inline fun <reified R, T> DataFrame<T>.~~add~~(property: KProperty<R>, infer: Infer = Infer.Nulls, noinline expression: AddExpression<T, R>): DataFrame<T>

inline fun <reified R, T> DataFrame<T>.~~add~~(column: ColumnAccessor<R>, infer: Infer = Infer.Nulls, noinline expression: AddExpression<T, R>): DataFrame<T>

inline fun <reified R, T> DataFrame<T>.add(path: ColumnPath, infer: Infer = Infer.Nulls, noinline expression: AddExpression<T, R>): DataFrame<T>

Creates a new column using AddExpression and inserts it at the specified ColumnPath.

addAll

@JvmName(name = "addAllFrames")

fun <T> DataFrame<T>.addAll(dataFrames: Iterable<DataFrame<*>>): DataFrame<T>

fun <T> DataFrame<T>.addAll(vararg dataFrames: DataFrame<*>): DataFrame<T>

Adds all columns from the given dataFrames to the end of this DataFrame (at the top level).

fun <T> DataFrame<T>.addAll(columns: Iterable<BaseColumn<*>>): DataFrame<T>

fun <T> DataFrame<T>.addAll(vararg columns: BaseColumn<*>): DataFrame<T>

Adds new columns to the end of this DataFrame (at the top level).

addFlag

internal fun <C> ColumnsResolver<C>.addFlag(flag: SortFlag): ColumnSetWithSortFlag<C>

addId

fun DataColumn<*>.addId(columnName: String = "id"): DataFrame<*>

fun <T> DataFrame<T>.addId(columnName: String = "id"): DataFrame<T>

fun <T> DataFrame<T>.~~addId~~(column: ColumnAccessor<Int>): DataFrame<T>

addParent

internal fun <T> BaseColumn<T>.addParent(parent: ColumnGroup<*>): DataColumn<T>

addParentPath

internal fun <T> BaseColumn<T>.addParentPath(path: ColumnPath): ColumnWithPath<T>

addPath

internal fun <T> BaseColumn<T>.addPath(): ColumnWithPath<T>

internal fun <T> BaseColumn<T>.addPath(path: ColumnPath): ColumnWithPath<T>

aggregate

open override fun <R> aggregate(body: AggregateGroupedBody<T, R>): DataRow<T>

Aggregates this DataFrame using the provided statistics inside the AggregateDsl.

aggregateAll

internal fun <T, C, R> DataFrame<T>.aggregateAll(aggregator: Aggregator<C & Any, R>, columns: ColumnsSelector<T, C>): R

all

fun <T> DataColumn<T>.all(predicate: Predicate<T>): Boolean

Returns true if all values match the given predicate or values is empty.

inline fun <T> DataFrame<T>.all(predicate: RowFilter<T>): Boolean

Returns true if all rows match the given predicate or rows is empty.

allAfterInternal

@PublishedApi

internal inline fun ColumnsResolver<*>.allAfterInternal(crossinline colByPredicate: ColumnFilter<*>): ColumnSet<*>

Returns a new ColumnSet containing all columns after the first column that matches the given predicate.

allBeforeInternal

@PublishedApi

internal inline fun ColumnsResolver<*>.allBeforeInternal(crossinline colByPredicate: ColumnFilter<*>): ColumnSet<*>

Returns a new ColumnSet containing all columns before the first column that satisfies the given predicate.

allColsExceptInternal

internal fun SingleColumn<DataRow<*>>.allColsExceptInternal(other: ColumnsResolver<*>): ColumnSet<Any?>

Returns a new ColumnSet that contains all columns from inside the receiver column group except those specified in the "other" ColumnsResolver.

allColumnsInternal

@PublishedApi

internal fun ColumnsResolver<*>.allColumnsInternal(removePaths: Boolean = false): TransformableColumnSet<*>

If this is a SingleColumn containing a single ColumnGroup (like SingleColumn<AnyRow> or ColumnsSelectionDsl), it returns a (transformable) ColumnSet containing the children of this ColumnGroup, else it simply returns a (transformable) ColumnSet from this (like when this is a ColumnSet).

allFromInternal

@PublishedApi

internal inline fun ColumnsResolver<*>.allFromInternal(crossinline colByPredicate: ColumnFilter<*>): ColumnSet<*>

Returns a column set containing all columns from the internal column set that satisfy the given predicate.

allNulls

fun <C> DataColumn<C>.allNulls(): Boolean

Returns true if all values are null or values is empty.

allUpToInternal

@PublishedApi

internal inline fun ColumnsResolver<*>.allUpToInternal(crossinline colByPredicate: ColumnFilter<*>): ColumnSet<*>

Returns a ColumnSet containing all columns up to (and including) the first column that satisfies the given predicate.

any

fun <T> DataColumn<T>.any(predicate: Predicate<T>): Boolean

Returns true if at least one element in this DataColumn satisfies the given predicate.

inline fun <T> DataFrame<T>.any(predicate: RowFilter<T>): Boolean

Returns true if at least one row in this DataFrame satisfies the given predicate.

append

fun <T> DataFrame<T>.append(vararg values: Any?): DataFrame<T>

inline fun <reified T : DataRowSchema> DataFrame<T>.append(vararg rows: T): DataFrame<T>

appendNulls

fun <T> DataFrame<T>.appendNulls(numberOfRows: Int = 1): DataFrame<T>

asAnyFrameColumn

@PublishedApi

internal fun AnyCol.asAnyFrameColumn(): FrameColumn<*>

asColumnGroup

@JvmName(name = "asColumnGroupUntyped")

fun DataColumn<*>.asColumnGroup(): ColumnGroup<*>

@JvmName(name = "asGroupedT")

fun <T> DataColumn<DataRow<T>>.asColumnGroup(): ColumnGroup<T>

fun <T> DataFrame<T>.asColumnGroup(name: String = ""): ColumnGroup<T>

fun <T> DataFrame<T>.asColumnGroup(column: ColumnGroupAccessor<T>): ColumnGroup<T>

fun <C> SingleColumn<C>.asColumnGroup(): SingleColumn<DataRow<C>>

@JvmName(name = "asColumnGroupDataRow")

fun <C> SingleColumn<DataRow<C>>.asColumnGroup(): SingleColumn<DataRow<C>>

Creates a ColumnAccessor<DataRow<C>> from this. This is especially useful when you want to use ColumnGroup functions in the ColumnsSelectionDsl but your column type is not recognized as a ColumnGroup. If you're not sure whether a column is recognized as ColumnGroup or not, you can always call asColumnGroup and it will return the same type if it is already a ColumnGroup.

asColumnSet

internal fun <C> ColumnsResolver<C>.asColumnSet(): ColumnSet<C>

@PublishedApi

internal fun <C> SingleColumn<C>.asColumnSet(): ColumnSet<C>

asComparable

@JvmName(name = "asComparableNullable")

fun <T> DataColumn<T?>.asComparable(): DataColumn<Comparable<T>?>

fun <T : Any> DataColumn<T>.asComparable(): DataColumn<Comparable<T>>

fun <T> SingleColumn<T>.asComparable(): SingleColumn<Comparable<T>>

asDataColumn

fun <T> ColumnGroup<T>.asDataColumn(): DataColumn<DataRow<T>>

asDataFrame

fun <T> DataColumn<DataRow<T>>.asDataFrame(): DataFrame<T>

fun <T> ColumnGroup<T>.asDataFrame(): DataFrame<T>

asFrameColumn

@JvmName(name = "asFrameColumnUntyped")

fun DataColumn<*>.asFrameColumn(): FrameColumn<*>

fun <T> DataColumn<DataFrame<T>>.asFrameColumn(): FrameColumn<T>

asGroupBy

fun <T> DataFrame<T>.asGroupBy(): GroupBy<T, T>

fun <T, G> DataFrame<T>.asGroupBy(selector: ColumnSelector<T, DataFrame<G>>): GroupBy<T, G>

fun <T> DataFrame<T>.asGroupBy(groupedColumnName: String): GroupBy<T, T>

fun <T, G> DataFrame<T>.~~asGroupBy~~(groupedColumn: ColumnReference<DataFrame<G>>): GroupBy<T, G>

asIterable

fun <T> DataColumn<T>.asIterable(): Iterable<T>

Returns an Iterable over the values of this DataColumn.

asNumbers

@JvmName(name = "asNumberAnyNullable")

fun DataColumn<Any?>.asNumbers(): ValueColumn<Number?>

@JvmName(name = "asNumberAny")

fun DataColumn<Any>.asNumbers(): ValueColumn<Number>

@JvmName(name = "asNumbersAnyNullable")

fun SingleColumn<Any?>.asNumbers(): SingleColumn<Number?>

@JvmName(name = "asNumbersAny")

fun SingleColumn<Any>.asNumbers(): SingleColumn<Number>

asSequence

fun <T> DataColumn<T>.asSequence(): Sequence<T>

Returns a Sequence over the values of this DataColumn.

fun <T> DataFrame<T>.asSequence(): Sequence<DataRow<T>>

Returns a Sequence of DataRow over this DataFrame.

assertIsComparable

internal fun <T> DataColumn<T>.assertIsComparable(): DataColumn<T>

associate

inline fun <T, K, V> DataFrame<T>.associate(transform: RowExpression<T, Pair<K, V>>): Map<K, V>

Builds a Map from key-value Pairs produced by applying transform to each row.

associateBy

inline fun <T, V> DataFrame<T>.associateBy(transform: RowExpression<T, V>): Map<V, DataRow<T>>

Builds a Map where each key is produced by applying transform to a row, and the value is the corresponding DataRow.

asValueColumn

fun DataColumn<*>.asValueColumn(): ValueColumn<*>

internal fun <T> DataColumn<T>.asValueColumn(): ValueColumn<T>

asValues

internal fun <T> AnyCol.asValues(): ValueColumn<T>

between

fun <T : Comparable<T>> DataColumn<T>.between(left: T, right: T, includeBoundaries: Boolean = true): DataColumn<Boolean>

Returns a DataColumn of Boolean values indicating whether each element in this column lies between left and right.

cast

fun <T> DataColumn<*>.cast(): DataColumn<T>

fun <T> DataFrame<*>.cast(): DataFrame<T>

fun <T> ColumnGroup<*>.cast(): ColumnGroup<T>

fun <C> ColumnReference<*>.cast(): ColumnReference<C>

fun <C> ColumnsResolver<*>.cast(): ColumnsResolver<C>

fun <C> SingleColumn<*>.cast(): SingleColumn<C>

inline fun <reified T> DataFrame<*>.cast(verify: Boolean = true): DataFrame<T>

castTo

inline fun <reified T> DataFrame<*>.castTo(schemaFrom: Function<DataFrame<T>>, verify: Boolean = true): DataFrame<T>

With the compiler plugin, schema marker T of DataFrame can be a local type. You cannot refer to it directly from your code, like a type argument for cast. The example below shows a situation where you'd need to cast DataFrame<*> to DataFrame. This function helps by inferring type from schemaFrom

inline fun <reified T> DataFrame<*>.castTo(schemaFrom: DataFrame<T>, verify: Boolean = true): DataFrame<T>

castToNotNullable

fun <T> DataColumn<T?>.castToNotNullable(): DataColumn<T>

fun <T> ColumnReference<T?>.castToNotNullable(): ColumnReference<T>

castToNullable

fun <T> DataColumn<T>.castToNullable(): DataColumn<T?>

fun <T> ColumnReference<T>.castToNullable(): ColumnReference<T?>

checkEquals

internal fun <T> BaseColumn<T>.checkEquals(other: Any?): Boolean

chunked

fun <T> DataColumn<T>.chunked(size: Int): ValueColumn<List<T>>

Groups consecutive values of this DataColumn into lists of at most size elements.

fun <T> DataColumn<DataRow<T>>.chunked(size: Int): FrameColumn<T>

Splits a DataColumn of DataRow into a FrameColumn of sub-dataframes with up to size rows in each chunk.

fun <T> ColumnGroup<T>.chunked(size: Int): FrameColumn<T>

Splits this ColumnGroup into a FrameColumn of sub-dataframes with up to size rows in each chunk.

fun <T> DataFrame<T>.chunked(size: Int, name: String = "groups"): FrameColumn<T>

Splits this DataFrame into consecutive chunks of up to size rows and returns them as a FrameColumn.

fun <T> DataFrame<T>.chunked(startIndices: Iterable<Int>, name: String = "groups"): FrameColumn<T>

Splits this DataFrame into chunks starting at the given startIndices.

chunkedImpl

internal fun <T> DataFrame<T>.chunkedImpl(startIndices: Iterable<Int>, name: String = "groups"): FrameColumn<T>

Creates a FrameColumn from this by splitting the dataframe into smaller ones, based on the given startIndices.

colsAtAnyDepthInternal

internal fun ColumnsResolver<*>.colsAtAnyDepthInternal(predicate: ColumnFilter<*>): ColumnSet<*>

Returns all columns inside this ColumnsResolver at any depth if they satisfy the given predicate.

colsInternal

@PublishedApi

internal inline fun ColumnsResolver<*>.colsInternal(crossinline predicate: ColumnFilter<*>): TransformableColumnSet<*>

If this ColumnsResolver is a SingleColumn, it returns a new ColumnSet containing the columns inside of this SingleColumn that match the given predicate.

internal fun ColumnsResolver<*>.colsInternal(indices: IntArray): TransformableColumnSet<*>

internal fun ColumnsResolver<*>.colsInternal(range: IntRange): TransformableColumnSet<*>

internal fun SingleColumn<DataRow<*>>.colsInternal(refs: Iterable<ColumnReference<*>>): ColumnSet<*>

colsOf

inline fun <reified C> SingleColumn<DataRow<*>>.colsOf(noinline filter: (ColumnWithPath<C>) -> Boolean = { true }): ColumnSet<C>

fun <C> SingleColumn<DataRow<*>>.colsOf(type: KType, filter: (ColumnWithPath<C>) -> Boolean = { true }): ColumnSet<C>

Returns a ColumnSet of columns from this that are a subtype of the given type C, optionally filtered by filter.

colsOfInternal

internal inline fun <C> ColumnsResolver<*>.colsOfInternal(type: KType, crossinline filter: ColumnFilter<C>): TransformableColumnSet<C>

If this ColumnsResolver is a SingleColumn, it returns a new ColumnSet containing the columns inside of this SingleColumn that match the given filter and are the given type.

column

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

fun <T> ColumnReference<DataRow<*>>.column(name: String): ColumnAccessor<T>

fun <T> ColumnReference<DataRow<*>>.~~column~~(property: KProperty<T>): ColumnAccessor<T>

fun <T> ColumnReference<DataRow<*>>.column(path: ColumnPath): ColumnAccessor<T>

columnGroup

fun ColumnReference<DataRow<*>>.columnGroup(): ColumnDelegate<DataRow<*>>

fun ColumnReference<DataRow<*>>.columnGroup(name: String): ColumnAccessor<DataRow<*>>

fun <T> ColumnReference<DataRow<*>>.~~columnGroup~~(property: KProperty<T>): ColumnAccessor<DataRow<T>>

@JvmName(name = "columnGroupDataRowKProperty")

fun <T> ColumnReference<DataRow<*>>.~~columnGroup~~(property: KProperty<DataRow<T>>): ColumnAccessor<DataRow<T>>

fun ColumnReference<DataRow<*>>.columnGroup(path: ColumnPath): ColumnAccessor<DataRow<*>>

columnGroupsInternal

internal inline fun ColumnsResolver<*>.columnGroupsInternal(crossinline filter: (ColumnGroup<*>) -> Boolean): ColumnSet<DataRow<*>>

Returns a ColumnSet containing the column groups that satisfy the given filter.

columnNames

open override fun columnNames(): List<String>

columns

open override fun columns(): List<DataColumn<*>>

columnsCount

open override fun columnsCount(): Int

columnsOfKindInternal

internal inline fun ColumnsResolver<*>.columnsOfKindInternal(kinds: Set<ColumnKind>, crossinline filter: ColumnFilter<*>): TransformableColumnSet<*>

Returns a TransformableColumnSet containing the columns of given kind(s) that satisfy the given filter.

columnTypes

open override fun columnTypes(): List<KType>

compileTimeSchema

inline fun <reified T> DataFrame<T>.compileTimeSchema(ordered: Boolean = true): DataFrameSchema

Returns the compile-time DataFrameSchema of this DataFrame: the schema that follows from its type argument T, not from the columns it holds.

concat

fun <T> DataColumn<Collection<T>>.concat(): List<T>

Returns a List containing the elements of every Collection stored in this column.

fun <T> DataColumn<DataFrame<T>>.concat(): DataFrame<T>

Returns a DataFrame containing the rows from every DataFrame stored in this column.

fun <T> DataColumn<T>.concat(vararg other: DataColumn<T>): DataColumn<T>

Returns a DataColumn containing the values of this column followed by the values of other.

fun <T> DataFrame<T>.concat(frames: Iterable<DataFrame<T>>): DataFrame<T>

Returns a DataFrame containing the rows of this DataFrame followed by the rows from frames.

@JvmName(name = "concatT")

fun <T> DataFrame<T>.concat(rows: Iterable<DataRow<T>>): DataFrame<T>

Returns a DataFrame containing the rows of this DataFrame followed by rows.

infix fun <T, T1> DataFrame<T>.concat(frame: DataFrame<T1>): DataFrame<Any>

Returns a DataFrame containing the rows of this DataFrame followed by the rows of frame.

fun <T> DataFrame<T>.concat(vararg frames: DataFrame<T>): DataFrame<T>

Returns a DataFrame containing the rows of this DataFrame followed by the rows of frames.

contains

open operator override fun contains(value: DataRow<T>): Boolean

contains

operator fun ColumnsContainer<*>.~~contains~~(column: KProperty<*>): Boolean

operator fun ColumnsContainer<*>.~~contains~~(column: ColumnReference<*>): Boolean

containsColumn

open override fun containsColumn(name: String): Boolean

open override fun containsColumn(path: ColumnPath): Boolean

containsColumn

fun ColumnsContainer<*>.~~containsColumn~~(column: KProperty<*>): Boolean

fun <C> ColumnsContainer<*>.~~containsColumn~~(column: ColumnReference<C>): Boolean

convert

fun <T, C> DataFrame<T>.convert(columns: ColumnsSelector<T, C>): Convert<T, C>

fun <T> DataFrame<T>.convert(vararg columns: String): Convert<T, Any?>

Converts the values in the specified columns either to a supported target type or using a custom converter, keeping their original names and positions within the DataFrame.

fun <T, C> DataFrame<T>.~~convert~~(vararg columns: KProperty<C>): Convert<T, C>

fun <T, C> DataFrame<T>.~~convert~~(vararg columns: ColumnReference<C>): Convert<T, C>

inline fun <T, C, reified R> DataFrame<T>.~~convert~~(firstCol: KProperty<C>, vararg cols: KProperty<C>, infer: Infer = Infer.Nulls, noinline expression: RowValueExpression<T, C, R>): DataFrame<T>

inline fun <T, C, reified R> DataFrame<T>.~~convert~~(firstCol: ColumnReference<C>, vararg cols: ColumnReference<C>, infer: Infer = Infer.Nulls, noinline expression: RowValueExpression<T, C, R>): DataFrame<T>

inline fun <T, reified R> DataFrame<T>.convert(firstCol: String, vararg cols: String, infer: Infer = Infer.Nulls, noinline expression: RowValueExpression<T, Any?, R>): DataFrame<T>

Converts specified columns using row converter expression within the DataFrame. Provide a new value for every selected cell given its row and its previous value using a row value expression.

convertTo

inline fun <reified C> DataColumn<*>.convertTo(): DataColumn<C>

Converts values in this column to the specified type C.

fun DataColumn<*>.convertTo(newType: KType): DataColumn<*>

Converts values in this column to the specified type.

inline fun <reified C> DataColumn<String?>.convertTo(parserOptions: ParserOptions? = null): DataColumn<C>

Converts values in this String column to the specified type C.

fun DataColumn<String?>.convertTo(newType: KType, parserOptions: ParserOptions? = null): DataColumn<*>

Converts values in this String column to the specified type.

inline fun <reified T : Any> DataFrame<*>.convertTo(excessiveColumnsBehavior: ExcessiveColumns = ExcessiveColumns.Keep, noinline body: ConvertSchemaDsl<T>.() -> Unit = {}): DataFrame<T>

inline fun <reified T : Any> DataFrame<*>.convertTo(schemaFrom: DataFrame<T>, excessiveColumnsBehavior: ExcessiveColumns = ExcessiveColumns.Keep, noinline body: ConvertSchemaDsl<T>.() -> Unit = {}): DataFrame<T>

Converts values in DataFrame to match given column schema T.

fun DataFrame<*>.convertTo(schemaType: KType, excessiveColumnsBehavior: ExcessiveColumns = ExcessiveColumns.Keep, body: ConvertSchemaDsl<Any>.() -> Unit = {}): DataFrame<*>

Converts values in DataFrame to match given column schema schemaType.

convertToBigDecimal

fun <T : Any> DataColumn<T?>.convertToBigDecimal(): DataColumn<BigDecimal?>

Converts values in this column to BigDecimal. Preserves null values.

