T>): T

getValueOrNull

open override fun <R> getValueOrNull(column: ColumnReference<R>): R?

getValueOrNull

fun <T> DataRow<*>.getValueOrNull(columnName: String): T?

fun <T> DataRow<*>.~~getValueOrNull~~(column: KProperty<T>): T?

getVisibleValues

internal fun AnyRow.getVisibleValues(): List<Pair<String, Any?>>

hashCode

open override fun hashCode(): Int

index

open override fun index(): Int

invoke

open operator fun <R> String.invoke(): R

open operator fun <R> ColumnPath.invoke(): R

open operator fun <R> ColumnReference<R>.~~invoke~~(): R

isEmpty

fun DataRow<*>.~~isEmpty~~(): Boolean

isNotEmpty

fun DataRow<*>.~~isNotEmpty~~(): Boolean

minus

open operator fun Double.minus(col: ColumnReference<Double>): Double

open operator fun Int.minus(col: ColumnReference<Int>): Int

open operator fun Long.minus(col: ColumnReference<Long>): Long

open operator fun ColumnReference<Double>.minus(a: Double): Double

open operator fun ColumnReference<Int>.minus(a: Int): Int

open operator fun ColumnReference<Long>.minus(a: Long): Long

movingAverage

inline fun <T> DataRow<T>.movingAverage(k: Int, expression: RowExpression<T, Number>): Double

namedValues

fun DataRow<*>.namedValues(): List<NameValuePair<Any?>>

internal fun AnyRow.namedValues(): Sequence<NamedValue>

namedValuesOf

inline fun <reified R> DataRow<*>.namedValuesOf(): List<NameValuePair<R>>

fun <T> DataRow<T>.next(): DataRow<T>?

Returns the next row in the DataFrame relative to the current row. If the current row is the last row in the DataFrame, it returns null.

plus

open operator fun Double.plus(col: ColumnReference<Double>): Double

open operator fun Int.plus(col: ColumnReference<Int>): Int

open operator fun Long.plus(col: ColumnReference<Long>): Long

open operator fun ColumnReference<Double>.plus(a: Double): Double

open operator fun ColumnReference<Int>.plus(a: Int): Int

open operator fun ColumnReference<Long>.plus(a: Long): Long

open operator fun ColumnReference<String>.plus(a: String): String

fun <T> DataRow<T>.prev(): DataRow<T>?

Returns the previous row in the DataFrame relative to the current row. If the current row is the first row in the DataFrame, it returns null.

primitiveOrMixedNumberColumns

internal fun <T> DataRow<T>.primitiveOrMixedNumberColumns(): ColumnsSelector<T, Number?>

fun <T> DataRow<T>.print()

relative

fun <T> DataRow<T>.relative(relativeIndices: Iterable<Int>): DataFrame<T>

fun <T> DataRow<T>.relative(relativeIndices: IntRange): DataFrame<T>

renderToString

internal fun AnyRow.renderToString(decimalFormat: RendererDecimalFormat = RendererDecimalFormat.DEFAULT): String

renderToStringTable

internal fun AnyRow.renderToStringTable(forHtml: Boolean = false): String

rowMax

fun DataRow<*>.~~rowMax~~(): Nothing

rowMaxOf

inline fun <reified T : Comparable<T>> DataRow<*>.rowMaxOf(skipNaN: Boolean = skipNaNDefault): T

Returns the maximum of the values of type T in this DataRow.

rowMaxOfOrNull

inline fun <reified T : Comparable<T>> DataRow<*>.rowMaxOfOrNull(skipNaN: Boolean = skipNaNDefault): T?

Returns the maximum of the values of type T in this DataRow, or null if there is nothing to compare.

rowMaxOrNull

fun DataRow<*>.~~rowMaxOrNull~~(): Nothing?

rowMean

fun DataRow<*>.rowMean(skipNaN: Boolean = skipNaNDefault): Double

Returns the mean of all the numbers in this DataRow, as a Double.

rowMeanOf

inline fun <reified T : Number> DataRow<*>.rowMeanOf(skipNaN: Boolean = skipNaNDefault): Double

Returns the mean of the values of type T in this DataRow, as a Double.

rowMedian

fun DataRow<*>.~~rowMedian~~(): Nothing

rowMedianOf

inline fun <reified T : Comparable<T>> DataRow<*>.rowMedianOf(): T

Returns the median of the comparable values of type T in this DataRow.

inline fun <reified T : Comparable<T>, Number> DataRow<*>.rowMedianOf(skipNaN: Boolean = skipNaNDefault): Double

Returns the median of the numbers of type T in this DataRow, as a Double.

rowMedianOfOrNull

inline fun <reified T : Comparable<T>> DataRow<*>.rowMedianOfOrNull(): T?

Returns the median of the comparable values of type T in this DataRow, or null if there is nothing to compute the median of.

inline fun <reified T : Comparable<T>, Number> DataRow<*>.rowMedianOfOrNull(skipNaN: Boolean = skipNaNDefault): Double?