@JvmName(name = "convertToBigDecimalFromT")

fun <T : Any> DataColumn<T>.convertToBigDecimal(): DataColumn<BigDecimal>

Converts values in this column to BigDecimal.

convertToBigInteger

fun <T : Any> DataColumn<T?>.convertToBigInteger(): DataColumn<BigInteger?>

Converts values in this column to BigInteger. Preserves null values.

@JvmName(name = "convertToBigIntegerFromT")

fun <T : Any> DataColumn<T>.convertToBigInteger(): DataColumn<BigInteger>

Converts values in this column to BigInteger.

convertToBoolean

fun <T : Any> DataColumn<T?>.convertToBoolean(): DataColumn<Boolean?>

Converts values in this column to Boolean. Preserves null values.

@JvmName(name = "convertToBooleanFromT")

fun <T : Any> DataColumn<T>.convertToBoolean(): DataColumn<Boolean>

Converts values in this column to Boolean.

convertToByte

fun <T : Any> DataColumn<T?>.convertToByte(): DataColumn<Byte?>

Converts values in this column to Byte. Preserves null values.

@JvmName(name = "convertToByteFromT")

fun <T : Any> DataColumn<T>.convertToByte(): DataColumn<Byte>

Converts values in this column to Byte.

convertToDateTimeComponents

@JvmName(name = "convertToDateTimeComponentsFromStringNullablePattern")

@FormatStringsInDatetimeFormats

fun DataColumn<String?>.convertToDateTimeComponents(pattern: String): DataColumn<DateTimeComponents?>

@JvmName(name = "convertToDateTimeComponentsFromStringNullable")

fun DataColumn<String?>.convertToDateTimeComponents(format: DateTimeFormat<DateTimeComponents>? = null): DataColumn<DateTimeComponents?>

Converts values in this String column to DateTimeComponents. Preserves null values.

@JvmName(name = "convertToDateTimeComponentsFromStringPattern")

@FormatStringsInDatetimeFormats

fun DataColumn<String>.convertToDateTimeComponents(pattern: String): DataColumn<DateTimeComponents>

@JvmName(name = "convertToDateTimeComponentsFromString")

fun DataColumn<String>.convertToDateTimeComponents(format: DateTimeFormat<DateTimeComponents>? = null): DataColumn<DateTimeComponents>

Converts values in this String column to DateTimeComponents.

convertToDeprecatedInstant

@JvmName(name = "convertToDeprecatedInstantFromStringNullable")

fun DataColumn<String?>.~~convertToDeprecatedInstant~~(): DataColumn<Instant?>

Converts values in this String column to the deprecated kotlinx.datetime.Instant. Preserves null values.

fun DataColumn<String>.~~convertToDeprecatedInstant~~(): DataColumn<Instant>

Converts values in this String column to the deprecated kotlinx.datetime.Instant.

convertToDouble

fun <T : Any> DataColumn<T?>.convertToDouble(): DataColumn<Double?>

Converts values in this column to Double. Preserves null values.

@JvmName(name = "convertToDoubleFromT")

fun <T : Any> DataColumn<T>.convertToDouble(): DataColumn<Double>

Converts values in this column to Double.

@JvmName(name = "convertToDoubleFromStringNullable")

fun DataColumn<String?>.convertToDouble(locale: Locale? = null): DataColumn<Double?>

@JvmName(name = "convertToDoubleFromString")

fun DataColumn<String>.convertToDouble(locale: Locale? = null): DataColumn<Double>

@JvmName(name = "convertToDoubleFromStringNullable")

fun DataColumn<String?>.convertToDouble(locale: Locale? = null, nullStrings: Set<String>?, useFastDoubleParser: Boolean?): DataColumn<Double?>

@JvmName(name = "convertToDoubleFromString")

fun DataColumn<String>.convertToDouble(locale: Locale? = null, nullStrings: Set<String>?, useFastDoubleParser: Boolean?): DataColumn<Double>

Converts values in this String column to Double considering locale (number format).

convertToDuration

fun <T : Any> DataColumn<T?>.convertToDuration(): DataColumn<Duration?>

Converts values in this column to Duration. Preserves null values.

@JvmName(name = "convertToDurationFromT")

fun <T : Any> DataColumn<T>.convertToDuration(): DataColumn<Duration>

Converts values in this column to Duration.

convertToFloat

fun <T : Any> DataColumn<T?>.convertToFloat(): DataColumn<Float?>

Converts values in this column to Float. Preserves null values.

@JvmName(name = "convertToFloatFromT")

fun <T : Any> DataColumn<T>.convertToFloat(): DataColumn<Float>

Converts values in this column to Float.

convertToImpl

@PublishedApi

internal fun AnyFrame.convertToImpl(type: KType, allowConversion: Boolean, excessiveColumns: ExcessiveColumns, body: ConvertSchemaDsl<Any>.() -> Unit = {}): AnyFrame

convertToInstant

@JvmName(name = "convertToInstantFromStringNullable")

fun DataColumn<String?>.~~convertToInstant~~(): DataColumn<Instant?>

fun DataColumn<String>.~~convertToInstant~~(): DataColumn<Instant>

Deprecated:

convertToInt

fun <T : Any> DataColumn<T?>.convertToInt(): DataColumn<Int?>

Converts values in this column to Int. Preserves null values.

@JvmName(name = "convertToIntFromT")

fun <T : Any> DataColumn<T>.convertToInt(): DataColumn<Int>

Converts values in this column to Int.

convertToJavaDuration

fun <T : Any> DataColumn<T?>.convertToJavaDuration(): DataColumn<Duration?>

Converts values in this column to JavaDuration. Preserves null values.

@JvmName(name = "convertToJavaDurationFromT")

fun <T : Any> DataColumn<T>.convertToJavaDuration(): DataColumn<Duration>

Converts values in this column to JavaDuration.

convertToJavaInstant

fun <T : Any> DataColumn<T?>.convertToJavaInstant(): DataColumn<Instant?>

Converts values in this column to JavaInstant. Preserves null values.

@JvmName(name = "convertToJavaInstantFromT")

fun <T : Any> DataColumn<T>.convertToJavaInstant(): DataColumn<Instant>

Converts values in this column to JavaInstant.

convertToJavaLocalDate

fun <T : Any> DataColumn<T?>.convertToJavaLocalDate(): DataColumn<LocalDate?>

Converts values in this column to JavaLocalDate. Preserves null values.

@JvmName(name = "convertToJavaLocalDateFromT")

fun <T : Any> DataColumn<T>.convertToJavaLocalDate(): DataColumn<LocalDate>

Converts values in this column to JavaLocalDate.

@JvmName(name = "convertToJavaLocalDateFromStringNullable")

fun DataColumn<String?>.convertToJavaLocalDate(formatter: DateTimeFormatter? = null, locale: Locale? = null): DataColumn<LocalDate?>

@JvmName(name = "convertToJavaLocalDateFromStringNullablePattern")

fun DataColumn<String?>.convertToJavaLocalDate(pattern: String, locale: Locale? = null): DataColumn<LocalDate?>

Converts values in this nullable String column to JavaLocalDate. Preserves null values.

@JvmName(name = "convertToJavaLocalDateFromString")

fun DataColumn<String>.convertToJavaLocalDate(formatter: DateTimeFormatter? = null, locale: Locale? = null): DataColumn<LocalDate>

@JvmName(name = "convertToJavaLocalDateFromStringPattern")

fun DataColumn<String>.convertToJavaLocalDate(pattern: String, locale: Locale? = null): DataColumn<LocalDate>

Converts values in this String column to JavaLocalDate.

convertToJavaLocalDateTime

fun <T : Any> DataColumn<T?>.convertToJavaLocalDateTime(): DataColumn<LocalDateTime?>

Converts values in this column to JavaLocalDateTime. Preserves null values.

@JvmName(name = "convertToJavaLocalDateTimeFromT")

fun <T : Any> DataColumn<T>.convertToJavaLocalDateTime(): DataColumn<LocalDateTime>

Converts values in this column to JavaLocalDateTime.

@JvmName(name = "convertToJavaLocalDateTimeFromStringNullable")

fun DataColumn<String?>.convertToJavaLocalDateTime(formatter: DateTimeFormatter? = null, locale: Locale? = null): DataColumn<LocalDateTime?>

@JvmName(name = "convertToJavaLocalDateTimeFromStringNullablePattern")

fun DataColumn<String?>.convertToJavaLocalDateTime(pattern: String, locale: Locale? = null): DataColumn<LocalDateTime?>

Converts values in this nullable String column to JavaLocalDateTime. Preserves null values.

@JvmName(name = "convertToJavaLocalDateTimeFromString")

fun DataColumn<String>.convertToJavaLocalDateTime(formatter: DateTimeFormatter? = null, locale: Locale? = null): DataColumn<LocalDateTime>

@JvmName(name = "convertToJavaLocalDateTimeFromStringPattern")

fun DataColumn<String>.convertToJavaLocalDateTime(pattern: String, locale: Locale? = null): DataColumn<LocalDateTime>

Converts values in this String column to JavaLocalDateTime.

convertToJavaLocalTime

fun <T : Any> DataColumn<T?>.convertToJavaLocalTime(): DataColumn<LocalTime?>

Converts values in this column to JavaLocalTime. Preserves null values.

@JvmName(name = "convertToJavaLocalTimeFromT")

fun <T : Any> DataColumn<T>.convertToJavaLocalTime(): DataColumn<LocalTime>

Converts values in this column to JavaLocalTime.

@JvmName(name = "convertToJavaLocalTimeFromStringNullable")

fun DataColumn<String?>.convertToJavaLocalTime(formatter: DateTimeFormatter? = null, locale: Locale? = null): DataColumn<LocalTime?>

@JvmName(name = "convertToJavaLocalTimeFromStringNullablePattern")

fun DataColumn<String?>.convertToJavaLocalTime(pattern: String, locale: Locale? = null): DataColumn<LocalTime?>

Converts values in this nullable String column to JavaLocalTime. Preserves null values.

@JvmName(name = "convertToJavaLocalTimeFromString")

fun DataColumn<String>.convertToJavaLocalTime(formatter: DateTimeFormatter? = null, locale: Locale? = null): DataColumn<LocalTime>

@JvmName(name = "convertToJavaLocalTimeFromStringPattern")

fun DataColumn<String>.convertToJavaLocalTime(pattern: String, locale: Locale? = null): DataColumn<LocalTime>

Converts values in this String column to JavaLocalTime.

convertToLocalDate

fun <T : Any> DataColumn<T?>.convertToLocalDate(): DataColumn<LocalDate?>

Converts values in this column to LocalDate. Preserves null values.

@JvmName(name = "convertToLocalDateFromT")

fun <T : Any> DataColumn<T>.convertToLocalDate(): DataColumn<LocalDate>

Converts values in this column to LocalDate.

@JvmName(name = "convertToLocalDateFromDateTimeComponentsNullable")

fun DataColumn<DateTimeComponents?>.convertToLocalDate(): DataColumn<LocalDate?>

Converts values in this DateTimeComponents column to LocalDate. Preserves null values.

@JvmName(name = "convertToLocalDateFromDateTimeComponents")

fun DataColumn<DateTimeComponents>.convertToLocalDate(): DataColumn<LocalDate>

Converts values in this DateTimeComponents column to LocalDate.

@JvmName(name = "convertToLocalDateFromIntNullable")

fun DataColumn<Int?>.convertToLocalDate(zone: TimeZone = defaultTimeZone): DataColumn<LocalDate?>

Converts values in this Int column to LocalDate. Preserves null values.

@JvmName(name = "convertToLocalDateFromInt")

fun DataColumn<Int>.convertToLocalDate(zone: TimeZone = defaultTimeZone): DataColumn<LocalDate>

Converts values in this Int column to LocalDate.

fun DataColumn<Long?>.convertToLocalDate(zone: TimeZone = defaultTimeZone): DataColumn<LocalDate?>

Converts values in this Long column to LocalDate. Preserves null values.

@JvmName(name = "convertToLocalDateFromLong")

fun DataColumn<Long>.convertToLocalDate(zone: TimeZone = defaultTimeZone): DataColumn<LocalDate>

Converts values in this Long column to LocalDate.

@JvmName(name = "convertToLocalDateFromStringNullablePattern")

@FormatStringsInDatetimeFormats

fun DataColumn<String?>.convertToLocalDate(pattern: String): DataColumn<LocalDate?>

@JvmName(name = "convertToLocalDateFromStringNullable")

fun DataColumn<String?>.convertToLocalDate(format: DateTimeFormat<LocalDate>? = null): DataColumn<LocalDate?>

Converts values in this String column to LocalDate. Preserves null values.

@JvmName(name = "convertToLocalDateFromStringPattern")

@FormatStringsInDatetimeFormats

fun DataColumn<String>.convertToLocalDate(pattern: String): DataColumn<LocalDate>

@JvmName(name = "convertToLocalDateFromString")

fun DataColumn<String>.convertToLocalDate(format: DateTimeFormat<LocalDate>? = null): DataColumn<LocalDate>

Converts values in this String column to LocalDate.

@JvmName(name = "convertToLocalDateFromStringNullable")

fun DataColumn<String?>.~~convertToLocalDate~~(pattern: String? = null, locale: Locale? = null): DataColumn<LocalDate?>

@JvmName(name = "convertToLocalDateFromString")

fun DataColumn<String>.~~convertToLocalDate~~(pattern: String? = null, locale: Locale? = null): DataColumn<LocalDate>

convertToLocalDateTime

fun <T : Any> DataColumn<T?>.convertToLocalDateTime(): DataColumn<LocalDateTime?>

Converts values in this column to LocalDateTime. Preserves null values.

@JvmName(name = "convertToLocalDateTimeFromT")

fun <T : Any> DataColumn<T>.convertToLocalDateTime(): DataColumn<LocalDateTime>

Converts values in this column to LocalDateTime.

@JvmName(name = "convertToLocalDateTimeFromDateTimeComponentsNullable")

fun DataColumn<DateTimeComponents?>.convertToLocalDateTime(): DataColumn<LocalDateTime?>

Converts values in this DateTimeComponents column to LocalDateTime. Preserves null values.

@JvmName(name = "convertToLocalDateTimeFromDateTimeComponents")

fun DataColumn<DateTimeComponents>.convertToLocalDateTime(): DataColumn<LocalDateTime>

Converts values in this DateTimeComponents column to LocalDateTime.

@JvmName(name = "convertToLocalDateTimeFromIntNullable")

fun DataColumn<Int?>.convertToLocalDateTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalDateTime?>

Converts values in this Int column to LocalDateTime. Preserves null values.

@JvmName(name = "convertToLocalDateTimeFromInt")

fun DataColumn<Int>.convertToLocalDateTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalDateTime>

Converts values in this Int column to LocalDateTime.

fun DataColumn<Long?>.convertToLocalDateTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalDateTime?>

Converts values in this Long column to LocalDateTime. Preserves null values.

@JvmName(name = "convertToLocalDateTimeFromLong")

fun DataColumn<Long>.convertToLocalDateTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalDateTime>

Converts values in this Long column to LocalDateTime.

@JvmName(name = "convertToLocalDateTimeFromStringNullablePattern")

@FormatStringsInDatetimeFormats

fun DataColumn<String?>.convertToLocalDateTime(pattern: String): DataColumn<LocalDateTime?>

@JvmName(name = "convertToLocalDateTimeFromStringNullable")

fun DataColumn<String?>.convertToLocalDateTime(format: DateTimeFormat<LocalDateTime>? = null): DataColumn<LocalDateTime?>

Converts values in this String column to LocalDateTime. Preserves null values.

@JvmName(name = "convertToLocalDateTimeFromStringPattern")

@FormatStringsInDatetimeFormats

fun DataColumn<String>.convertToLocalDateTime(pattern: String): DataColumn<LocalDateTime>

@JvmName(name = "convertToLocalDateTimeFromString")

fun DataColumn<String>.convertToLocalDateTime(format: DateTimeFormat<LocalDateTime>? = null): DataColumn<LocalDateTime>

Converts values in this String column to LocalDateTime.

@JvmName(name = "convertToLocalDateTimeFromStdlibInstantNullable")

fun DataColumn<Instant?>.convertToLocalDateTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalDateTime?>

Converts values in this kotlin.time.Instant column to LocalDateTime. Preserves null values.

@JvmName(name = "convertToLocalDateTimeFromStdlibInstant")

fun DataColumn<Instant>.convertToLocalDateTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalDateTime>

Converts values in this kotlin.time.Instant column to LocalDateTime.

@JvmName(name = "convertToLocalDateTimeFromDeprecatedInstantNullable")

fun DataColumn<Instant?>.convertToLocalDateTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalDateTime?>

Converts values in this kotlinx.datetime.Instant column to LocalDateTime. Preserves null values.

@JvmName(name = "convertToLocalDateTimeFromDeprecatedInstant")

fun DataColumn<Instant>.convertToLocalDateTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalDateTime>

Converts values in this kotlinx.datetime.Instant column to LocalDateTime.

@JvmName(name = "convertToLocalDateTimeFromStringNullable")

fun DataColumn<String?>.~~convertToLocalDateTime~~(pattern: String? = null, locale: Locale? = null): DataColumn<LocalDateTime?>

@JvmName(name = "convertToLocalDateTimeFromString")

fun DataColumn<String>.~~convertToLocalDateTime~~(pattern: String? = null, locale: Locale? = null): DataColumn<LocalDateTime>

convertToLocalTime

fun <T : Any> DataColumn<T?>.convertToLocalTime(): DataColumn<LocalTime?>

Converts values in this column to LocalTime. Preserves null values.

@JvmName(name = "convertToLocalTimeFromT")

fun <T : Any> DataColumn<T>.convertToLocalTime(): DataColumn<LocalTime>

Converts values in this column to LocalTime.

@JvmName(name = "convertToLocalTimeFromDateTimeComponentsNullable")

fun DataColumn<DateTimeComponents?>.convertToLocalTime(): DataColumn<LocalTime?>

Converts values in this DateTimeComponents column to LocalTime. Preserves null values.

@JvmName(name = "convertToLocalTimeFromDateTimeComponents")

fun DataColumn<DateTimeComponents>.convertToLocalTime(): DataColumn<LocalTime>

Converts values in this DateTimeComponents column to LocalTime.

@JvmName(name = "convertToLocalTimeIntNullable")

fun DataColumn<Int?>.convertToLocalTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalTime?>

Converts values in this Int column to LocalTime. Preserves null values.

@JvmName(name = "convertToLocalTimeFromInt")

fun DataColumn<Int>.convertToLocalTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalTime>

Converts values in this Int column to LocalTime.

fun DataColumn<Long?>.convertToLocalTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalTime?>

Converts values in this Long column to LocalTime. Preserves null values.

@JvmName(name = "convertToLocalTimeFromLong")

fun DataColumn<Long>.convertToLocalTime(zone: TimeZone = defaultTimeZone): DataColumn<LocalTime>

Converts values in this Long column to LocalTime.

@JvmName(name = "convertToLocalTimeFromStringNullablePattern")

@FormatStringsInDatetimeFormats

fun DataColumn<String?>.convertToLocalTime(pattern: String): DataColumn<LocalTime?>

@JvmName(name = "convertToLocalTimeFromStringNullable")

fun DataColumn<String?>.convertToLocalTime(format: DateTimeFormat<LocalTime>? = null): DataColumn<LocalTime?>

Converts values in this String column to LocalTime. Preserves null values.

@JvmName(name = "convertToLocalTimeFromStringPattern")

@FormatStringsInDatetimeFormats

fun DataColumn<String>.convertToLocalTime(pattern: String): DataColumn<LocalTime>

@JvmName(name = "convertToLocalTimeFromString")

fun DataColumn<String>.convertToLocalTime(format: DateTimeFormat<LocalTime>? = null): DataColumn<LocalTime>

Converts values in this String column to LocalTime.

@JvmName(name = "convertToLocalTimeFromStringNullable")

fun DataColumn<String?>.~~convertToLocalTime~~(pattern: String? = null, locale: Locale? = null): DataColumn<LocalTime?>

@JvmName(name = "convertToLocalTimeFromString")

fun DataColumn<String>.~~convertToLocalTime~~(pattern: String? = null, locale: Locale? = null): DataColumn<LocalTime>

convertToLong

fun <T : Any> DataColumn<T?>.convertToLong(): DataColumn<Long?>

Converts values in this column to Long. Preserves null values.

@JvmName(name = "convertToLongFromT")

fun <T : Any> DataColumn<T>.convertToLong(): DataColumn<Long>

Converts values in this column to Long.

convertToShort

fun <T : Any> DataColumn<T?>.convertToShort(): DataColumn<Short?>

Converts values in this column to Short. Preserves null values.

@JvmName(name = "convertToShortFromT")

fun <T : Any> DataColumn<T>.convertToShort(): DataColumn<Short>

Converts values in this column to Short.

convertToStdlibInstant

@JvmName(name = "convertToStdlibInstantFromStringNullable")

fun DataColumn<String?>.convertToStdlibInstant(): DataColumn<Instant?>

Converts values in this String column to kotlin.time.Instant. Preserves null values.

fun DataColumn<String>.convertToStdlibInstant(): DataColumn<Instant>

Converts values in this String column to kotlin.time.Instant.

@JvmName(name = "convertToStdlibInstantFromDeprecatedInstantNullable")

fun DataColumn<Instant?>.convertToStdlibInstant(): DataColumn<Instant?>

Converts values in this kotlinx.datetime.Instant column to kotlin.time.Instant. Preserves null values.

@JvmName(name = "convertToStdlibInstantFromDeprecatedInstant")

fun DataColumn<Instant>.convertToStdlibInstant(): DataColumn<Instant>

Converts values in this kotlinx.datetime.Instant column to kotlin.time.Instant.

@JvmName(name = "convertToStdlibInstantFromDateTimeComponentsNullable")

fun DataColumn<DateTimeComponents?>.convertToStdlibInstant(): DataColumn<Instant?>

Converts values in this DateTimeComponents column to kotlin.time.Instant. Preserves null values.

@JvmName(name = "convertToStdlibInstantFromDateTimeComponents")

fun DataColumn<DateTimeComponents>.convertToStdlibInstant(): DataColumn<Instant>

Converts values in this DateTimeComponents column to kotlin.time.Instant.

convertToString

fun <T : Any> DataColumn<T?>.convertToString(): DataColumn<String?>

Converts values in this column to String. Preserves null values.

@JvmName(name = "convertToStringFromT")

fun <T : Any> DataColumn<T>.convertToString(): DataColumn<String>

Converts values in this column to String.

convertToTypeImpl

internal fun AnyCol.convertToTypeImpl(to: KType, parserOptions: ParserOptions?): AnyCol

convertToURL

@JvmName(name = "convertToURLFromStringNullable")

fun DataColumn<String?>.~~convertToURL~~(): DataColumn<URL?>

fun DataColumn<String>.~~convertToURL~~(): DataColumn<URL>

convertToUrl

@JvmName(name = "convertToUrlFromStringNullable")

fun DataColumn<String?>.convertToUrl(): DataColumn<URL?>

Converts values in this String column to an URL. Preserves null values.

fun DataColumn<String>.convertToUrl(): DataColumn<URL>

Converts values in this String column to an URL.

convertToUtcOffset

@JvmName(name = "convertToUtcOffsetNullable")

fun DataColumn<DateTimeComponents?>.convertToUtcOffset(): DataColumn<UtcOffset?>

Converts values in this DateTimeComponents column to UtcOffset. Preserves null values.

fun DataColumn<DateTimeComponents>.convertToUtcOffset(): DataColumn<UtcOffset>

Converts values in this DateTimeComponents column to UtcOffset.

convertToYearMonth

@JvmName(name = "convertToYearMonthNullable")

fun DataColumn<DateTimeComponents?>.convertToYearMonth(): DataColumn<YearMonth?>

Converts values in this DateTimeComponents column to YearMonth. Preserves null values.

fun DataColumn<DateTimeComponents>.convertToYearMonth(): DataColumn<YearMonth>

Converts values in this DateTimeComponents column to YearMonth.

copy

fun <T> DataFrame<T>.~~copy~~(): DataFrame<T>

corr

fun <T> DataFrame<T>.corr(): DataFrame<T>

Computes the pearson correlation between all suitable columns in this DataFrame, including nested columns at any depth.

fun <T, C> DataFrame<T>.corr(columns: ColumnsSelector<T, C>): Corr<T, C>

fun <T> DataFrame<T>.corr(vararg columns: String): Corr<T, Any?>

Calculates the Pearson pairwise correlation between values in the specified columns.

fun <T, C> DataFrame<T>.~~corr~~(vararg columns: KProperty<C>): Corr<T, C>

fun <T, C> DataFrame<T>.~~corr~~(vararg columns: ColumnReference<C>): Corr<T, C>

count

fun <T> DataFrame<T>.count(): Int

Returns the total number of rows of this DataFrame.

fun <T> DataColumn<T>.count(predicate: Predicate<T>? = null): Int

Counts the elements in this DataColumn that satisfy a given predicate or returns the total count if no predicate is provided.

inline fun <T> DataFrame<T>.count(predicate: RowFilter<T>): Int

Counts the number of rows in this DataFrame that satisfy the given predicate.

countDistinct

open override fun countDistinct(): Int

countDistinct

fun DataFrame<*>.countDistinct(): Int

Returns the number of distinct rows in this DataFrame.

fun <T, C> DataFrame<T>.countDistinct(columns: ColumnsSelector<T, C>): Int

fun <T> DataFrame<T>.countDistinct(vararg columns: String): Int

Returns the number of distinct combinations of values in selected columns in this DataFrame.

fun <T, C> DataFrame<T>.~~countDistinct~~(vararg columns: KProperty<C>): Int

fun <T> DataFrame<T>.~~countDistinct~~(vararg columns: ColumnReference<*>): Int

createComparator

internal fun AnyCol.createComparator(nullsLast: Boolean): Comparator<Int>

cumSum

fun <T : Number?> DataColumn<T>.cumSum(skipNA: Boolean = defaultCumSumSkipNA): DataColumn<T>

@JvmName(name = "cumSumNullableByte")

fun DataColumn<Byte?>.cumSum(skipNA: Boolean = defaultCumSumSkipNA): DataColumn<Int?>

@JvmName(name = "cumSumByte")

fun DataColumn<Byte>.cumSum(skipNA: Boolean = defaultCumSumSkipNA): DataColumn<Int>

@JvmName(name = "cumSumDouble")

fun DataColumn<Double?>.cumSum(skipNA: Boolean = defaultCumSumSkipNA): DataColumn<Double>

@JvmName(name = "cumSumFloat")

fun DataColumn<Float?>.cumSum(skipNA: Boolean = defaultCumSumSkipNA): DataColumn<Float>

@JvmName(name = "cumSumNullableShort")

fun DataColumn<Short?>.cumSum(skipNA: Boolean = defaultCumSumSkipNA): DataColumn<Int?>

@JvmName(name = "cumSumShort")

fun DataColumn<Short>.cumSum(skipNA: Boolean = defaultCumSumSkipNA): DataColumn<Int>

Computes the cumulative sums of the values in each column from the DataColumn from the first cell to the last cell.

fun <T> DataFrame<T>.cumSum(skipNA: Boolean = defaultCumSumSkipNA): DataFrame<T>

fun <T, C : Number?> DataFrame<T>.cumSum(skipNA: Boolean = defaultCumSumSkipNA, columns: ColumnsSelector<T, C>): DataFrame<T>

fun <T> DataFrame<T>.cumSum(vararg columns: String, skipNA: Boolean = defaultCumSumSkipNA): DataFrame<T>

fun <T> DataFrame<T>.~~cumSum~~(vararg columns: KProperty<Number?>, skipNA: Boolean = defaultCumSumSkipNA): DataFrame<T>

fun <T> DataFrame<T>.~~cumSum~~(vararg columns: ColumnReference<Number?>, skipNA: Boolean = defaultCumSumSkipNA): DataFrame<T>

Computes the cumulative sums of the values in each column from the DataFrame from the first cell to the last cell.

cumSumImpl

@JvmName(name = "byteCumsum")

internal fun DataColumn<Byte>.cumSumImpl(): DataColumn<Int>

@JvmName(name = "intCumsum")

internal fun DataColumn<Int>.cumSumImpl(): DataColumn<Int>

@JvmName(name = "longCumsum")

internal fun DataColumn<Long>.cumSumImpl(): DataColumn<Long>

@JvmName(name = "shortCumsum")

internal fun DataColumn<Short>.cumSumImpl(): DataColumn<Int>

@JvmName(name = "cumsumByteNullable")

internal fun DataColumn<Byte?>.cumSumImpl(skipNA: Boolean): DataColumn<Int?>

@JvmName(name = "cumsumDoubleNullable")

internal fun DataColumn<Double?>.cumSumImpl(skipNA: Boolean): DataColumn<Double>

@JvmName(name = "doubleCumsum")

internal fun DataColumn<Double>.cumSumImpl(skipNA: Boolean): DataColumn<Double>

internal fun DataColumn<Float?>.cumSumImpl(skipNA: Boolean): DataColumn<Float>

@JvmName(name = "floatCumsum")

internal fun DataColumn<Float>.cumSumImpl(skipNA: Boolean): DataColumn<Float>

@JvmName(name = "intCumsum")

internal fun DataColumn<Int?>.cumSumImpl(skipNA: Boolean): DataColumn<Int?>

@JvmName(name = "cumsumLongNullable")

internal fun DataColumn<Long?>.cumSumImpl(skipNA: Boolean): DataColumn<Long?>

@JvmName(name = "cumsumShortNullable")

internal fun DataColumn<Short?>.cumSumImpl(skipNA: Boolean): DataColumn<Int?>

internal fun DataColumn<Number?>.cumSumImpl(type: KType, skipNA: Boolean): DataColumn<Number?>

defaultValue

open override fun defaultValue(): DataRow<T>?

describe

fun <T> DataColumn<T>.describe(): DataFrame<ColumnDescription>

Computes descriptive statistics for a given DataColumn, returning a DataFrame with key summary metrics.

fun <T> DataFrame<T>.describe(): DataFrame<ColumnDescription>

Computes descriptive statistics for all columns in a given DataFrame, including nested columns, returning a DataFrame with key summary metrics for each column (with a ColumnDescription data schema).

fun <T> DataFrame<T>.describe(columns: ColumnsSelector<T, *>): DataFrame<ColumnDescription>

fun <T> DataFrame<T>.describe(vararg columns: String): DataFrame<ColumnDescription>

fun <T, C : Number?> DataFrame<T>.~~describe~~(vararg columns: KProperty<C>): DataFrame<ColumnDescription>

fun <T, C : Number?> DataFrame<T>.~~describe~~(vararg columns: ColumnReference<C>): DataFrame<ColumnDescription>

Computes descriptive statistics for the selected columns in a given DataFrame, including nested columns, returning a DataFrame with key summary metrics for each column (with a ColumnDescription data schema).

distinct

open override fun distinct(): DataColumnGroup<T>

distinct

fun <T> DataFrame<T>.distinct(): DataFrame<T>

Removes duplicated rows based on all columns.

fun <T, C> DataFrame<T>.distinct(columns: ColumnsSelector<T, C>): DataFrame<T>

fun <T> DataFrame<T>.distinct(vararg columns: String): DataFrame<T>

Selects the specified columns and keeps only distinct rows based on these selected columns.

fun <T> DataFrame<T>.~~distinct~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~distinct~~(vararg columns: ColumnReference<*>): DataFrame<T>

distinctBy

fun <T, C> DataFrame<T>.distinctBy(columns: ColumnsSelector<T, C>): DataFrame<T>

fun <T> DataFrame<T>.distinctBy(vararg columns: String): DataFrame<T>

Removes duplicated rows based on the specified columns.

fun <T> DataFrame<T>.~~distinctBy~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~distinctBy~~(vararg columns: ColumnReference<*>): DataFrame<T>

div

operator fun DataColumn<BigDecimal>.div(value: BigDecimal): DataColumn<BigDecimal>

operator fun DataColumn<BigInteger>.div(value: BigInteger): DataColumn<BigInteger>

operator fun DataColumn<Double>.div(value: Double): DataColumn<Double>

@JvmName(name = "divDouble")

operator fun DataColumn<Double>.div(value: Int): DataColumn<Double>

@JvmName(name = "divIntNullable")

operator fun DataColumn<Int?>.div(value: Int): DataColumn<Int?>

@JvmName(name = "divInt")

operator fun DataColumn<Int>.div(value: Double): DataColumn<Double>

operator fun DataColumn<Int>.div(value: Int): DataColumn<Int>

operator fun DataColumn<Long>.div(value: Long): DataColumn<Long>

Returns a DataColumn containing the results of dividing each element of this DataColumn by value.

operator fun ColumnReference<Int>.div(value: Int): ColumnReference<Int>

Returns a ColumnReference containing the results of dividing each element of this ColumnReference by value.

drop

inline fun <T> DataColumn<T>.drop(predicate: Predicate<T>): DataColumn<T>

Returns a DataColumn containing only the values that do not match the given predicate.

fun <T> DataColumn<T>.drop(n: Int): DataColumn<T>

Returns a DataColumn containing all values of this DataColumn except the first n values.

inline fun <T> DataFrame<T>.drop(predicate: RowFilter<T>): DataFrame<T>

Returns a DataFrame containing all rows except the rows that satisfy the given predicate.

fun <T> DataFrame<T>.drop(n: Int): DataFrame<T>

Returns a DataFrame containing all rows except the first n rows.

dropLast

fun <T> DataColumn<T>.dropLast(n: Int = 1): DataColumn<T>

Returns a DataColumn containing all values of this DataColumn except the last n values.

fun <T> DataFrame<T>.dropLast(n: Int = 1): DataFrame<T>

Returns a DataFrame containing all rows except the last n rows.

dropNA

fun <T> DataColumn<T?>.dropNA(): DataColumn<T>

Removes NA values from this DataColumn, adjusting the type accordingly.

fun <T> DataFrame<T>.dropNA(whereAllNA: Boolean = false): DataFrame<T>

fun <T> DataFrame<T>.dropNA(whereAllNA: Boolean = false, columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.dropNA(vararg columns: String, whereAllNA: Boolean = false): DataFrame<T>

fun <T> DataFrame<T>.~~dropNA~~(vararg columns: KProperty<*>, whereAllNA: Boolean = false): DataFrame<T>

fun <T> DataFrame<T>.~~dropNA~~(vararg columns: ColumnReference<*>, whereAllNA: Boolean = false): DataFrame<T>

Removes rows with NA values. Specific case of drop.

dropNaNs

fun <T> DataColumn<T>.dropNaNs(): DataColumn<T>

Removes NaN values from this DataColumn, adjusting the type accordingly.

fun <T> DataFrame<T>.dropNaNs(whereAllNaN: Boolean = false): DataFrame<T>

fun <T> DataFrame<T>.dropNaNs(whereAllNaN: Boolean = false, columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.dropNaNs(vararg columns: String, whereAllNaN: Boolean = false): DataFrame<T>

fun <T> DataFrame<T>.~~dropNaNs~~(vararg columns: KProperty<*>, whereAllNaN: Boolean = false): DataFrame<T>

fun <T> DataFrame<T>.~~dropNaNs~~(vararg columns: ColumnReference<*>, whereAllNaN: Boolean = false): DataFrame<T>

Removes rows with NaN values. Specific case of drop.

dropNulls

fun <T> DataColumn<T?>.dropNulls(): DataColumn<T>

Removes null values from this DataColumn, adjusting the type accordingly.

fun <T> DataFrame<T>.dropNulls(whereAllNull: Boolean = false): DataFrame<T>

fun <T> DataFrame<T>.dropNulls(whereAllNull: Boolean = false, columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.dropNulls(vararg columns: String, whereAllNull: Boolean = false): DataFrame<T>

fun <T> DataFrame<T>.~~dropNulls~~(vararg columns: KProperty<*>, whereAllNull: Boolean = false): DataFrame<T>

fun <T> DataFrame<T>.~~dropNulls~~(vararg columns: ColumnReference<*>, whereAllNull: Boolean = false): DataFrame<T>

Removes rows with null values. Specific case of drop.

dropWhile

inline fun <T> DataFrame<T>.dropWhile(predicate: RowFilter<T>): DataFrame<T>

Returns a DataFrame containing all rows except the first rows that satisfy the given predicate.

duplicate

fun <T> DataFrame<T>.duplicate(n: Int): FrameColumn<T>

Returns a FrameColumn that holds this DataFrame n times.

duplicateImpl

internal fun <T> DataFrame<T>.duplicateImpl(n: Int): FrameColumn<T>

duplicateRows

fun <T> DataFrame<T>.duplicateRows(n: Int): DataFrame<T>

Returns a DataFrame where every row is repeated n times.

inline fun <T> DataFrame<T>.duplicateRows(n: Int, filter: RowFilter<T>): DataFrame<T>

Returns a DataFrame where each row that matches the filter is repeated n times.

duplicateRowsImpl

internal fun <T> DataFrame<T>.duplicateRowsImpl(n: Int): DataFrame<T>

@PublishedApi

internal fun <T> DataFrame<T>.duplicateRowsImpl(n: Int, indicesSorted: Iterable<Int>): DataFrame<T>

duplicateValuesImpl

internal fun <T> DataColumn<T>.duplicateValuesImpl(n: Int): DataColumn<T>

internal fun <T> DataColumn<T>.duplicateValuesImpl(n: Int, indicesSorted: Iterable<Int>): DataColumn<T>

ensureIsColumnGroup

@PublishedApi

internal fun <C> SingleColumn<DataRow<C>>.ensureIsColumnGroup(): SingleColumn<DataRow<C>>

Checks the validity of this SingleColumn, by adding a check to see it's a ColumnGroup (so, a SingleColumn<*>) and throwing an IllegalArgumentException if it's not.

ensureIsFrameColumn

internal fun <C> SingleColumn<DataFrame<C>>.ensureIsFrameColumn(): SingleColumn<DataFrame<C>>

Checks the validity of this SingleColumn, by adding a check to see it's a FrameColumn (so, a SingleColumn<*>) and throwing an IllegalArgumentException if it's not.

ensureIsValueColumn

internal fun <C> SingleColumn<C>.ensureIsValueColumn(): SingleColumn<C>

Checks the validity of this SingleColumn, by adding a check to see it's a ValueColumn (so, a SingleColumn<*>) and throwing an IllegalArgumentException if it's not.

infix fun <T> DataColumn<T>.eq(value: T): DataColumn<Boolean>

Returns a DataColumn containing the results of comparing each element of this DataColumn with value for equality using the == operator.

infix fun <C> ColumnReference<C>.eq(value: C): ColumnReference<Boolean>

equals

open operator override fun equals(other: Any?): Boolean

exceptInternal

@JvmName(name = "exceptInternalSingleColumn")

internal fun <C> SingleColumn<DataRow<C>>.exceptInternal(other: ColumnsResolver<*>): SingleColumn<DataRow<C>>

Returns a new SingleColumn> that has the same structure as the receiver, but excludes columns specified in the "other" ColumnsResolver.

excludeJoin

fun <A, B> DataFrame<A>.excludeJoin(other: DataFrame, selector: JoinColumnsSelector<A, B>? = null): DataFrame<A>

fun <A, B> DataFrame<A>.excludeJoin(other: DataFrame, vararg columns: String): DataFrame<A>

Performs an exclude join of this DataFrame with the other DataFrame using the selected key columns. Includes only rows from the left DataFrame that do not have a match in the right one; right-side columns are not merged.

excludeJoinWith

fun <A, B> DataFrame<A>.excludeJoinWith(right: DataFrame, joinExpression: JoinExpression<A, B>): DataFrame<A>

Performs an exclude join of this DataFrame with the right DataFrame using the provided joinExpression. Includes only rows from the left DataFrame that do not have a match in the right one; right-side columns are not merged.

explode

@JvmName(name = "explodeList")

fun <T> DataColumn<Collection<T>>.explode(): DataColumn<T>

Splits list-like values in this DataColumn and spreads them vertically — that is, it adds a separate row for each element (one value per row).