Returns the median of the numbers of type T in this DataRow, as a Double, or null if there is nothing to compute the median of.

rowMedianOrNull

fun DataRow<*>.~~rowMedianOrNull~~(): Nothing?

rowMin

fun DataRow<*>.~~rowMin~~(): Nothing

rowMinOf

inline fun <reified T : Comparable<T>> DataRow<*>.rowMinOf(skipNaN: Boolean = skipNaNDefault): T

Returns the minimum of the values of type T in this DataRow.

rowMinOfOrNull

inline fun <reified T : Comparable<T>> DataRow<*>.rowMinOfOrNull(skipNaN: Boolean = skipNaNDefault): T?

Returns the minimum of the values of type T in this DataRow, or null if there is nothing to compare.

rowMinOrNull

fun DataRow<*>.~~rowMinOrNull~~(): Nothing?

rowPercentile

fun DataRow<*>.~~rowPercentile~~(): Nothing

rowPercentileOf

inline fun <reified T : Comparable<T>> DataRow<*>.rowPercentileOf(percentile: Double): T

Returns the given percentile of the comparable values of type T in this DataRow.

inline fun <reified T : Comparable<T>, Number> DataRow<*>.rowPercentileOf(percentile: Double, skipNaN: Boolean = skipNaNDefault): Double

Returns the given percentile of the numbers of type T in this DataRow, as a Double.

rowPercentileOfOrNull

inline fun <reified T : Comparable<T>> DataRow<*>.rowPercentileOfOrNull(percentile: Double): T?

Returns the given percentile of the comparable values of type T in this DataRow, or null if there is nothing to compute the percentile of.

inline fun <reified T : Comparable<T>, Number> DataRow<*>.rowPercentileOfOrNull(percentile: Double, skipNaN: Boolean = skipNaNDefault): Double?

Returns the given percentile of the numbers of type T in this DataRow, as a Double, or null if there is nothing to compute the percentile of.

rowPercentileOrNull

fun DataRow<*>.~~rowPercentileOrNull~~(): Nothing?

rowStd

fun DataRow<*>.rowStd(skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault): Double

Returns the standard deviation of all the numbers in this DataRow, as a Double.

rowStdOf

inline fun <reified T : Number?> DataRow<*>.rowStdOf(skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault): Double

Returns the standard deviation of the values of type T in this DataRow, as a Double.

rowSum

fun DataRow<*>.rowSum(skipNaN: Boolean = skipNaNDefault): Number

Returns the sum of all the numbers in this DataRow.

rowSumOf

@JvmName(name = "rowSumOfByte")

inline fun <reified T : Byte> DataRow<*>.rowSumOf(_kClass: KClass<Byte> = Byte::class): Int

Returns the sum of the Byte values in this DataRow, as an Int.

@JvmName(name = "rowSumOfInt")

inline fun <reified T : Int> DataRow<*>.rowSumOf(_kClass: KClass<Int> = Int::class): Int

Returns the sum of the Int values in this DataRow.

@JvmName(name = "rowSumOfLong")

inline fun <reified T : Long> DataRow<*>.rowSumOf(_kClass: KClass<Long> = Long::class): Long

Returns the sum of the Long values in this DataRow.

@JvmName(name = "rowSumOfShort")

inline fun <reified T : Short> DataRow<*>.rowSumOf(_kClass: KClass<Short> = Short::class): Int

Returns the sum of the Short values in this DataRow, as an Int.

@JvmName(name = "rowSumOfDouble")

inline fun <reified T : Double> DataRow<*>.rowSumOf(skipNaN: Boolean = skipNaNDefault, _kClass: KClass<Double> = Double::class): Double

Returns the sum of the Double values in this DataRow.

@JvmName(name = "rowSumOfFloat")

inline fun <reified T : Float> DataRow<*>.rowSumOf(skipNaN: Boolean = skipNaNDefault, _kClass: KClass<Float> = Float::class): Float

Returns the sum of the Float values in this DataRow.

fun DataRow<*>.rowSumOf(type: KType, skipNaN: Boolean = skipNaNDefault): Number

Returns the sum of the values of the given type in this DataRow.

schema

fun DataRow<*>.schema(): DataFrameSchema

Returns the runtime DataFrameSchema of the DataFrame this row is part of.

times

open operator fun ColumnReference<Double>.times(a: Double): Double

open operator fun ColumnReference<Double>.times(a: Int): Double

open operator fun ColumnReference<Double>.times(a: Long): Double

open operator fun ColumnReference<Int>.times(a: Int): Int

open operator fun ColumnReference<Long>.times(a: Int): Long

open operator fun ColumnReference<Long>.times(a: Long): Long

toDataFrame

fun <T> DataRow<T>.toDataFrame(): DataFrame<T>

toMap

fun DataRow<*>.toMap(): Map<String, Any?>

toString

open override fun toString(): String

transpose

fun DataRow<*>.transpose(): DataFrame<NameValuePair<*>>

Converts this DataRow into a DataFrame with one row per column of the original row.

transposeTo

inline fun <reified T> DataRow<*>.transposeTo(): DataFrame<NameValuePair<T>>

Converts this DataRow into a DataFrame with one row per column of the original row.

@PublishedApi

internal fun <T> AnyRow.transposeTo(type: KType): DataFrame<NameValuePair<T>>

Implementation of the public transposeTo that takes the target type explicitly instead of as a reified type parameter.

values

open override fun values(): List<Any?>

valuesOf

inline fun <reified R> DataRow<*>.valuesOf(): List<R>