@JvmName(name = "explodeFrames")

fun <T> DataColumn<DataFrame<T>>.explode(): ColumnGroup<T>

Explodes a DataColumn of DataFrame values into a single ColumnGroup.

fun <T> DataFrame<T>.explode(dropEmpty: Boolean = true, selector: ColumnsSelector<T, *> = defaultExplodeColumns): DataFrame<T>

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

fun <T> DataFrame<T>.explode(vararg columns: String, dropEmpty: Boolean = true): DataFrame<T>

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

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

explodeImpl

internal fun AnyCol.explodeImpl(): AnyCol

internal fun <T> DataFrame<T>.explodeImpl(dropEmpty: Boolean = true, columns: ColumnsSelector<T, *>): DataFrame<T>

extractDataFrame

internal fun <T> ColumnGroup<T>.extractDataFrame(): DataFrame<T>

extractJoinColumns

internal fun <C> ColumnsResolver<C>.extractJoinColumns(): List<ColumnMatch<C>>

extractSchema

internal fun AnyCol.extractSchema(): ColumnSchema

internal fun AnyFrame.extractSchema(): DataFrameSchema

fillNA

fun <T, C> DataFrame<T>.fillNA(columns: ColumnsSelector<T, C?>): Update<T, C?>

fun <T> DataFrame<T>.fillNA(vararg columns: String): Update<T, Any?>

fun <T, C> DataFrame<T>.~~fillNA~~(vararg columns: KProperty<C>): Update<T, C?>

fun <T, C> DataFrame<T>.~~fillNA~~(vararg columns: ColumnReference<C>): Update<T, C?>

Replaces NA values with the given value or expression. Specific case of update.

fillNaNs

fun <T, C> DataFrame<T>.fillNaNs(columns: ColumnsSelector<T, C>): Update<T, C>

fun <T> DataFrame<T>.fillNaNs(vararg columns: String): Update<T, Any?>

fun <T, C> DataFrame<T>.~~fillNaNs~~(vararg columns: KProperty<C>): Update<T, C>

fun <T, C> DataFrame<T>.~~fillNaNs~~(vararg columns: ColumnReference<C>): Update<T, C>

Replaces NaN values with the given value or expression. Specific case of update.

fillNulls

fun <T, C> DataFrame<T>.fillNulls(columns: ColumnsSelector<T, C?>): Update<T, C?>

fun <T> DataFrame<T>.fillNulls(vararg columns: String): Update<T, Any?>

fun <T, C> DataFrame<T>.~~fillNulls~~(vararg columns: KProperty<C>): Update<T, C?>

fun <T, C> DataFrame<T>.~~fillNulls~~(vararg columns: ColumnReference<C>): Update<T, C?>

Replaces null values with the given value or expression. Specific case of update.

filter

inline fun <T> DataColumn<T>.filter(predicate: Predicate<T>): DataColumn<T>

Returns a new DataColumn containing only the elements that match the given predicate.

inline fun <T> DataFrame<T>.filter(predicate: RowFilter<T>): DataFrame<T>

Filters the rows of this DataFrame based on the provided RowFilter. Returns a new DataFrame containing only the rows that satisfy the given predicate.

filterBy

fun <T> DataFrame<T>.~~filterBy~~(column: ColumnSelector<T, Boolean>): DataFrame<T>

fun <T> DataFrame<T>.~~filterBy~~(column: String): DataFrame<T>

fun <T> DataFrame<T>.~~filterBy~~(column: KProperty<Boolean>): DataFrame<T>

fun <T> DataFrame<T>.~~filterBy~~(column: ColumnReference<Boolean>): DataFrame<T>

filterJoin

fun <A, B> DataFrame<A>.filterJoin(other: DataFrame, selector: JoinColumnsSelector<A, B>? = null): DataFrame<A>

fun <A, B> DataFrame<A>.filterJoin(other: DataFrame, vararg columns: String): DataFrame<A>

Performs a filter join of this DataFrame with the other DataFrame using the selected key columns. Includes only rows from the left DataFrame that have a match in the right one; right-side columns are not merged.

filterJoinWith

fun <A, B> DataFrame<A>.filterJoinWith(right: DataFrame, joinExpression: JoinExpression<A, B>): DataFrame<A>

Performs a filter join of this DataFrame with the right DataFrame using the provided joinExpression. Includes only rows from the left DataFrame that have a match in the right one; right-side columns are not merged.

filterNotNull

fun <T> DataFrame<T>.~~filterNotNull~~(columns: ColumnsSelector<T, *>): DataFrame<T>

first

fun <T> DataColumn<T>.first(): T

Returns the first value in this DataColumn.

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

Returns the first row in this DataFrame.

fun <T> DataColumn<T>.first(predicate: (T) -> Boolean): T

Returns the first value in this DataColumn that matches the given predicate.

inline fun <T> DataFrame<T>.first(predicate: RowFilter<T>): DataRow<T>

Returns the first row in this DataFrame that satisfies the given predicate.

firstOrNull

fun <T> DataColumn<T>.firstOrNull(): T?

Returns the first value in this DataColumn. If the DataColumn is empty, returns null.

fun <T> DataFrame<T>.firstOrNull(): DataRow<T>?

Returns the first row in this DataFrame. If the DataFrame does not contain any rows, returns null.

fun <T> DataColumn<T>.firstOrNull(predicate: (T) -> Boolean): T?

Returns the first value in this DataColumn that matches the given predicate. Returns null if the DataColumn contains no elements matching the predicate (including the case when the DataColumn is empty).

inline fun <T> DataFrame<T>.firstOrNull(predicate: RowFilter<T>): DataRow<T>?

Returns the first row in this DataFrame that satisfies the given predicate. Returns null if the DataFrame contains no rows matching the predicate (including the case when the DataFrame is empty).

flatten

fun <T> DataFrame<T>.flatten(keepParentNameForColumns: Boolean = false, separator: String = "_"): DataFrame<T>

Removes all column groups in the DataFrame, replacing them with their leaf columns.

fun <T, C> DataFrame<T>.flatten(keepParentNameForColumns: Boolean = false, separator: String = "_", columns: ColumnsSelector<T, C>): DataFrame<T>

Removes specified column groups in the DataFrame, replacing them with their leaf columns.

fun <T> DataFrame<T>.flatten(vararg columns: String, keepParentNameForColumns: Boolean = false, separator: String = "_"): DataFrame<T>

fun <T, C> DataFrame<T>.~~flatten~~(vararg columns: KProperty<C>, keepParentNameForColumns: Boolean = false, separator: String = "_"): DataFrame<T>

fun <T, C> DataFrame<T>.~~flatten~~(vararg columns: ColumnReference<C>, keepParentNameForColumns: Boolean = false, separator: String = "_"): DataFrame<T>

Removes selected column groups in the DataFrame, replacing them with their leaf columns.

flattenImpl

internal fun <T, C> DataFrame<T>.flattenImpl(columns: ColumnsSelector<T, C>, keepParentNameForColumns: Boolean = false, separator: String = "_"): DataFrame<T>

flattenRecursively

internal fun ColumnsResolver<*>.flattenRecursively(includeGroups: Boolean = true, includeTopLevel: Boolean = true): ColumnsResolver<*>

Flattens a ColumnsResolver recursively.

forEach

inline fun <T> DataColumn<T>.forEach(action: (T) -> Unit)

Calls action for every value of this DataColumn, from the first one to the last one.

inline fun <T> DataFrame<T>.forEach(action: RowExpression<T, Unit>)

Calls action for every row of this DataFrame, from the first one to the last one.

forEachIndexed

inline fun <T> DataColumn<T>.forEachIndexed(action: (Int, T) -> Unit)

Calls action for every value of this DataColumn and its position, from the first value to the last one.

format

fun <T> DataFrame<T>.format(): FormatClause<T, Any?>

Formats the specified columns or cells within this dataframe such that they have specific CSS attributes applied to them when rendering the dataframe to HTML.

fun <T, C> DataFrame<T>.format(columns: ColumnsSelector<T, C>): FormatClause<T, C>

fun <T> DataFrame<T>.format(vararg columns: String): FormatClause<T, Any?>

Formats the specified columns or cells within this dataframe such that they have specific CSS attributes applied to them when rendering the dataframe to HTML.

fun <T, C> DataFrame<T>.~~format~~(vararg columns: KProperty<C>): FormatClause<T, C>

fun <T, C> DataFrame<T>.~~format~~(vararg columns: ColumnReference<C>): FormatClause<T, C>

formatHeader

fun <T> DataFrame<T>.formatHeader(): HeaderFormatClause<T, Any?>

fun <T, C> DataFrame<T>.formatHeader(columns: ColumnsSelector<T, C>): HeaderFormatClause<T, C>

fun <T> DataFrame<T>.formatHeader(vararg columns: String): HeaderFormatClause<T, Any?>

Experimental API. It may be changed in the future.

frameColumn

fun ColumnReference<DataRow<*>>.frameColumn(): ColumnDelegate<DataFrame<*>>

fun ColumnReference<DataRow<*>>.frameColumn(name: String): ColumnAccessor<DataFrame<*>>

fun <T> ColumnReference<DataRow<*>>.~~frameColumn~~(property: KProperty<List<T>>): ColumnAccessor<DataFrame<T>>

@JvmName(name = "frameColumnDataFrameKProperty")

fun <T> ColumnReference<DataRow<*>>.~~frameColumn~~(property: KProperty<DataFrame<T>>): ColumnAccessor<DataFrame<T>>

fun ColumnReference<DataRow<*>>.frameColumn(path: ColumnPath): ColumnAccessor<DataFrame<*>>

frameColumnsInternal

internal inline fun ColumnsResolver<*>.frameColumnsInternal(crossinline filter: (FrameColumn<*>) -> Boolean): TransformableColumnSet<AnyFrame>

Returns a TransformableColumnSet containing the frame columns that satisfy the given filter.

fullJoin

fun <A, B> DataFrame<A>.fullJoin(other: DataFrame, selector: JoinColumnsSelector<A, B>? = null): DataFrame<A>

fun <A, B> DataFrame<A>.fullJoin(other: DataFrame, vararg columns: String): DataFrame<A>

Performs a full join of this DataFrame with the other DataFrame using the selected key columns. Includes all rows from both DataFrames; matching rows are merged, all mismatches are filled with null.

fullJoinWith

fun <A, B> DataFrame<A>.fullJoinWith(right: DataFrame, joinExpression: JoinExpression<A, B>): DataFrame<A>

Performs a full join of this DataFrame with the right DataFrame using the provided joinExpression. Includes all rows from both DataFrames; matching rows are merged, all mismatches are filled with null.

gather

fun <T, C> DataFrame<T>.gather(selector: ColumnsSelector<T, C>): Gather<T, C, String, C>

Reshapes the DataFrame by gathering specified columns into two columns: keys and values (or into just one of them).

fun <T> DataFrame<T>.gather(vararg columns: String): Gather<T, Any?, String, Any?>

Reshapes the DataFrame by gathering specified columns into two columns: keys and values (or into just one of them).

fun <T, C> DataFrame<T>.~~gather~~(vararg columns: KProperty<C>): Gather<T, C, String, C>

fun <T, C> DataFrame<T>.~~gather~~(vararg columns: ColumnReference<C>): Gather<T, C, String, C>

generateCode

inline fun <reified T> DataFrame<T>.~~generateCode~~(fields: Boolean = true, extensionProperties: Boolean = true): CodeString

fun <T> DataFrame<T>.~~generateCode~~(markerName: String, fields: Boolean = true, extensionProperties: Boolean = true, visibility: MarkerVisibility = MarkerVisibility.IMPLICIT_PUBLIC): CodeString

generateDataClasses

inline fun <reified T> DataFrame<T>.generateDataClasses(extensionProperties: Boolean = false, visibility: MarkerVisibility = MarkerVisibility.IMPLICIT_PUBLIC, useFqNames: Boolean = false, nameNormalizer: NameNormalizer = NameNormalizer.default, nestedMarkerNameProvider: MarkerNameProvider = MarkerNameProvider.fromColumnName): CodeString

fun <T> DataFrame<T>.generateDataClasses(markerName: String, extensionProperties: Boolean = false, visibility: MarkerVisibility = MarkerVisibility.IMPLICIT_PUBLIC, useFqNames: Boolean = false, nameNormalizer: NameNormalizer = NameNormalizer.default, nestedMarkerNameProvider: MarkerNameProvider = MarkerNameProvider.fromColumnName): CodeString

Generates a CodeString containing generated @DataSchema data classes for the given DataFrame's schema (including all nested frame columns and column groups).

generateInterfaces

inline fun <reified T> DataFrame<T>.generateInterfaces(extensionProperties: Boolean = false, visibility: MarkerVisibility = MarkerVisibility.IMPLICIT_PUBLIC, useFqNames: Boolean = false, nameNormalizer: NameNormalizer = NameNormalizer.default, nestedMarkerNameProvider: MarkerNameProvider = MarkerNameProvider.fromColumnName): CodeString

fun <T> DataFrame<T>.generateInterfaces(markerName: String, extensionProperties: Boolean = false, visibility: MarkerVisibility = MarkerVisibility.IMPLICIT_PUBLIC, useFqNames: Boolean = false, nameNormalizer: NameNormalizer = NameNormalizer.default, nestedMarkerNameProvider: MarkerNameProvider = MarkerNameProvider.fromColumnName): CodeString

Generates a CodeString containing generated @DataSchema interfaces for the given DataFrame's schema (including all nested frame columns and column groups).

get

open override fun <C> get(column: ColumnSelector<T, C>): DataColumn<C>

open operator override fun <R> ~~get~~(column: KProperty<R>): DataColumn<R>

open operator override fun <R> ~~get~~(column: KProperty<DataFrame<R>>): FrameColumn<R>

open operator override fun <R> ~~get~~(column: KProperty<DataRow<R>>): ColumnGroup<R>

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

open operator override fun <R> ~~get~~(column: DataColumn<DataFrame<R>>): FrameColumn<R>

open operator override fun <R> ~~get~~(column: DataColumn<DataRow<R>>): ColumnGroup<R>

open operator override fun get(columnPath: ColumnPath): DataColumn<*>

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

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

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

open operator override fun get(first: IntRange, vararg ranges: IntRange): DataFrame<T>

open operator override fun get(row: AnyRow): DataRow<T>

open operator override fun get(columnName: String): DataColumn<*>

open override fun <C> get(columns: ColumnsSelector<T, C>): List<DataColumn<C>>

Returns a list of columns selected by columns, a ColumnsSelectionDsl.

open operator override fun get(index: Int): DataRow<T>

Gets the row at given index.

open operator override fun get(firstIndex: Int, vararg otherIndices: Int): ColumnGroup<T>

open operator override fun get(indices: Iterable<Int>): DataColumnGroup<T>

Gets the rows at given indices.

open operator override fun get(range: IntRange): DataColumnGroup<T>

Gets the rows at given range of indices.

get

operator fun <T, C> DataFrame<T>.get(columns: ColumnsSelector<T, C>): List<DataColumn<C>>

Returns a list of columns selected by columns, a ColumnsSelectionDsl.

operator fun <T> DataFrame<T>.get(columnRange: ClosedRange<String>): DataFrame<T>

operator fun <T> DataFrame<T>.get(first: String, vararg other: String): DataFrame<T>

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

getAggregateColumn

internal fun <T, C> DataFrame<T>.getAggregateColumn(selector: ColumnsForAggregateSelector<T, C>): AggregateColumnDescriptor<C>

getAggregateColumns

internal fun <T, C> DataFrame<T>.getAggregateColumns(selector: ColumnsForAggregateSelector<T, C>): List<AggregateColumnDescriptor<C>>

getAt

internal fun <T> ColumnsResolver<T>.getAt(index: Int): SingleColumn<T>

getColumn

fun <T, C> ColumnsContainer<T>.getColumn(selector: ColumnSelector<T, C>): DataColumn<C>

fun <T> ColumnsContainer<T>.getColumn(index: Int): DataColumn<*>

fun <T> ColumnsContainer<T>.getColumn(name: String): DataColumn<*>

fun <T> ColumnsContainer<T>.getColumn(path: ColumnPath): DataColumn<*>

fun <T, R> ColumnsContainer<T>.~~getColumn~~(column: ColumnReference<R>): DataColumn<R>

fun <T, R> ColumnsContainer<T>.~~getColumn~~(column: ColumnReference<DataFrame<R>>): FrameColumn<R>

fun <T, R> ColumnsContainer<T>.~~getColumn~~(column: ColumnReference<DataRow<R>>): ColumnGroup<R>

internal fun <C> ColumnsContainer<*>.getColumn(name: String, policy: UnresolvedColumnsPolicy): DataColumn<C>?

internal fun <C> ColumnsContainer<*>.getColumn(path: ColumnPath, policy: UnresolvedColumnsPolicy): DataColumn<C>?

getColumnGroup

fun <T, C> ColumnsContainer<T>.getColumnGroup(column: ColumnSelector<T, DataRow<C>>): ColumnGroup<C>

fun <T> ColumnsContainer<T>.getColumnGroup(index: Int): ColumnGroup<*>

fun <T> ColumnsContainer<T>.getColumnGroup(name: String): ColumnGroup<*>

fun <T> ColumnsContainer<T>.~~getColumnGroup~~(column: KProperty<*>): ColumnGroup<*>

fun <T> ColumnsContainer<T>.getColumnGroup(columnPath: ColumnPath): ColumnGroup<*>

fun <T, C> ColumnsContainer<T>.~~getColumnGroup~~(column: ColumnReference<DataRow<C>>): ColumnGroup<C>

getColumnGroupOrNull

fun <T> ColumnsContainer<T>.getColumnGroupOrNull(name: String): ColumnGroup<*>?

fun <T> ColumnsContainer<T>.~~getColumnGroupOrNull~~(column: KProperty<*>): ColumnGroup<*>?

getColumnIndex

open override fun getColumnIndex(name: String): Int

getColumnIndex

fun <T> DataFrame<T>.getColumnIndex(col: DataColumn<*>): Int

getColumnOrNull

open override fun <R> getColumnOrNull(column: ColumnSelector<T, R>): DataColumn<R>?

open override fun getColumnOrNull(index: Int): DataColumn<*>?

open override fun getColumnOrNull(name: String): DataColumn<*>?

open override fun <R> ~~getColumnOrNull~~(column: KProperty<R>): DataColumn<R>?

open override fun getColumnOrNull(path: ColumnPath): DataColumn<*>?

open override fun <R> ~~getColumnOrNull~~(column: ColumnReference<R>): DataColumn<R>?

getColumnPath

fun <T, C> DataFrame<T>.getColumnPath(selector: ColumnSelector<T, C>): ColumnPath

getColumnPaths

fun <T, C> DataFrame<T>.getColumnPaths(selector: ColumnsSelector<T, C>): List<ColumnPath>

internal fun <T, C> DataFrame<T>.getColumnPaths(unresolvedColumnsPolicy: UnresolvedColumnsPolicy, selector: ColumnsSelector<T, C>): List<ColumnPath>

getColumns

fun <T, C> DataFrame<T>.getColumns(selector: ColumnsSelector<T, C>): List<DataColumn<C>>

fun <T> DataFrame<T>.getColumns(vararg columns: String): List<DataColumn<*>>

getColumnsImpl

internal fun <T, C> DataFrame<T>.getColumnsImpl(unresolvedColumnsPolicy: UnresolvedColumnsPolicy, selector: ColumnsSelector<T, C>): List<DataColumn<C>>

getColumnsWithPaths

fun <T, C> DataFrame<T>.getColumnsWithPaths(selector: ColumnsSelector<T, C>): List<ColumnWithPath<C>>

internal fun <T, C> DataFrame<T>.getColumnsWithPaths(unresolvedColumnsPolicy: UnresolvedColumnsPolicy, selector: ColumnsSelector<T, C>): List<ColumnWithPath<C>>

getColumnWithPath

fun <T, C> DataFrame<T>.getColumnWithPath(selector: ColumnSelector<T, C>): ColumnWithPath<C>

getFrameColumn

fun <T> ColumnsContainer<T>.getFrameColumn(columnName: String): FrameColumn<*>

fun <T> ColumnsContainer<T>.getFrameColumn(columnPath: ColumnPath): FrameColumn<*>

getHashCode

internal fun AnyCol.getHashCode(): Int

getOrNull

fun <T> DataFrame<T>.getOrNull(index: Int): DataRow<T>?

getPivotColumnPaths

internal fun <T> DataFrame<T>.getPivotColumnPaths(columns: PivotColumnsSelector<T, *>): List<ColumnPath>

getPivotSequences

internal fun <T, C> DataFrame<T>.getPivotSequences(columns: PivotColumnsSelector<T, C>): List<List<PivotChainElement>>

getRows

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

fun <T> DataFrame<T>.getRows(range: IntRange): DataFrame<T>

getSortColumns

internal fun <T, C> DataFrame<T>.getSortColumns(columns: SortColumnsSelector<T, C>, unresolvedColumnsPolicy: UnresolvedColumnsPolicy): List<SortColumnDescriptor<*>>

getValue

open operator override fun getValue(thisRef: Any?, property: KProperty<*>): DataColumnGroup<T>

open override fun getValue(row: AnyRow): DataRow<T>

getValueOrNull

open override fun getValueOrNull(row: AnyRow): DataRow<T>?

group

fun <T, C> DataFrame<T>.group(columns: ColumnsSelector<T, C>): GroupClause<T, C>

fun <T> DataFrame<T>.group(vararg columns: String): GroupClause<T, Any?>

Groups the specified columns within the DataFrame into column group.

fun <T> DataFrame<T>.~~group~~(vararg columns: KProperty<*>): GroupClause<T, Any?>

fun <T> DataFrame<T>.~~group~~(vararg columns: ColumnReference<*>): GroupClause<T, Any?>

groupBy

fun <T> DataFrame<T>.groupBy(vararg cols: String): GroupBy<T, T>

fun <T> DataFrame<T>.groupBy(moveToTop: Boolean = true, cols: ColumnsSelector<T, *>): GroupBy<T, T>

Groups the rows of this DataFrame based on the values in one or more specified key columns. Each unique value in a key column — or a unique tuple of values for multiple columns — defines the group consisting of all rows where the column(s) contain that value combination.

fun <T> DataFrame<T>.~~groupBy~~(vararg cols: KProperty<*>): GroupBy<T, T>

fun <T> DataFrame<T>.~~groupBy~~(vararg cols: ColumnReference<*>, moveToTop: Boolean = true): GroupBy<T, T>

groupByImpl

@PublishedApi

internal fun <T> DataFrame<T>.groupByImpl(moveToTop: Boolean, columns: ColumnsSelector<T, *>): GroupBy<T, T>

grouped

internal fun <T> AnyCol.grouped(): ColumnGroup<T>

infix fun <T : Comparable<T>> DataColumn<T>.gt(value: T): DataColumn<Boolean>

Returns a DataColumn containing the results of comparing each element of this DataColumn with value using the > operator.

infix fun <C : Comparable<C>> ColumnReference<C>.gt(value: C): ColumnReference<Boolean>

hashCode

open override fun hashCode(): Int

hasNulls

open override fun hasNulls(): Boolean

head

fun <T> DataFrame<T>.head(numRows: Int = 5): DataFrame<T>

implode

fun <T> DataFrame<T>.implode(dropNA: Boolean = false): DataRow<T>

fun <T, C> DataFrame<T>.implode(dropNA: Boolean = false, columns: ColumnsSelector<T, C>): DataFrame<T>

fun <T> DataFrame<T>.implode(vararg columns: String, dropNA: Boolean = false): DataFrame<T>

fun <T, C> DataFrame<T>.~~implode~~(vararg columns: KProperty<C>, dropNA: Boolean = false): DataFrame<T>

fun <T, C> DataFrame<T>.~~implode~~(vararg columns: ColumnReference<C>, dropNA: Boolean = false): DataFrame<T>

implodeImpl

internal fun <T, C> DataFrame<T>.implodeImpl(dropNA: Boolean = false, columns: ColumnsSelector<T, C>): DataFrame<T>

indices

fun AnyBaseCol.indices(): IntRange

fun DataFrame<*>.indices(): IntRange

Returns the indices of all rows in this DataFrame, from 0 to the number of rows minus one, or an empty range if this DataFrame has no rows.

inline fun <T> DataFrame<T>.indices(filter: RowFilter<T>): List<Int>

Returns the indices of the rows in this DataFrame that satisfy the given filter.

inferType

fun DataColumn<*>.inferType(): DataColumn<*>

fun <T> DataFrame<T>.inferType(): DataFrame<T>

fun <T> DataFrame<T>.inferType(columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.inferType(vararg columns: String): DataFrame<T>

fun <T> DataFrame<T>.~~inferType~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~inferType~~(vararg columns: ColumnReference<*>): DataFrame<T>

innerJoin

fun <A, B> DataFrame<A>.innerJoin(other: DataFrame, selector: JoinColumnsSelector<A, B>? = null): DataFrame<A>

fun <A, B> DataFrame<A>.innerJoin(other: DataFrame, vararg columns: String): DataFrame<A>

Performs an inner join of this DataFrame with the other DataFrame using the selected key columns. Includes only matching rows from both DataFrames; rows are merged.

innerJoinWith

fun <A, B> DataFrame<A>.innerJoinWith(right: DataFrame, joinExpression: JoinExpression<A, B>): DataFrame<A>

Performs an inner join of this DataFrame with the right DataFrame using the provided joinExpression. Includes only matching rows from both DataFrames; rows are merged.

insert

fun <T, C> DataFrame<T>.insert(column: DataColumn<C>): InsertClause<T>

Inserts the given column into this DataFrame.

inline fun <T, reified R> DataFrame<T>.insert(name: String, infer: Infer = Infer.Nulls, noinline expression: AddExpression<T, R>): InsertClause<T>

Creates a new column using the provided expression and inserts it into this DataFrame.

inline fun <T, reified R> DataFrame<T>.~~insert~~(column: KProperty<R>, infer: Infer = Infer.Nulls, noinline expression: AddExpression<T, R>): InsertClause<T>

inline fun <T, reified R> DataFrame<T>.~~insert~~(column: ColumnAccessor<R>, infer: Infer = Infer.Nulls, noinline expression: AddExpression<T, R>): InsertClause<T>

insertImpl

@JvmName(name = "insertImplT")

internal fun <T> DataFrame<T>.insertImpl(columns: List<ColumnToInsert>): DataFrame<T>

@PublishedApi

internal fun <T> DataFrame<T>.insertImpl(path: ColumnPath, column: AnyCol): DataFrame<T>

internal

@PublishedApi

internal fun <T> Aggregatable<T>.internal(): AggregatableInternal<T>

internal fun <T> DataColumn<T>.internal(): DataColumnInternal<T>

intraComparableColumns

internal fun <T> Aggregatable<T>.intraComparableColumns(): ColumnsSelector<T, Comparable<Any>?>

Emulates selecting all columns whose values are mutually comparable to each other. These are columns of type R where R : Comparable<R>.

isColumnGroup

fun DataColumn<*>.isColumnGroup(): Boolean

Returns true if this column is a ColumnGroup, i.e., its kind is ColumnKind.Group.

isComparable

fun DataColumn<*>.~~isComparable~~(): Boolean

Returns true if this column is intra-comparable (mutually comparable), i.e., its values can be compared with each other and thus ordered.

isEmpty

fun DataFrame<*>.isEmpty(): Boolean

Returns true if this DataFrame has no rows or no columns.

isFrameColumn

fun DataColumn<*>.isFrameColumn(): Boolean

Returns true if this column is a FrameColumn, i.e., its kind is ColumnKind.Frame.

isList

fun DataColumn<*>.isList(): Boolean

Returns true when the class of this column's type is List, i.e., the column holds List<*> (or List<*>?) values.

isMissingColumn

internal fun AnyCol.isMissingColumn(): Boolean

isMixedNumber

fun DataColumn<*>.isMixedNumber(): Boolean

Returns true only when this column's type is exactly Number or Number?.

isNotEmpty

fun DataFrame<*>.isNotEmpty(): Boolean

Returns true if this DataFrame has at least one row and at least one column, that is, if it is not empty.

isNumber

fun DataColumn<*>.isNumber(): Boolean

Returns true when this column's type is a subtype of Number?

isPrimitiveNumber

fun DataColumn<*>.isPrimitiveNumber(): Boolean

Returns true when this column has the (nullable) type of either: Byte, Short, Int, Long, Float, or Double.

isPrimitiveOrMixedNumber

fun DataColumn<*>.isPrimitiveOrMixedNumber(): Boolean

Returns true when this column has the (nullable) type of either: Byte, Short, Int, Long, Float, Double, or Number.

isSubtypeOf

inline fun <reified T> DataColumn<*>.isSubtypeOf(): Boolean

Returns true if the type of this column is a subtype of T.

fun DataColumn<*>.isSubtypeOf(type: KType): Boolean

Returns true if the type of this column is a subtype of the given type.

isSuitableForCorr

internal fun AnyCol.isSuitableForCorr(): Boolean

isType

inline fun <reified T> DataColumn<*>.isType(): Boolean

Returns true only if the type of this column is exactly T.

isValueColumn

fun DataColumn<*>.isValueColumn(): Boolean

Returns true if this column is a ValueColumn, i.e., its kind is ColumnKind.Value.

iterator

open operator override fun iterator(): Iterator<DataRow<T>>

join

fun <A, B> DataFrame<A>.join(other: DataFrame, type: JoinType = JoinType.Inner, selector: JoinColumnsSelector<A, B>? = null): DataFrame<A>

fun <A, B> DataFrame<A>.join(other: DataFrame, vararg columns: String, type: JoinType = JoinType.Inner): DataFrame<A>

Joins this DataFrame with the other DataFrame using the selected key columns.

joinImpl

internal fun <A, B> DataFrame<A>.joinImpl(other: DataFrame, joinType: JoinType = JoinType.Inner, addNewColumns: Boolean = true, selector: JoinColumnsSelector<A, B>?): DataFrame<A>

joinWith

fun <A, B> DataFrame<A>.joinWith(right: DataFrame, type: JoinType = JoinType.Inner, joinExpression: JoinExpression<A, B>): DataFrame<A>

Joins this DataFrame with the right DataFrame using the provided joinExpression.

joinWithImpl

internal fun <A, B> DataFrame<A>.joinWithImpl(right: DataFrame, type: JoinType = JoinType.Inner, addNewColumns: Boolean, joinExpression: JoinExpression<A, B>): DataFrame<A>

kind

open override fun kind(): ColumnKind

last

fun <T> DataColumn<T>.last(): T

Returns the last value in this DataColumn.

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

Returns the last row in this DataFrame.

inline fun <T> DataColumn<T>.last(predicate: (T) -> Boolean): T

Returns the last value in this DataColumn that matches the given predicate.

inline fun <T> DataFrame<T>.last(predicate: RowFilter<T>): DataRow<T>

Returns the last row in this DataFrame that satisfies the given predicate.

lastOrNull

fun <T> DataColumn<T>.lastOrNull(): T?

Returns the last value in this DataColumn. If the DataColumn is empty, returns null.

fun <T> DataFrame<T>.lastOrNull(): DataRow<T>?

Returns the last row in this DataFrame. If the DataFrame does not contain any rows, returns null.

inline fun <T> DataColumn<T>.lastOrNull(predicate: (T) -> Boolean): T?

Returns the last value in this DataColumn that matches the given predicate. Returns null if the DataColumn contains no elements matching the predicate (including the case when the DataColumn is empty).

inline fun <T> DataFrame<T>.lastOrNull(predicate: RowFilter<T>): DataRow<T>?

Returns the last row in this DataFrame that satisfies the given predicate. Returns null if the DataFrame contains no rows matching the predicate (including the case when the DataFrame is empty).

leftJoin

fun <A, B> DataFrame<A>.leftJoin(other: DataFrame, selector: JoinColumnsSelector<A, B>? = null): DataFrame<A>

fun <A, B> DataFrame<A>.leftJoin(other: DataFrame, vararg columns: String): DataFrame<A>

Performs a left join of this DataFrame with the other DataFrame using the selected key columns. Includes all rows from the left DataFrame; matching rows are merged, unmatched right-side values are filled with null.

leftJoinWith

fun <A, B> DataFrame<A>.leftJoinWith(right: DataFrame, joinExpression: JoinExpression<A, B>): DataFrame<A>

Performs a left join of this DataFrame with the right DataFrame using the provided joinExpression. Includes all rows from the left DataFrame; matching rows are merged, unmatched right-side values are filled with null.

length

fun DataColumn<String?>.~~length~~(): DataColumn<Int>

fun ColumnReference<String?>.~~length~~(): ColumnReference<Int>

lowercase

fun DataColumn<String?>.~~lowercase~~(): DataColumn<String?>

fun ColumnReference<String?>.~~lowercase~~(): ColumnReference<String?>

infix fun <T : Comparable<T>> DataColumn<T>.lt(value: T): DataColumn<Boolean>

Returns a DataColumn containing the results of comparing each element of this DataColumn with value using the < operator.

infix fun <C : Comparable<C>> ColumnReference<C>.lt(value: C): ColumnReference<Boolean>

map

inline fun <T, R> DataFrame<T>.map(transform: RowExpression<T, R>): List<R>

Returns a List with the values that transform computes from the rows of this DataFrame.

inline fun <T, reified R> DataColumn<T>.map(infer: Infer = Infer.Nulls, transform: (T) -> R): DataColumn<R>

Returns a new DataColumn with the values that transform computes from the values of this column.

internal inline fun <C, reified R> ColumnReference<C>.~~map~~(infer: Infer = Infer.Nulls, noinline transform: (C) -> R): ColumnReference<R>

inline fun <T, R> DataColumn<T>.map(type: KType, infer: Infer = Infer.Nulls, transform: (T) -> R): DataColumn<R>

Returns a new DataColumn of the given type with the values that transform computes from the values of this column.

mapIndexed

inline fun <T, reified R> DataColumn<T>.mapIndexed(infer: Infer = Infer.Nulls, transform: (Int, T) -> R): DataColumn<R>

Returns a new DataColumn with the values that transform computes from the values of this column and their positions.

inline fun <T, R> DataColumn<T>.mapIndexed(type: KType, infer: Infer = Infer.Nulls, transform: (Int, T) -> R): DataColumn<R>

Returns a new DataColumn of the given type with the values that transform computes from the values of this column and their positions.

mapNotNullValues

@PublishedApi

internal fun <T, R> DataColumn<T?>.mapNotNullValues(transform: (T) -> R): DataColumn<R?>

mapToColumn

inline fun <T, reified R> ColumnsContainer<T>.~~mapToColumn~~(name: String, infer: Infer = Infer.Nulls, noinline body: AddExpression<T, R>): DataColumn<R>

Returns a new DataColumn with the given name and the values that body computes from the rows of this ColumnsContainer.

inline fun <T, reified R> ColumnsContainer<T>.~~mapToColumn~~(column: KProperty<R>, infer: Infer = Infer.Nulls, noinline body: AddExpression<T, R>): DataColumn<R>

inline fun <T, reified R> ColumnsContainer<T>.~~mapToColumn~~(column: ColumnReference<R>, infer: Infer = Infer.Nulls, noinline body: AddExpression<T, R>): DataColumn<R>

@PublishedApi

internal fun <T, R> ColumnsContainer<T>.mapToColumn(name: String, type: KType, infer: Infer = Infer.Nulls, body: AddExpression<T, R>): DataColumn<R>

fun <T, R> ColumnsContainer<T>.~~mapToColumn~~(column: KProperty<R>, type: KType, infer: Infer = Infer.Nulls, body: AddExpression<T, R>): DataColumn<R>

fun <T, R> ColumnsContainer<T>.~~mapToColumn~~(column: ColumnReference<R>, type: KType, infer: Infer = Infer.Nulls, body: AddExpression<T, R>): DataColumn<R>

inline fun <T, reified R> DataFrame<T>.mapToColumn(name: String, infer: Infer = Infer.Nulls, noinline body: AddExpression<T, R>): DataColumn<R>

Returns a new DataColumn with the given name and the values that body computes from the rows of this DataFrame.

mapToFrame

inline fun <T> DataFrame<T>.mapToFrame(body: AddDsl<T>.() -> Unit): DataFrame<*>

Returns a new DataFrame made of the columns described in body.

max

fun <T : Comparable<T>> DataColumn<T?>.max(skipNaN: Boolean = skipNaNDefault): T

Returns the maximum of the values in this DataColumn.

fun <T> DataFrame<T>.max(skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the maximum of the values of each suitable column of this DataFrame separately.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.max(skipNaN: Boolean = skipNaNDefault, columns: ColumnsSelector<T, C>): C & Any

fun <T> DataFrame<T>.max(vararg columns: String, skipNaN: Boolean = skipNaNDefault): Comparable<Any>

Returns a single maximum of all the values in the selected columns of this DataFrame.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~max~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): C & Any

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~max~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): C & Any

maxBy

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.maxBy(skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): T

Returns the first element of this DataColumn for which the given selector returns the maximum value.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.maxBy(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): DataRow<T>

Returns the first row of this DataFrame for which the given expression returns the maximum value.

fun <T> DataFrame<T>.maxBy(column: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the first row of this DataFrame that has the largest value in the column with the given name.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~maxBy~~(column: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~maxBy~~(column: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

maxByOrNull

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.maxByOrNull(skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): T?

Returns the first element of this DataColumn for which the given selector returns the maximum value, or null if there is nothing to compare.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.maxByOrNull(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): DataRow<T>?

Returns the first row of this DataFrame for which the given expression returns the maximum value, or null if there is nothing to compare.

fun <T> DataFrame<T>.maxByOrNull(column: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

Returns the first row of this DataFrame that has the largest value in the column with the given name, or null if there is nothing to compare.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~maxByOrNull~~(column: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~maxByOrNull~~(column: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

maxDepth

internal fun AnyFrame.maxDepth(startingAt: Int = 0): Int

Returns the depth of the most-nested column in this df/group, starting at 0

maxFor

fun <T, C : Comparable<*>?> DataFrame<T>.maxFor(skipNaN: Boolean = skipNaNDefault, columns: ColumnsForAggregateSelector<T, C>): DataRow<T>

fun <T> DataFrame<T>.maxFor(vararg columns: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the maximum of the values of each selected column of this DataFrame separately.

fun <T, C : Comparable<*>?> DataFrame<T>.~~maxFor~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

fun <T, C : Comparable<*>?> DataFrame<T>.~~maxFor~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

maxOf

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.maxOf(skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): R & Any

Returns the maximum of the values that the given selector returns for each element of this DataColumn.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.maxOf(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): C & Any

Returns the maximum of the values that the given expression returns for each row of this DataFrame.

maxOfOrNull

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.maxOfOrNull(skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): R?

Returns the maximum of the values that the given selector returns for each element of this DataColumn, or null if there is nothing to compare.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.maxOfOrNull(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): C?

Returns the maximum of the values that the given expression returns for each row of this DataFrame, or null if there is nothing to compare.

maxOrNull

fun <T : Comparable<T>> DataColumn<T?>.maxOrNull(skipNaN: Boolean = skipNaNDefault): T?

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

fun <T, C : Comparable<C & Any>?> DataFrame<T>.maxOrNull(skipNaN: Boolean = skipNaNDefault, columns: ColumnsSelector<T, C>): C?

fun <T> DataFrame<T>.maxOrNull(vararg columns: String, skipNaN: Boolean = skipNaNDefault): Comparable<Any>?

Returns a single maximum of all the values in the selected columns of this DataFrame, or null if there is nothing to compare.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~maxOrNull~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): C?

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~maxOrNull~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): C?

maxWidth

internal fun BaseColumn<*>.maxWidth(): Int

Returns the max number of columns needed to display this column flattened

mean

fun DataColumn<Number?>.mean(skipNaN: Boolean = skipNaNDefault): Double

Returns the mean of the values in this DataColumn, as a Double.

fun <T> DataFrame<T>.mean(skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the mean of the values of each suitable column of this DataFrame separately.

fun <T, C : Number?> DataFrame<T>.mean(skipNaN: Boolean = skipNaNDefault, columns: ColumnsSelector<T, C>): Double

fun <T> DataFrame<T>.mean(vararg columns: String, skipNaN: Boolean = skipNaNDefault): Double

Returns a single mean of means of the selected columns of this DataFrame, as a Double.

fun <T, C : Number?> DataFrame<T>.~~mean~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): Double

fun <T, C : Number?> DataFrame<T>.~~mean~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): Double

meanFor

fun <T, C : Number?> DataFrame<T>.meanFor(skipNaN: Boolean = skipNaNDefault, columns: ColumnsForAggregateSelector<T, C>): DataRow<T>

fun <T> DataFrame<T>.meanFor(vararg columns: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the mean of the values of each selected column of this DataFrame separately.

fun <T, C : Number?> DataFrame<T>.~~meanFor~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

fun <T, C : Number?> DataFrame<T>.~~meanFor~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

meanOf

inline fun <T, reified R : Number?> DataColumn<T>.meanOf(skipNaN: Boolean = skipNaNDefault, crossinline expression: (T) -> R): Double

Returns the mean of the values that the given expression returns for each element of this DataColumn, as a Double.

inline fun <T, reified D : Number?> DataFrame<T>.meanOf(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, D>): Double

Returns the mean of the values that the given expression returns for each row of this DataFrame, as a Double.

median

fun <T : Comparable<T & Any>?> DataColumn<T>.median(): T & Any

Returns the median of the comparable values in this DataColumn.

fun <T : Comparable<T & Any>?, Number?> DataColumn<T>.median(skipNaN: Boolean = skipNaNDefault): Double

Returns the median of the numbers in this DataColumn, as a Double.

fun <T> DataFrame<T>.median(skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the median of the values of each suitable column of this DataFrame separately.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.median(columns: ColumnsSelector<T, C>): C & Any

Returns a single median of all the comparable values in the selected columns of this DataFrame.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~median~~(vararg columns: KProperty<C>): C & Any

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~median~~(vararg columns: ColumnReference<C>): C & Any

fun <T, C : Comparable<C & Any>?, Number?> DataFrame<T>.~~median~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): Double

fun <T, C : Comparable<C & Any>?, Number?> DataFrame<T>.~~median~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): Double

fun <T, C : Number?, Comparable<C & Any>?> DataFrame<T>.median(skipNaN: Boolean = skipNaNDefault, columns: ColumnsSelector<T, C>): Double

Returns a single median of all the numbers in the selected columns of this DataFrame, as a Double.

fun <T> DataFrame<T>.median(vararg columns: String, skipNaN: Boolean = skipNaNDefault): Any

Returns a single median of all the values in the columns of this DataFrame with the given names.

medianBy

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.medianBy(skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): T

Returns the element of this DataColumn at the median of the values that the given selector returns for each element.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.medianBy(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): DataRow<T>

Returns the row of this DataFrame at the median of the values that the given expression returns for each row.

fun <T> DataFrame<T>.medianBy(column: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the row of this DataFrame at the median of the values in the column with the given name.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~medianBy~~(column: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~medianBy~~(column: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

medianByOrNull

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.medianByOrNull(skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): T?

Returns the element of this DataColumn at the median of the values that the given selector returns for each element, or null if there is nothing to compute the median of.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.medianByOrNull(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): DataRow<T>?

Returns the row of this DataFrame at the median of the values that the given expression returns for each row, or null if there is nothing to compute the median of.

fun <T> DataFrame<T>.medianByOrNull(column: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

Returns the row of this DataFrame at the median of the values in the column with the given name, or null if there is nothing to compute the median of.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~medianByOrNull~~(column: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~medianByOrNull~~(column: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

medianFor

fun <T, C : Comparable<*>?> DataFrame<T>.medianFor(skipNaN: Boolean = skipNaNDefault, columns: ColumnsForAggregateSelector<T, C>): DataRow<T>

fun <T> DataFrame<T>.medianFor(vararg columns: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the median of the values of each selected column of this DataFrame separately.

fun <T, C : Comparable<*>?> DataFrame<T>.~~medianFor~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

fun <T, C : Comparable<*>?> DataFrame<T>.~~medianFor~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

medianOf

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.medianOf(crossinline expression: (T) -> R): R & Any

Returns the median of the comparable values that the given expression returns for each element of this DataColumn.

inline fun <T, reified R : Comparable<R & Any>?> DataFrame<T>.medianOf(crossinline expression: RowExpression<T, R>): R & Any

Returns the median of the comparable values that the given expression returns for each row of this DataFrame.

inline fun <T, reified R : Comparable<R & Any>?, Number?> DataColumn<T>.medianOf(skipNaN: Boolean = skipNaNDefault, crossinline expression: (T) -> R): Double

Returns the median of the numbers that the given expression returns for each element of this DataColumn, as a Double.

inline fun <T, reified R : Comparable<R & Any>?, Number?> DataFrame<T>.medianOf(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, R>): Double

Returns the median of the numbers that the given expression returns for each row of this DataFrame, as a Double.

medianOfOrNull

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.medianOfOrNull(crossinline expression: (T) -> R): R?

Returns the median of the comparable values that the given expression returns for each element of this DataColumn, or null if there is nothing to compute the median of.

inline fun <T, reified R : Comparable<R & Any>?> DataFrame<T>.medianOfOrNull(crossinline expression: RowExpression<T, R>): R?

Returns the median of the comparable values that the given expression returns for each row of this DataFrame, or null if there is nothing to compute the median of.

inline fun <T, reified R : Comparable<R & Any>?, Number?> DataColumn<T>.medianOfOrNull(skipNaN: Boolean = skipNaNDefault, crossinline expression: (T) -> R): Double?

Returns the median of the numbers that the given expression returns for each element of this DataColumn, as a Double, or null if there is nothing to compute the median of.

inline fun <T, reified R : Comparable<R & Any>?, Number?> DataFrame<T>.medianOfOrNull(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, R>): Double?

Returns the median of the numbers that the given expression returns for each row of this DataFrame, as a Double, or null if there is nothing to compute the median of.

medianOrNull

fun <T : Comparable<T & Any>?> DataColumn<T>.medianOrNull(): T?

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

fun <T : Comparable<T & Any>?, Number?> DataColumn<T>.medianOrNull(skipNaN: Boolean = skipNaNDefault): Double?

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

fun <T, C : Comparable<C & Any>?> DataFrame<T>.medianOrNull(columns: ColumnsSelector<T, C>): C?

Returns a single median of all the comparable values in the selected columns of this DataFrame, or null if there is nothing to compute the median of.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~medianOrNull~~(vararg columns: KProperty<C>): C?

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~medianOrNull~~(vararg columns: ColumnReference<C>): C?

fun <T, C : Comparable<C & Any>?, Number?> DataFrame<T>.~~medianOrNull~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): Double?

fun <T, C : Comparable<C & Any>?, Number?> DataFrame<T>.~~medianOrNull~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): Double?

fun <T, C : Comparable<C & Any>?, Number?> DataFrame<T>.medianOrNull(skipNaN: Boolean = skipNaNDefault, columns: ColumnsSelector<T, C>): Double?

Returns a single median of all the numbers in the selected columns of this DataFrame, as a Double, or null if there is nothing to compute the median of.

fun <T> DataFrame<T>.medianOrNull(vararg columns: String, skipNaN: Boolean = skipNaNDefault): Any?

Returns a single median of all the values in the columns of this DataFrame with the given names, or null if there is nothing to compute the median of.

merge

fun <T, C> DataFrame<T>.merge(selector: ColumnsSelector<T, C>): Merge<T, C, List<C>>

fun <T> DataFrame<T>.merge(vararg columns: String): Merge<T, Any?, List<Any?>>

inline fun <T, reified C> DataFrame<T>.~~merge~~(vararg columns: KProperty<C>): Merge<T, C, List<C>>

inline fun <T, reified C> DataFrame<T>.~~merge~~(vararg columns: ColumnReference<C>): Merge<T, C, List<C>>

min

fun <T : Comparable<T>> DataColumn<T?>.min(skipNaN: Boolean = skipNaNDefault): T

Returns the minimum of the values in this DataColumn.

fun <T> DataFrame<T>.min(skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the minimum of the values of each suitable column of this DataFrame separately.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.min(skipNaN: Boolean = skipNaNDefault, columns: ColumnsSelector<T, C>): C & Any

fun <T> DataFrame<T>.min(vararg columns: String, skipNaN: Boolean = skipNaNDefault): Comparable<Any>

Returns a single minimum of all the values in the selected columns of this DataFrame.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~min~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): C & Any

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~min~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): C & Any

minBy

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.minBy(skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): T

Returns the first element of this DataColumn for which the given selector returns the minimum value.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.minBy(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): DataRow<T>

Returns the first row of this DataFrame for which the given expression returns the minimum value.

fun <T> DataFrame<T>.minBy(column: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the first row of this DataFrame that has the smallest value in the column with the given name.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~minBy~~(column: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~minBy~~(column: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

minByOrNull

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.minByOrNull(skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): T?

Returns the first element of this DataColumn for which the given selector returns the minimum value, or null if there is nothing to compare.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.minByOrNull(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): DataRow<T>?

Returns the first row of this DataFrame for which the given expression returns the minimum value, or null if there is nothing to compare.

fun <T> DataFrame<T>.minByOrNull(column: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

Returns the first row of this DataFrame that has the smallest value in the column with the given name, or null if there is nothing to compare.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~minByOrNull~~(column: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~minByOrNull~~(column: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

minFor

fun <T, C : Comparable<*>?> DataFrame<T>.minFor(skipNaN: Boolean = skipNaNDefault, columns: ColumnsForAggregateSelector<T, C>): DataRow<T>

fun <T> DataFrame<T>.minFor(vararg columns: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the minimum of the values of each selected column of this DataFrame separately.

fun <T, C : Comparable<*>?> DataFrame<T>.~~minFor~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

fun <T, C : Comparable<*>?> DataFrame<T>.~~minFor~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

minOf

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.minOf(skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): R & Any

Returns the minimum of the values that the given selector returns for each element of this DataColumn.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.minOf(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): C & Any

Returns the minimum of the values that the given expression returns for each row of this DataFrame.

minOfOrNull

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.minOfOrNull(skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): R?

Returns the minimum of the values that the given selector returns for each element of this DataColumn, or null if there is nothing to compare.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.minOfOrNull(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): C?

Returns the minimum of the values that the given expression returns for each row of this DataFrame, or null if there is nothing to compare.

minOrNull

fun <T : Comparable<T>> DataColumn<T?>.minOrNull(skipNaN: Boolean = skipNaNDefault): T?

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

fun <T, C : Comparable<C & Any>?> DataFrame<T>.minOrNull(skipNaN: Boolean = skipNaNDefault, columns: ColumnsSelector<T, C>): C?

fun <T> DataFrame<T>.minOrNull(vararg columns: String, skipNaN: Boolean = skipNaNDefault): Comparable<Any>?

Returns a single minimum of all the values in the selected columns of this DataFrame, or null if there is nothing to compare.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~minOrNull~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): C?

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~minOrNull~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): C?

minus

operator fun DataColumn<BigDecimal>.minus(value: BigDecimal): DataColumn<BigDecimal>

operator fun DataColumn<BigInteger>.minus(value: BigInteger): DataColumn<BigInteger>

operator fun DataColumn<Double>.minus(value: Double): DataColumn<Double>

@JvmName(name = "minusDouble")

operator fun DataColumn<Double>.minus(value: Int): DataColumn<Double>

@JvmName(name = "minusIntNullable")

operator fun DataColumn<Int?>.minus(value: Int): DataColumn<Int?>

@JvmName(name = "minusInt")

operator fun DataColumn<Int>.minus(value: Double): DataColumn<Double>

operator fun DataColumn<Int>.minus(value: Int): DataColumn<Int>

operator fun DataColumn<Long>.minus(value: Long): DataColumn<Long>

Returns a DataColumn where each element is the result of subtracting value from the corresponding element of this DataColumn.

infix operator fun <T> DataFrame<T>.~~minus~~(columns: ColumnsSelector<T, *>): DataFrame<T>

infix operator fun <T> DataFrame<T>.~~minus~~(column: String): DataFrame<T>

infix operator fun <T> DataFrame<T>.~~minus~~(columns: KProperty<*>): DataFrame<T>

infix operator fun <T> DataFrame<T>.~~minus~~(column: ColumnReference<*>): DataFrame<T>

operator fun ColumnReference<Int>.minus(value: Int): ColumnReference<Int>

Returns a ColumnReference where each element is the result of subtracting value from the corresponding element of this ColumnReference.

move

fun <T, C> DataFrame<T>.move(columns: ColumnsSelector<T, C>): MoveClause<T, C>

fun <T> DataFrame<T>.move(vararg columns: String): MoveClause<T, Any?>

Moves the specified columns within the DataFrame.

fun <T, C> DataFrame<T>.~~move~~(vararg columns: KProperty<C>): MoveClause<T, C>

fun <T, C> DataFrame<T>.~~move~~(vararg columns: ColumnReference<C>): MoveClause<T, C>

moveTo

fun <T> DataFrame<T>.moveTo(newColumnIndex: Int, columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.moveTo(newColumnIndex: Int, vararg columns: String): DataFrame<T>

Moves the specified columns to a new position specified by newColumnIndex within the DataFrame.

fun <T> DataFrame<T>.~~moveTo~~(newColumnIndex: Int, vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~moveTo~~(newColumnIndex: Int, vararg columns: ColumnReference<*>): DataFrame<T>

fun <T> DataFrame<T>.moveTo(newColumnIndex: Int, insideGroup: Boolean, columns: ColumnsSelector<T, *>): DataFrame<T>

Moves the specified columns to a new position specified by newColumnIndex. If insideGroup is true selected columns will be moved remaining within their ColumnGroup, else they will be moved to the top level.

moveToEnd

fun <T> DataFrame<T>.moveToEnd(columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.moveToEnd(vararg columns: String): DataFrame<T>

fun <T> DataFrame<T>.moveToEnd(insideGroup: Boolean, columns: ColumnsSelector<T, *>): DataFrame<T>

Moves the specified columns to the DataFrame end. Returns a new DataFrame with an updated column structure.

fun <T> DataFrame<T>.~~moveToEnd~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~moveToEnd~~(vararg columns: ColumnReference<*>): DataFrame<T>

moveToLeft

fun <T> DataFrame<T>.~~moveToLeft~~(columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.~~moveToLeft~~(vararg columns: String): DataFrame<T>

fun <T> DataFrame<T>.~~moveToLeft~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~moveToLeft~~(vararg columns: ColumnReference<*>): DataFrame<T>

moveToRight

fun <T> DataFrame<T>.~~moveToRight~~(columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.~~moveToRight~~(vararg columns: String): DataFrame<T>

fun <T> DataFrame<T>.~~moveToRight~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~moveToRight~~(vararg columns: ColumnReference<*>): DataFrame<T>

moveToStart

fun <T> DataFrame<T>.moveToStart(columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.moveToStart(vararg columns: String): DataFrame<T>

fun <T> DataFrame<T>.moveToStart(insideGroup: Boolean, columns: ColumnsSelector<T, *>): DataFrame<T>

Moves the specified columns to the DataFrame start (on top-level). Returns a new DataFrame with an updated column structure.

fun <T> DataFrame<T>.~~moveToStart~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~moveToStart~~(vararg columns: ColumnReference<*>): DataFrame<T>

name

open override fun name(): String

nameGenerator

internal fun AnyFrame.nameGenerator(): ColumnNameGenerator

neq

infix fun <T> DataColumn<T>.neq(value: T): DataColumn<Boolean>

Returns a DataColumn containing the results of comparing each element of this DataColumn with value for inequality using the != operator.

infix fun <C> ColumnReference<C>.~~neq~~(value: C): ColumnReference<Boolean>

newColumn

@PublishedApi

internal fun <T, R> ColumnsContainer<T>.newColumn(type: KType, name: String = "", infer: Infer = Infer.Nulls, expression: AddExpression<T, R>): DataColumn<R>

newColumnWithActualType

@PublishedApi

internal fun <T, R> ColumnsContainer<T>.newColumnWithActualType(name: String, expression: AddExpression<T, R>): DataColumn<R>

none

fun <T> DataColumn<T>.none(predicate: Predicate<T>): Boolean

Returns true if none of the values match the given predicate.

inline fun <T> DataFrame<T>.none(predicate: RowFilter<T>): Boolean

Returns true if none of the rows in this DataFrame satisfies the given predicate.

not

@JvmName(name = "notBooleanNullable")

operator fun DataColumn<Boolean?>.not(): DataColumn<Boolean?>

Returns a DataColumn containing the inverse Boolean values of this DataColumn. Each null value in the original DataColumn is preserved.

operator fun DataColumn<Boolean>.not(): DataColumn<Boolean>

Returns a DataColumn containing the inverse Boolean values of this DataColumn.

@JvmName(name = "notBooleanNullable")

operator fun ColumnReference<Boolean?>.not(): ColumnReference<Boolean?>

Returns a ColumnReference containing the inverse Boolean values of this ColumnReference. Each null value in the original ColumnReference is preserved.

operator fun ColumnReference<Boolean>.not(): ColumnReference<Boolean>

Returns a ColumnReference containing the inverse Boolean values of this ColumnReference.

numberColumns

internal fun <T> Aggregatable<T>.numberColumns(): ColumnsSelector<T, Number?>

onResolve

internal fun <A> SingleColumn<A>.onResolve(check: (ColumnWithPath<A>?) -> Unit): SingleColumn<A>

Helper function to perform runtime checks on a SingleColumn.

parse

@JvmName(name = "parseChar")

fun DataColumn<Char?>.parse(options: ParserOptions? = null): DataColumn<*>

Tries to parse a column of chars as strings into a column of a different type. Each parser in Parsers is run in order until a valid parser is found, a.k.a. that parser was able to parse all values in the column successfully. If a parser fails to parse any value, the next parser is tried.

fun DataColumn<String?>.parse(options: ParserOptions? = null): DataColumn<*>

Tries to parse a column of strings into a column of a different type. Each parser in Parsers is run in order until a valid parser is found, a.k.a. that parser was able to parse all values in the column successfully. If a parser fails to parse any value, the next parser is tried.

@JvmName(name = "parseAnyFrameNullable")

fun DataColumn<DataFrame<*>?>.parse(options: ParserOptions? = null): DataColumn<DataFrame<*>?>

fun <T> DataFrame<T>.parse(options: ParserOptions? = null): DataFrame<T>

fun <T> DataFrame<T>.parse(options: ParserOptions? = null, columns: ColumnsSelector<T, Any?>): DataFrame<T>

fun <T> DataFrame<T>.parse(vararg columns: String, options: ParserOptions? = null): DataFrame<T>

fun <T, C> DataFrame<T>.~~parse~~(vararg columns: KProperty<C>, options: ParserOptions? = null): DataFrame<T>

fun <T, C> DataFrame<T>.~~parse~~(vararg columns: ColumnReference<C>, options: ParserOptions? = null): DataFrame<T>

internal fun <T> DataColumn<String?>.parse(parser: StringParser<T>, options: ParserOptions?): DataColumn<T?>

parseImpl

internal fun <T> DataFrame<T>.parseImpl(options: ParserOptions?, columns: ColumnsSelector<T, Any?>): DataFrame<T>

path

open override fun path(): ColumnPath

percentile

fun <T : Comparable<T & Any>?> DataColumn<T>.percentile(percentile: Double): T & Any

Returns the given percentile of the comparable values in this DataColumn.

fun <T : Comparable<T & Any>?, Number?> DataColumn<T>.percentile(percentile: Double, skipNaN: Boolean = skipNaNDefault): Double

Returns the given percentile of the numbers in this DataColumn, as a Double.

fun <T> DataFrame<T>.percentile(percentile: Double, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the given percentile of the values of each suitable column of this DataFrame separately.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.percentile(percentile: Double, columns: ColumnsSelector<T, C>): C & Any

Returns a single percentile of all the comparable values in the selected columns of this DataFrame.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~percentile~~(percentile: Double, vararg columns: KProperty<C>): C & Any

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~percentile~~(percentile: Double, vararg columns: ColumnReference<C>): C & Any

fun <T, C : Comparable<C & Any>?, Number?> DataFrame<T>.~~percentile~~(percentile: Double, vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): Double

fun <T, C : Comparable<C & Any>?, Number?> DataFrame<T>.~~percentile~~(percentile: Double, vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): Double

fun <T, C : Number?, Comparable<C & Any>?> DataFrame<T>.percentile(percentile: Double, skipNaN: Boolean = skipNaNDefault, columns: ColumnsSelector<T, C>): Double

Returns a single percentile of all the numbers in the selected columns of this DataFrame, as a Double.

fun <T> DataFrame<T>.percentile(percentile: Double, vararg columns: String, skipNaN: Boolean = skipNaNDefault): Any

Returns a single percentile of all the values in the columns of this DataFrame with the given names.

percentileBy

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.percentileBy(percentile: Double, skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): T

Returns the element of this DataColumn at the given percentile of the values that the given selector returns for each element.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.percentileBy(percentile: Double, skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): DataRow<T>

Returns the row of this DataFrame at the given percentile of the values that the given expression returns for each row.

fun <T> DataFrame<T>.percentileBy(percentile: Double, column: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the row of this DataFrame at the given percentile of the values in the column with the given name.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~percentileBy~~(percentile: Double, column: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~percentileBy~~(percentile: Double, column: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

percentileByOrNull

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.percentileByOrNull(percentile: Double, skipNaN: Boolean = skipNaNDefault, crossinline selector: (T) -> R): T?

Returns the element of this DataColumn at the given percentile of the values that the given selector returns for each element, or null if there is nothing to compute the percentile of.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.percentileByOrNull(percentile: Double, skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): DataRow<T>?

Returns the row of this DataFrame at the given percentile of the values that the given expression returns for each row, or null if there is nothing to compute the percentile of.

fun <T> DataFrame<T>.percentileByOrNull(percentile: Double, column: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

Returns the row of this DataFrame at the given percentile of the values in the column with the given name, or null if there is nothing to compute the percentile of.

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~percentileByOrNull~~(percentile: Double, column: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

inline fun <T, reified C : Comparable<C & Any>?> DataFrame<T>.~~percentileByOrNull~~(percentile: Double, column: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>?

percentileFor

fun <T, C : Comparable<*>?> DataFrame<T>.percentileFor(percentile: Double, skipNaN: Boolean = skipNaNDefault, columns: ColumnsForAggregateSelector<T, C>): DataRow<T>

fun <T> DataFrame<T>.percentileFor(percentile: Double, vararg columns: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the given percentile of the values of each selected column of this DataFrame separately.

fun <T, C : Comparable<*>?> DataFrame<T>.~~percentileFor~~(percentile: Double, vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

fun <T, C : Comparable<*>?> DataFrame<T>.~~percentileFor~~(percentile: Double, vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

percentileOf

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.percentileOf(percentile: Double, crossinline expression: (T) -> R): R & Any

Returns the given percentile of the comparable values that the given expression returns for each element of this DataColumn.

inline fun <T, reified R : Comparable<R & Any>?> DataFrame<T>.percentileOf(percentile: Double, crossinline expression: RowExpression<T, R>): R & Any

Returns the given percentile of the comparable values that the given expression returns for each row of this DataFrame.

inline fun <T, reified R : Comparable<R & Any>?, Number?> DataColumn<T>.percentileOf(percentile: Double, skipNaN: Boolean = skipNaNDefault, crossinline expression: (T) -> R): Double

Returns the given percentile of the numbers that the given expression returns for each element of this DataColumn, as a Double.

inline fun <T, reified R : Comparable<R & Any>?, Number?> DataFrame<T>.percentileOf(percentile: Double, skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, R>): Double

Returns the given percentile of the numbers that the given expression returns for each row of this DataFrame, as a Double.

percentileOfOrNull

inline fun <T, reified R : Comparable<R & Any>?> DataColumn<T>.percentileOfOrNull(percentile: Double, crossinline expression: (T) -> R): R?

Returns the given percentile of the comparable values that the given expression returns for each element of this DataColumn, or null if there is nothing to compute the percentile of.

inline fun <T, reified R : Comparable<R & Any>?> DataFrame<T>.percentileOfOrNull(percentile: Double, crossinline expression: RowExpression<T, R>): R?

Returns the given percentile of the comparable values that the given expression returns for each row of this DataFrame, or null if there is nothing to compute the percentile of.

inline fun <T, reified R : Comparable<R & Any>?, Number?> DataColumn<T>.percentileOfOrNull(percentile: Double, skipNaN: Boolean = skipNaNDefault, crossinline expression: (T) -> R): Double?

Returns the given percentile of the numbers that the given expression returns for each element of this DataColumn, as a Double, or null if there is nothing to compute the percentile of.

inline fun <T, reified R : Comparable<R & Any>?, Number?> DataFrame<T>.percentileOfOrNull(percentile: Double, skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, R>): Double?

Returns the given percentile of the numbers that the given expression returns for each row of this DataFrame, as a Double, or null if there is nothing to compute the percentile of.

percentileOrNull

fun <T : Comparable<T & Any>?> DataColumn<T>.percentileOrNull(percentile: Double): T?

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

fun <T : Comparable<T & Any>?, Number?> DataColumn<T>.percentileOrNull(percentile: Double, skipNaN: Boolean = skipNaNDefault): Double?

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

fun <T, C : Comparable<C & Any>?> DataFrame<T>.percentileOrNull(percentile: Double, columns: ColumnsSelector<T, C>): C?

Returns a single percentile of all the comparable values in the selected columns of this DataFrame, or null if there is nothing to compute the percentile of.

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~percentileOrNull~~(percentile: Double, vararg columns: KProperty<C>): C?

fun <T, C : Comparable<C & Any>?> DataFrame<T>.~~percentileOrNull~~(percentile: Double, vararg columns: ColumnReference<C>): C?

fun <T, C : Comparable<C & Any>?, Number?> DataFrame<T>.~~percentileOrNull~~(percentile: Double, vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): Double?

fun <T, C : Comparable<C & Any>?, Number?> DataFrame<T>.~~percentileOrNull~~(percentile: Double, vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): Double?

fun <T, C : Comparable<C & Any>?, Number?> DataFrame<T>.percentileOrNull(percentile: Double, skipNaN: Boolean = skipNaNDefault, columns: ColumnsSelector<T, C>): Double?

Returns a single percentile of all the numbers in the selected columns of this DataFrame, as a Double, or null if there is nothing to compute the percentile of.

fun <T> DataFrame<T>.percentileOrNull(percentile: Double, vararg columns: String, skipNaN: Boolean = skipNaNDefault): Any?

Returns a single percentile of all the values in the columns of this DataFrame with the given names, or null if there is nothing to compute the percentile of.

pivot

fun <T> DataFrame<T>.pivot(inward: Boolean? = null, columns: PivotColumnsSelector<T, *>): Pivot<T>

fun <T> DataFrame<T>.pivot(vararg columns: String, inward: Boolean? = null): Pivot<T>

Splits the rows of this DataFrame and groups them horizontally into new columns based on values from one or several provided columns of the original DataFrame.

fun <T> DataFrame<T>.~~pivot~~(vararg columns: KProperty<*>, inward: Boolean? = null): Pivot<T>

fun <T> DataFrame<T>.~~pivot~~(vararg columns: ColumnReference<*>, inward: Boolean? = null): Pivot<T>

pivotCounts

fun <T> DataFrame<T>.pivotCounts(inward: Boolean = true, columns: PivotColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.pivotCounts(vararg columns: String, inward: Boolean = true): DataFrame<T>

Computes a count matrix (similar to frequency encoding) for the values in the specified columns of this DataFrame, returning a new DataFrame where:

fun <T> DataFrame<T>.~~pivotCounts~~(vararg columns: KProperty<*>, inward: Boolean = true): DataFrame<T>

fun <T> DataFrame<T>.~~pivotCounts~~(vararg columns: ColumnReference<*>, inward: Boolean = true): DataFrame<T>

pivotMatches

fun <T> DataFrame<T>.pivotMatches(inward: Boolean = true, columns: PivotColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.pivotMatches(vararg columns: String, inward: Boolean = true): DataFrame<T>

Computes a presence matrix (similar to one-hot encoding) for the values in the specified columns of this DataFrame, returning a new DataFrame where:

fun <T> DataFrame<T>.~~pivotMatches~~(vararg columns: KProperty<*>, inward: Boolean = true): DataFrame<T>

fun <T> DataFrame<T>.~~pivotMatches~~(vararg columns: ColumnReference<*>, inward: Boolean = true): DataFrame<T>

plus

open operator override fun plus(cols: Iterable<AnyBaseCol>): DataFrame<T>

open operator override fun plus(col: AnyBaseCol): DataFrame<T>

plus

operator fun DataColumn<*>.plus(str: String): DataColumn<String>

Returns a DataColumn of String values obtained by converting each element of this AnyCol to a String and concatenating it with str.

operator fun DataColumn<BigDecimal>.plus(value: BigDecimal): DataColumn<BigDecimal>

operator fun DataColumn<BigInteger>.plus(value: BigInteger): DataColumn<BigInteger>

operator fun DataColumn<Double>.plus(value: Double): DataColumn<Double>

@JvmName(name = "plusDouble")

operator fun DataColumn<Double>.plus(value: Int): DataColumn<Double>

@JvmName(name = "plusIntNullable")

operator fun DataColumn<Int?>.plus(value: Int): DataColumn<Int?>

@JvmName(name = "plusInt")

operator fun DataColumn<Int>.plus(value: Double): DataColumn<Double>

operator fun DataColumn<Int>.plus(value: Int): DataColumn<Int>

operator fun DataColumn<Long>.plus(value: Long): DataColumn<Long>

Returns a DataColumn where each element is the result of adding value to the corresponding element of this DataColumn.

operator fun ColumnReference<Any?>.plus(str: String): ColumnReference<String>

Returns a ColumnReference of String values obtained by converting each element of this ColumnReference to a String and concatenating it with str.

operator fun ColumnReference<Int>.plus(value: Int): ColumnReference<Int>

Returns a ColumnReference where each element is the result of adding value to the corresponding element of this ColumnReference.

prepareTable

internal fun AnyFrame.prepareTable(rowsLimit: Int?, valueLimit: Int?, columnTypes: Boolean, rowIndex: Boolean, escapeValue: (String) -> String = { it }): PreparedTable

primitiveOrMixedNumberColumns

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

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

fun <T> DataFrame<T>.print(rowsLimit: Int? = 20, valueLimit: Int? = 40, borders: Boolean = false, alignLeft: Boolean = false, columnTypes: Boolean = true, title: Boolean = false, rowIndex: Boolean = true, borderStyle: StringBorderStyle = StringBorderStyle.DottedLineWithRounderCorners)

properties

fun <T> DataFrame<T>.properties(): ColumnsScope<T>

Utility property to access scope with only dataframe column properties for code completion, filtering out DataFrame API.

remainingColumns

internal inline fun <T> Aggregatable<T>.remainingColumns(crossinline predicate: (AnyCol) -> Boolean): ColumnsSelector<T, Any?>

remainingColumnsSelector

internal fun <T> Aggregatable<T>.remainingColumnsSelector(): ColumnsSelector<*, *>

remove

fun <T> DataFrame<T>.remove(columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.remove(vararg columns: String): DataFrame<T>

fun <T> DataFrame<T>.~~remove~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~remove~~(vararg columns: ColumnReference<*>): DataFrame<T>

Removes the specified columns from the original DataFrame and returns a new DataFrame without them.

removeImpl

internal fun <T> DataFrame<T>.removeImpl(allowMissingColumns: Boolean = false, columns: ColumnsSelector<T, *>): RemoveResult<T>

rename

open override fun rename(newName: String): ResolvingColumnGroup<T>

rename

fun <T, C> DataFrame<T>.rename(columns: ColumnsSelector<T, C>): RenameClause<T, C>

Renames the specified columns keeping their original values and location within the DataFrame.

fun <T> DataFrame<T>.rename(vararg mappings: Pair<String, String>): DataFrame<T>

Renames columns in the DataFrame.

fun <T> DataFrame<T>.rename(vararg cols: String): RenameClause<T, Any?>

Renames the specified columns keeping their original values and location within the DataFrame.

fun <T, C> DataFrame<T>.~~rename~~(vararg cols: KProperty<C>): RenameClause<T, C>

fun <T, C> DataFrame<T>.~~rename~~(vararg cols: ColumnReference<C>): RenameClause<T, C>

renamedColumn

internal fun <C> SingleColumn<C>.renamedColumn(newName: String): SingleColumn<C>

renamedReference

internal fun <C> ColumnReference<C>.renamedReference(newName: String): ColumnReference<C>

renameToCamelCase

fun <T> DataFrame<T>.renameToCamelCase(): DataFrame<T>

Renames all columns in this DataFrame to the "camelCase" format.

render

internal fun DataFrame<ValueCount>.render(): List<Counts>

renderShort

internal fun AnyCol.renderShort(): String

renderToMarkdown

fun AnyFrame.renderToMarkdown(rowsLimit: Int? = 20, valueLimit: Int? = 40, alignment: MarkdownAlignment = MarkdownAlignment.UNSPECIFIED, columnTypes: Boolean = false, title: Boolean = false, rowIndex: Boolean = true): String

renderToString

fun AnyFrame.renderToString(rowsLimit: Int? = 20, valueLimit: Int? = 40, borders: Boolean = false, alignLeft: Boolean = false, columnTypes: Boolean = true, title: Boolean = false, rowIndex: Boolean = true, borderStyle: StringBorderStyle = StringBorderStyle.DottedLineWithRounderCorners): String

reorder

fun <T, C> DataFrame<T>.reorder(selector: ColumnsSelector<T, C>): Reorder<T, C>

fun <T> DataFrame<T>.reorder(vararg columns: String): Reorder<T, *>

Reorders the selected columns of the DataFrame.

fun <T, C> DataFrame<T>.~~reorder~~(vararg columns: KProperty<C>): Reorder<T, C>

fun <T, C> DataFrame<T>.~~reorder~~(vararg columns: ColumnReference<C>): Reorder<T, C>

reorderColumnsBy

fun <T, V : Comparable<V>> DataFrame<T>.reorderColumnsBy(atAnyDepth: Boolean = true, desc: Boolean = false, expression: Selector<DataColumn<*>, V>): DataFrame<T>

fun <T, V : Comparable<V>> DataFrame<T>.reorderColumnsBy(atAnyDepth: Boolean = true, desc: Boolean = false, inFrameColumns: Boolean, expression: Selector<DataColumn<*>, V>): DataFrame<T>

Puts all columns of the DataFrame in order of the value of the expression and returns a new DataFrame.

reorderColumnsByName

fun <T> DataFrame<T>.reorderColumnsByName(atAnyDepth: Boolean = true, desc: Boolean = false): DataFrame<T>

fun <T> DataFrame<T>.reorderColumnsByName(atAnyDepth: Boolean = true, desc: Boolean = false, inFrameColumns: Boolean): DataFrame<T>

Puts all columns of the DataFrame in lexicographic order of their names and returns a new DataFrame.

replace

fun <T, C> DataFrame<T>.replace(columns: ColumnsSelector<T, C>): ReplaceClause<T, C>

fun <T> DataFrame<T>.replace(vararg columns: String): ReplaceClause<T, Any?>

fun <T, C> DataFrame<T>.~~replace~~(vararg columns: KProperty<C>): ReplaceClause<T, C>

fun <T, C> DataFrame<T>.~~replace~~(vararg columns: ColumnReference<C>): ReplaceClause<T, C>

replaceAll

fun <T> DataFrame<T>.replaceAll(vararg valuePairs: Pair<Any?, Any?>, columns: ColumnsSelector<T, *> = { colsAtAnyDepth().filter { !it.isColumnGroup() } }): DataFrame<T>

requireColumn

inline fun <T, reified C> DataFrame<T>.requireColumn(noinline column: ColumnSelector<T, C>): DataFrame<T>

Resolves column in this DataFrame and checks that its runtime type is a subtype of C. Throws if the column can't be resolved or if its type doesn't match.

requireImpl

@PublishedApi

internal fun <T, C> DataFrame<T>.requireImpl(column: ColumnSelector<T, C>, type: KType): DataFrame<T>

resolve

open override fun resolve(context: ColumnResolutionContext): List<ColumnWithPath<DataRow<T>>>

Resolves this ColumnsResolver as a List<ColumnWithPath<C>>. In many cases this function transforms a parent ColumnsResolver to reach the current ColumnsResolver result.

resolve

internal fun <C> ColumnsResolver<C>.resolve(df: DataFrame<*>, unresolvedColumnsPolicy: UnresolvedColumnsPolicy = UnresolvedColumnsPolicy.Fail): List<ColumnWithPath<C>>

resolveFor

internal fun <C> ColumnReference<C>.resolveFor(df: AnyFrame): ColumnWithPath<C>?

resolveSingle

open override fun resolveSingle(context: ColumnResolutionContext): ColumnWithPath<DataRow<T>>?

resolveSingle

internal fun <C> SingleColumn<C>.resolveSingle(df: DataFrame<*>, unresolvedColumnsPolicy: UnresolvedColumnsPolicy = UnresolvedColumnsPolicy.Fail): ColumnWithPath<C>?

reverse

fun <T> DataColumn<T>.reverse(): DataColumn<T>

Returns a new DataColumn with the same values in reversed order, so the last value becomes the first one.

fun <T> DataFrame<T>.reverse(): DataFrame<T>

Returns a new DataFrame with the same rows in reversed order, so the last row becomes the first one.

fun <T> ColumnGroup<T>.reverse(): ColumnGroup<T>

Returns a new ColumnGroup with the same rows in reversed order, so the last row becomes the first one.

rightJoin

fun <A, B> DataFrame<A>.rightJoin(other: DataFrame, selector: JoinColumnsSelector<A, B>? = null): DataFrame<A>

fun <A, B> DataFrame<A>.rightJoin(other: DataFrame, vararg columns: String): DataFrame<A>

Performs a right join of this DataFrame with the other DataFrame using the selected key columns. Includes all rows from the right DataFrame; matching rows are merged, unmatched left-side values are filled with null.

rightJoinWith

fun <A, B> DataFrame<A>.rightJoinWith(right: DataFrame, joinExpression: JoinExpression<A, B>): DataFrame<A>

Performs a right join of this DataFrame with the right DataFrame using the provided joinExpression. Includes all rows from the right DataFrame; matching rows are merged, unmatched left-side values are filled with null.

rows

fun <T> DataFrame<T>.rows(): Iterable<DataRow<T>>

rowsCount

open override fun rowsCount(): Int

Returns the total number of rows of this DataFrame.

rowsReversed

fun <T> DataFrame<T>.rowsReversed(): Iterable<DataRow<T>>

scale

internal fun <T : Number> DataColumn<T?>.scale(): Int

schema

fun DataFrame<*>.schema(): DataFrameSchema

Returns the runtime DataFrameSchema of this DataFrame, read from the columns it holds.

select

fun <T> DataFrame<T>.select(columns: ColumnsSelector<T, *>): DataFrame<T>

fun <T> DataFrame<T>.select(vararg columns: String): DataFrame<T>

fun <T> DataFrame<T>.~~select~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~select~~(vararg columns: ColumnReference<*>): DataFrame<T>

Returns a new DataFrame with only the columns selected by columns.

selectInternal

internal fun <C, R> SingleColumn<DataRow<C>>.selectInternal(selector: ColumnsSelector<C, R>): ColumnSet<R>

setNullable

fun DataColumn<*>.setNullable(nullable: Boolean): DataColumn<*>

shortPath

internal fun ColumnReference<*>.shortPath(): ColumnPath

shuffle

fun <T> DataColumn<T>.shuffle(): DataColumn<T>

Returns a new DataColumn with values in random order using the default randomness.

fun <T> DataFrame<T>.shuffle(): DataFrame<T>

Returns a new DataFrame with rows in random order using the default randomness.

fun <T> DataColumn<T>.shuffle(random: Random): DataColumn<T>

Returns a new DataColumn with the same values in random order using the provided random source.

fun <T> DataFrame<T>.shuffle(random: Random): DataFrame<T>

Returns a new DataFrame with rows reordered randomly using the provided random source.

simplifyInternal

internal fun ColumnsResolver<*>.simplifyInternal(): ColumnSet<*>

Simplifies structure by removing columns that are already present in column groups in this.

single

fun <C> DataColumn<C>.single(): C

Returns the single value in this DataColumn.

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

Returns the single row in this DataFrame.

inline fun <T> DataFrame<T>.single(predicate: RowFilter<T>): DataRow<T>

Returns the single row in this DataFrame that satisfies the given predicate.

singleImpl

internal fun <T> ColumnsResolver<T>.singleImpl(): SingleColumn<T>

Converts this ColumnsResolver to a SingleColumn. resolveSingle will return the single column of this if there is only one, else it will throw an exception: In case of an empty ColumnsResolver, a NoSuchElementException will be thrown. In case of more than one column, an IllegalArgumentException will be thrown. If the result is used as a ColumnSet, null will be converted to an empty list.

singleInternal

internal fun <C> ColumnsResolver<C>.singleInternal(condition: ColumnFilter<C> = { true }): TransformableSingleColumn<C>

singleOrNull

fun <T> DataFrame<T>.singleOrNull(): DataRow<T>?

Returns the single row in this DataFrame. Returns null if the DataFrame contains no rows or contains more than one row.

inline fun <T> DataFrame<T>.singleOrNull(predicate: RowFilter<T>): DataRow<T>?

Returns the single row in this DataFrame that satisfies the given predicate. Returns null if the DataFrame contains no rows matching the predicate (including the case when the DataFrame is empty) or contains more than one row matching the predicate.

singleOrNullImpl

internal fun <T> ColumnsResolver<T>.singleOrNullImpl(): SingleColumn<T>

Converts this ColumnsResolver to a SingleColumn. resolveSingle will return the single column of this if there is only one, else it will return null. If the result used as a ColumnSet, null will be converted to an empty list.

size

open override fun size(): Int

size

fun AnyFrame.size(): DataFrameSize

sort

fun <T : Comparable<T>> DataColumn<T>.sort(): ValueColumn<T>

Sorts the values in this column in ascending order.

sortBy

fun <T, C> DataFrame<T>.sortBy(columns: SortColumnsSelector<T, C>): DataFrame<T>

Sorts this DataFrame rows by the specified columns in ascending (default) or descending order.

fun <T> DataFrame<T>.sortBy(vararg cols: String): DataFrame<T>

Sorts this DataFrame rows by the specified columns in ascending order.

fun <T> DataFrame<T>.~~sortBy~~(vararg cols: KProperty<Comparable<*>?>): DataFrame<T>

fun <T> DataFrame<T>.~~sortBy~~(vararg cols: ColumnReference<*>): DataFrame<T>

sortByDesc

fun <T, C> DataFrame<T>.sortByDesc(columns: SortColumnsSelector<T, C>): DataFrame<T>

Sorts this DataFrame rows by the specified columns in ascending or descending (default) order.

fun <T> DataFrame<T>.sortByDesc(vararg columns: String): DataFrame<T>

Sorts this DataFrame rows by the specified columns in descending order.

fun <T, C> DataFrame<T>.~~sortByDesc~~(vararg columns: KProperty<Comparable<C>?>): DataFrame<T>

fun <T> DataFrame<T>.~~sortByDesc~~(vararg columns: ColumnReference<*>): DataFrame<T>

sortByImpl

internal fun <T, C> DataFrame<T>.sortByImpl(unresolvedColumnsPolicy: UnresolvedColumnsPolicy = UnresolvedColumnsPolicy.Fail, columns: SortColumnsSelector<T, C>): DataFrame<T>

sortDesc

fun <T : Comparable<T>> DataColumn<T>.sortDesc(): ValueColumn<T>

Sorts the values in this column in descending order.

sortWith

fun <T> DataFrame<T>.sortWith(comparator: Comparator<DataRow<T>>): DataFrame<T>

fun <T> DataFrame<T>.sortWith(comparator: (DataRow<T>, DataRow<T>) -> Int): DataFrame<T>

Sorts the rows of this DataFrame using the specified row comparator.

split

fun <T, C> DataFrame<T>.split(columns: ColumnsSelector<T, C?>): Split<T, C>

fun <T> DataFrame<T>.split(vararg columns: String): Split<T, Any>

fun <T, C> DataFrame<T>.~~split~~(vararg columns: KProperty<C?>): Split<T, C>

fun <T, C> DataFrame<T>.~~split~~(vararg columns: ColumnReference<C?>): Split<T, C>

splitByIndices

internal fun <T> DataFrame<T>.splitByIndices(startIndices: Sequence<Int>): Sequence<DataFrame<T>>

splitInto

fun DataColumn<Iterable<*>>.splitInto(vararg names: String): DataFrame<*>

std

fun <T, C : Number?> DataFrame<T>.~~std~~(vararg columns: KProperty<C>): Double

fun <T, C : Number?> DataFrame<T>.~~std~~(vararg columns: ColumnReference<C>): Double

fun DataColumn<Number?>.std(skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault): Double

Returns the standard deviation of the values in this DataColumn, as a Double.

fun <T> DataFrame<T>.std(skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault): DataRow<T>

Returns the standard deviation of the values of each suitable column of this DataFrame separately.

fun <T> DataFrame<T>.std(skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault, columns: ColumnsSelector<T, Number?>): Double

fun <T> DataFrame<T>.std(vararg columns: String, skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault): Double

Returns a single standard deviation of all the values in the selected columns of this DataFrame, as a Double.

stdFor

fun <T, C : Number?> DataFrame<T>.stdFor(skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault, columns: ColumnsForAggregateSelector<T, C>): DataRow<T>

fun <T> DataFrame<T>.stdFor(vararg columns: String, skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault): DataRow<T>

Returns the standard deviation of the values of each selected column of this DataFrame separately.

fun <T, C : Number?> DataFrame<T>.~~stdFor~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault): DataRow<T>

fun <T, C : Number?> DataFrame<T>.~~stdFor~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault): DataRow<T>

stdOf

inline fun <T, reified R : Number?> DataColumn<T>.stdOf(skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault, noinline expression: (T) -> R): Double

Returns the standard deviation of the values that the given expression returns for each element of this DataColumn, as a Double.

inline fun <T, reified R : Number?> DataFrame<T>.stdOf(skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault, crossinline expression: RowExpression<T, R>): Double

Returns the standard deviation of the values that the given expression returns for each row of this DataFrame, as a Double.

sum

@JvmName(name = "sumByte")

fun DataColumn<Byte?>.sum(): Int

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

@JvmName(name = "sumShort")

fun DataColumn<Short?>.sum(): Int

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

@JvmName(name = "sumNumber")

fun <T : Number?> DataColumn<T>.sum(skipNaN: Boolean = skipNaNDefault): T & Any

Returns the sum of the values in this DataColumn.

fun <T> DataFrame<T>.sum(skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the sum of the values of each suitable column of this DataFrame separately.

@JvmName(name = "sumByte")

fun <T, C : Byte?> DataFrame<T>.sum(columns: ColumnsSelector<T, C>): Int

Returns a single sum of all the Byte values in the selected columns of this DataFrame, as an Int.

@JvmName(name = "sumShort")

fun <T, C : Short?> DataFrame<T>.sum(columns: ColumnsSelector<T, C>): Int

Returns a single sum of all the Short values in the selected columns of this DataFrame, as an Int.

@JvmName(name = "sumByte")

fun <T> DataFrame<T>.~~sum~~(vararg columns: KProperty<Byte?>): Int

@JvmName(name = "sumShort")

fun <T> DataFrame<T>.~~sum~~(vararg columns: KProperty<Short?>): Int

@JvmName(name = "sumByte")

fun <T, C : Byte?> DataFrame<T>.~~sum~~(vararg columns: ColumnReference<C>): Int

@JvmName(name = "sumShort")

fun <T, C : Short?> DataFrame<T>.~~sum~~(vararg columns: ColumnReference<C>): Int

@JvmName(name = "sumNumber")

fun <T, C : Number?> DataFrame<T>.~~sum~~(skipNaN: Boolean = skipNaNDefault, vararg columns: KProperty<C>): C & Any

@JvmName(name = "sumNumber")

fun <T, C : Number?> DataFrame<T>.~~sum~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): C & Any

@JvmName(name = "sumNumber")

fun <T, C : Number?> DataFrame<T>.sum(skipNaN: Boolean = skipNaNDefault, columns: ColumnsSelector<T, C>): C & Any

fun <T> DataFrame<T>.sum(vararg columns: String, skipNaN: Boolean = skipNaNDefault): Number

Returns a single sum of all the values in the selected columns of this DataFrame.

sumFor

fun <T, C : Number?> DataFrame<T>.sumFor(skipNaN: Boolean = skipNaNDefault, columns: ColumnsForAggregateSelector<T, C>): DataRow<T>

fun <T> DataFrame<T>.sumFor(vararg columns: String, skipNaN: Boolean = skipNaNDefault): DataRow<T>

Returns the sum of the values of each selected column of this DataFrame separately.

fun <T, C : Number?> DataFrame<T>.~~sumFor~~(vararg columns: KProperty<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

fun <T, C : Number?> DataFrame<T>.~~sumFor~~(vararg columns: ColumnReference<C>, skipNaN: Boolean = skipNaNDefault): DataRow<T>

sumOf

@JvmName(name = "sumOfByte")

inline fun <C, reified V : Byte?> DataColumn<C>.sumOf(crossinline expression: (C) -> V): Int

Returns the sum of the Byte values that the given expression returns for each element of this DataColumn, as an Int.

@JvmName(name = "sumOfShort")

inline fun <C, reified V : Short?> DataColumn<C>.sumOf(crossinline expression: (C) -> V): Int

Returns the sum of the Short values that the given expression returns for each element of this DataColumn, as an Int.

@JvmName(name = "sumOfByte")

inline fun <T, reified C : Byte?> DataFrame<T>.sumOf(crossinline expression: RowExpression<T, C>): Int

Returns the sum of the Byte values that the given expression returns for each row of this DataFrame, as an Int.

@JvmName(name = "sumOfShort")

inline fun <T, reified C : Short?> DataFrame<T>.sumOf(crossinline expression: RowExpression<T, C>): Int

Returns the sum of the Short values that the given expression returns for each row of this DataFrame, as an Int.

@JvmName(name = "sumOfNumber")

inline fun <C, reified V : Number?> DataColumn<C>.sumOf(skipNaN: Boolean = skipNaNDefault, crossinline expression: (C) -> V): V & Any

Returns the sum of the values that the given expression returns for each element of this DataColumn.

@JvmName(name = "sumOfNumber")

inline fun <T, reified C : Number?> DataFrame<T>.sumOf(skipNaN: Boolean = skipNaNDefault, crossinline expression: RowExpression<T, C>): C & Any

Returns the sum of the values that the given expression returns for each row of this DataFrame.

tail

fun <T> DataFrame<T>.tail(numRows: Int = 5): DataFrame<T>

Returns a DataFrame containing the last numRows rows.

take

fun <T> DataColumn<T>.take(n: Int): DataColumn<T>

Returns a DataColumn containing the first n values of this DataColumn.

fun <T> DataFrame<T>.take(n: Int): DataFrame<T>

Returns a DataFrame containing the first n rows.

takeLast

fun <T> DataColumn<T>.takeLast(n: Int = 1): DataColumn<T>

Returns a DataColumn containing the last n values of this DataColumn.

fun <T> DataFrame<T>.takeLast(n: Int = 1): DataFrame<T>

Returns a DataFrame containing the last n rows.

takeWhile

inline fun <T> DataFrame<T>.takeWhile(predicate: RowFilter<T>): DataFrame<T>

Returns a DataFrame containing the first rows that satisfy the given predicate.

times

operator fun DataColumn<BigDecimal>.times(value: BigDecimal): DataColumn<BigDecimal>

operator fun DataColumn<BigInteger>.times(value: BigInteger): DataColumn<BigInteger>

operator fun DataColumn<Double>.times(value: Double): DataColumn<Double>

@JvmName(name = "timesDouble")

operator fun DataColumn<Double>.times(value: Int): DataColumn<Double>

@JvmName(name = "timesIntNullable")

operator fun DataColumn<Int?>.times(value: Int): DataColumn<Int?>

@JvmName(name = "timesInt")

operator fun DataColumn<Int>.times(value: Double): DataColumn<Double>

operator fun DataColumn<Int>.times(value: Int): DataColumn<Int>

operator fun DataColumn<Long>.times(value: Long): DataColumn<Long>

Returns a DataColumn containing the results of multiplying each element of this DataColumn by value.

operator fun ColumnReference<Int>.times(value: Int): ColumnReference<Int>

Returns a ColumnReference containing the results of multiplying each element of this ColumnReference by value.

toByteArray

fun DataColumn<Number>.toByteArray(): ByteArray

toColumnAccessor

fun <T> ColumnReference<T>.toColumnAccessor(): ColumnAccessor<T>

toCsv

fun AnyFrame.~~toCsv~~(format: CSVFormat = CSVFormat.DEFAULT): String

toDataFrame

fun BaseColumn<*>.toDataFrame(): DataFrame<*>

toDataFrames

fun <T> DataColumn<List<List<T>>>.toDataFrames(containsColumns: Boolean = false): DataColumn<DataFrame<*>>

Converts a list of lists values in this DataColumn to DataFrame.

toDoubleArray

fun DataColumn<Number>.toDoubleArray(): DoubleArray

toFloatArray

fun DataColumn<Number>.toFloatArray(): FloatArray

toHTML

fun <T> DataFrame<T>.~~toHTML~~(configuration: DisplayConfiguration = DisplayConfiguration.DEFAULT, cellRenderer: CellRenderer = DefaultCellRenderer, getFooter: (DataFrame<T>) -> String? = { "DataFrame [${it.size}]" }): DataFrameHtmlData

toHtml

fun <T> DataFrame<T>.toHtml(configuration: DisplayConfiguration = DisplayConfiguration.DEFAULT, cellRenderer: CellRenderer = DefaultCellRenderer, getFooter: (DataFrame<T>) -> String? = { "DataFrame [${it.size}]" }): DataFrameHtmlData

Returns a DataFrameHtmlData without additional definitions. Can be rendered in Jupyter kernel (Kotlin Notebook) environments or other environments that already have CSS- and script definitions for DataFrame.

toHtmlData

internal fun AnyFrame.toHtmlData(defaultConfiguration: DisplayConfiguration = DisplayConfiguration.DEFAULT, cellRenderer: CellRenderer): DataFrameHtmlData

toIntArray

fun DataColumn<Number>.toIntArray(): IntArray

toList

open override fun toList(): List<DataRow<T>>

toList

inline fun <reified T> DataFrame<T>.toList(): List<T>

Converts this DataFrame into a List of T instances, where T is the type argument of this DataFrame.

toListOf

inline fun <reified T> DataFrame<*>.toListOf(): List<T>

Converts this DataFrame into a List of T instances, where T is given explicitly as the type argument of this call.

toLongArray

fun DataColumn<Number>.toLongArray(): LongArray

toMap

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

toSequence

inline fun <reified T> DataFrame<T>.toSequence(): Sequence<T>

Converts this DataFrame into a Sequence of T instances, where T is the type argument of this DataFrame.

toSequenceImpl

@PublishedApi

internal fun AnyFrame.toSequenceImpl(type: KType): Sequence<Any>

toSequenceOf

inline fun <reified T> DataFrame<*>.toSequenceOf(): Sequence<T>

Converts this DataFrame into a Sequence of T instances, where T is given explicitly as the type argument of this call.

toSet

open override fun toSet(): Set<DataRow<T>>

toShortArray

fun DataColumn<Number>.toShortArray(): ShortArray

toStandaloneHTML

fun <T> DataFrame<T>.~~toStandaloneHTML~~(configuration: DisplayConfiguration = DisplayConfiguration.DEFAULT, cellRenderer: CellRenderer = DefaultCellRenderer, getFooter: (DataFrame<T>) -> String? = { "DataFrame [${it.size}]" }): DataFrameHtmlData

toStandaloneHtml

fun <T> DataFrame<T>.toStandaloneHtml(configuration: DisplayConfiguration = DisplayConfiguration.DEFAULT, cellRenderer: CellRenderer = DefaultCellRenderer, getFooter: (DataFrame<T>) -> String? = { "DataFrame [${it.size}]" }): DataFrameHtmlData

Returns a DataFrameHtmlData with CSS- and script definitions for DataFrame.

toStaticHtml

fun AnyFrame.toStaticHtml(configuration: DisplayConfiguration = DisplayConfiguration.DEFAULT, cellRenderer: CellRenderer = DefaultCellRenderer, includeCss: Boolean = true, openNestedDfs: Boolean = false): DataFrameHtmlData

Renders this DataFrame as static HTML (meaning no JS is used). CSS rendering is enabled by default but can be turned off using includeCss

toString

open override fun toString(): String

toTypedArray

inline fun <reified T> DataColumn<T>.toTypedArray(): Array<T>

transform

@PublishedApi

internal inline fun <A, B> ColumnsResolver<A>.transform(crossinline converter: (List<ColumnWithPath<A>>) -> List<ColumnWithPath>): TransformableColumnSet

Applies a transformation on this by converting its List<ColumnWithPath<A>] to List<ColumnWithPath<B>] using converter.

transformSingle

internal fun <A, B> SingleColumn<A>.transformSingle(converter: (ColumnWithPath<A>) -> List<ColumnWithPath>): ColumnSet

Applies a transformation on this SingleColumn by converting its single ColumnWithPath<A> to List<ColumnWithPath<B>] using converter. Since converter allows you to return multiple columns, the result is turned into a ColumnSet<B>.

transformSingleWithContext

internal fun <A, B> SingleColumn<A>.transformSingleWithContext(converter: ColumnResolutionContext.(ColumnWithPath<A>) -> List<ColumnWithPath>): ColumnSet

Applies a transformation on this SingleColumn by converting its single ColumnWithPath<A> to List<ColumnWithPath<B>] using converter but also providing the ColumnResolutionContext to the converter.

transformWithContext

internal fun <A, B> ColumnsResolver<A>.transformWithContext(converter: ColumnResolutionContext.(List<ColumnWithPath<A>>) -> List<ColumnWithPath>): TransformableColumnSet

Applies a transformation on this by converting its List<ColumnWithPath<A>] to List<ColumnWithPath<B>] using converter, but also providing the ColumnResolutionContext to the converter.

tryParse

@JvmName(name = "tryParseChar")

fun DataColumn<Char?>.tryParse(options: ParserOptions? = null): DataColumn<*>

Tries to parse a column of chars into a column of a different type. Each parser in Parsers is run in order until a valid parser is found, a.k.a. that parser was able to parse all values in the column successfully. If a parser fails to parse any value, the next parser is tried. If all the others fail, the final parser returns strings.

fun DataColumn<String?>.tryParse(options: ParserOptions? = null): DataColumn<*>

tryParseImpl

internal fun DataColumn<String?>.tryParseImpl(options: ParserOptions?): DataColumn<*>

type

open override fun type(): KType

unaryMinus

@JvmName(name = "unaryMinusBigDecimal")

operator fun DataColumn<BigDecimal>.unaryMinus(): DataColumn<BigDecimal>

@JvmName(name = "unaryMinusBigInteger")

operator fun DataColumn<BigInteger>.unaryMinus(): DataColumn<BigInteger>

@JvmName(name = "unaryMinusDouble")

operator fun DataColumn<Double>.unaryMinus(): DataColumn<Double>

@JvmName(name = "unaryMinusIntNullable")

operator fun DataColumn<Int?>.unaryMinus(): DataColumn<Int?>

operator fun DataColumn<Int>.unaryMinus(): DataColumn<Int>

@JvmName(name = "unaryMinusLong")

operator fun DataColumn<Long>.unaryMinus(): DataColumn<Long>

Returns a DataColumn containing negatives of the corresponding elements of this DataColumn.

operator fun ColumnReference<Int>.unaryMinus(): ColumnReference<Int>

Returns a ColumnReference containing negatives of the corresponding elements of this ColumnReference.

unbox

internal fun AnyBaseCol.unbox(): AnyCol

unfold

fun <T> DataFrame<T>.unfold(vararg columns: String): DataFrame<T>

fun <T> DataFrame<T>.unfold(vararg roots: KCallable<*>, maxDepth: Int = 0, columns: ColumnsSelector<T, *>): DataFrame<T>

Returns a new DataFrame in which the selected columns of objects are turned into ColumnGroups, with a column for every public property of these objects. The other columns and the order of the columns stay the same.

fun <T> DataFrame<T>.~~unfold~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~unfold~~(vararg columns: ColumnReference<*>): DataFrame<T>

inline fun <reified T> DataColumn<T>.unfold(vararg roots: KCallable<*>, maxDepth: Int = 0): DataColumn<*>

Returns a ColumnGroup made from the objects of this column, with a column for every public property of these objects, or this column itself when it cannot be unfolded.

unfoldImpl

@PublishedApi

internal fun <T> DataColumn<T>.unfoldImpl(type: KType, body: CreateDataFrameDsl<T>.() -> Unit): AnyCol

ungroup

fun <T, C> DataFrame<T>.ungroup(columns: ColumnsSelector<T, C>): DataFrame<T>

fun <T> DataFrame<T>.ungroup(vararg columns: String): DataFrame<T>

Ungroups the specified column groups within the DataFrame, i.e., replaces each ColumnGroup with its nested columns.

fun <T> DataFrame<T>.~~ungroup~~(vararg columns: KProperty<*>): DataFrame<T>

fun <T> DataFrame<T>.~~ungroup~~(vararg columns: ColumnReference<*>): DataFrame<T>

update

fun <T, C> DataFrame<T>.update(columns: ColumnsSelector<T, C>): Update<T, C>

fun <T> DataFrame<T>.update(vararg columns: String): Update<T, Any?>

fun <T, C> DataFrame<T>.~~update~~(vararg columns: KProperty<C>): Update<T, C>

fun <T, C> DataFrame<T>.~~update~~(vararg columns: ColumnReference<C>): Update<T, C>

fun <T> DataFrame<T>.update(firstCol: String, vararg cols: String, expression: UpdateExpression<T, Any?, Any?>): DataFrame<T>

fun <T, C> DataFrame<T>.~~update~~(firstCol: KProperty<C>, vararg cols: KProperty<C>, expression: UpdateExpression<T, C, C>): DataFrame<T>

fun <T, C> DataFrame<T>.~~update~~(firstCol: ColumnReference<C>, vararg cols: ColumnReference<C>, expression: UpdateExpression<T, C, C>): DataFrame<T>

Returns the DataFrame with changed values in some cells (column types cannot be changed).

updateImpl

internal fun <T, C> DataColumn<C>.updateImpl(df: DataFrame<T>, filter: RowValueFilter<T, C>?, expression: (AddDataRow<T>, DataColumn<C>, C) -> C?): DataColumn<C>

updateWith

internal fun <T> DataColumn<T>.updateWith(values: List<T>): DataColumn<T>

Replaces all values in the column asserting that new values are compatible with the current column kind.

uppercase

fun DataColumn<String?>.~~uppercase~~(): DataColumn<String?>

fun ColumnReference<String?>.~~uppercase~~(): ColumnReference<String?>

valueColumn

fun ColumnReference<DataRow<*>>.valueColumn(): ColumnDelegate<Any?>

fun ColumnReference<DataRow<*>>.valueColumn(name: String): ColumnAccessor<Any?>

fun <T> ColumnReference<DataRow<*>>.~~valueColumn~~(property: KProperty<T>): ColumnAccessor<T>

fun ColumnReference<DataRow<*>>.valueColumn(path: ColumnPath): ColumnAccessor<Any?>

valueColumnsInternal

internal inline fun ColumnsResolver<*>.valueColumnsInternal(crossinline filter: (ValueColumn<*>) -> Boolean): TransformableColumnSet<*>

Returns a TransformableColumnSet containing the value columns that satisfy the given filter.

valueCounts

fun <T> DataColumn<T>.valueCounts(sort: Boolean = true, ascending: Boolean = false, dropNA: Boolean = true, resultColumn: String = defaultCountColumnName): DataFrame<ValueCount>

Returns a DataFrame containing counts of unique values in this DataColumn.

fun <T> DataFrame<T>.valueCounts(sort: Boolean = true, ascending: Boolean = false, dropNA: Boolean = true, resultColumn: String = defaultCountColumnName, columns: ColumnsSelector<T, *>? = null): DataFrame<T>

fun <T> DataFrame<T>.valueCounts(vararg columns: String, sort: Boolean = true, ascending: Boolean = false, dropNA: Boolean = true, resultColumn: String = defaultCountColumnName): DataFrame<T>

Returns a DataFrame containing the counts of unique rows (or combinations of selected values) in this DataFrame.

fun <T> DataFrame<T>.~~valueCounts~~(vararg columns: KProperty<*>, sort: Boolean = true, ascending: Boolean = false, dropNA: Boolean = true, resultColumn: String = defaultCountColumnName): DataFrame<T>

fun <T> DataFrame<T>.~~valueCounts~~(vararg columns: ColumnReference<*>, sort: Boolean = true, ascending: Boolean = false, dropNA: Boolean = true, resultColumn: String = defaultCountColumnName): DataFrame<T>

values

open override fun values(): Iterable<DataRow<T>>

values

fun <T> DataFrame<T>.values(byRows: Boolean = false): Sequence<Any?>

fun <T, C> DataFrame<T>.values(byRow: Boolean = false, columns: ColumnsSelector<T, C>): Sequence<C>

valuesAreComparable

fun DataColumn<*>.valuesAreComparable(): Boolean

Returns true if this column is intra-comparable (mutually comparable), i.e., its values can be compared with each other and thus ordered.

valuesImpl

internal fun <T, C> DataFrame<T>.valuesImpl(byRow: Boolean, columns: ColumnsSelector<T, C>): Sequence<C>

valuesNotNull

fun <T> DataFrame<T>.valuesNotNull(byRow: Boolean = false): Sequence<Any>

fun <T, C> DataFrame<T>.valuesNotNull(byRow: Boolean = false, columns: ColumnsSelector<T, C?>): Sequence<C>

withDf

internal fun <T> ColumnGroup<*>.withDf(newDf: DataFrame<T>): ColumnGroup<T>

withValues

inline fun <reified T> ColumnReference<T>.~~withValues~~(values: Iterable<T>): ValueColumn<T>

inline fun <reified T> ColumnReference<T>.~~withValues~~(vararg values: T): ValueColumn<T>

writeCSV

fun AnyFrame.~~writeCSV~~(file: File, format: CSVFormat = CSVFormat.DEFAULT)

fun AnyFrame.~~writeCSV~~(writer: Appendable, format: CSVFormat = CSVFormat.DEFAULT)

fun AnyFrame.~~writeCSV~~(path: String, format: CSVFormat = CSVFormat.DEFAULT)

fun <T> DataFrame<T>.xs(vararg keyValues: Any?): DataFrame<T>

Returns a cross-section of this DataFrame: only the rows in which the key columns hold the given keyValues, without those key columns.

fun <T, C> DataFrame<T>.xs(vararg keyValues: C, keyColumns: ColumnsSelector<T, C>): DataFrame<T>

Returns a cross-section of this DataFrame: only the rows in which the key columns hold the given keyValues, without those key columns.

xsImpl

internal fun <T, C> DataFrame<T>.xsImpl(keyColumns: ColumnsSelector<T, C>, allowMissingColumns: Boolean, vararg keyValues: C): DataFrame<T>