convert

Returns DataFrame with changed values in some columns. Allows changing column types.

convert { columnsSelector }
    .with { rowExpression } | .asFrame { frameExpression } | .perRowCol { rowColExpression } | to<Type>() | to { colExpression }

rowExpression = DataRow.(OldValue) -> NewValue
rowColExpression = (DataRow, DataColumn) -> NewValue
colExpression = DataFrame.(DataColumn) -> DataColumn
frameExpression: DataFrame.(DataFrame) -> DataFrame

Related operations: Update / convert values, convertTo

See column selectors for how to select the columns for this operation and row expressions for how to provide new values.

df.convert { age }.with { it.toDouble() }
df.convert { colsAtAnyDepth().colsOf<String>() }.with { it.toCharArray().toList() }

df.weight.convertTo<Float?>()
df.age.convertToDouble()

ColumnGroup can be converted using DataFrame API, for example:

df.convert { name }.asFrame { it.add("fullName") { "$firstName $lastName" } }

Similar to replace with operation, columns can be converted in a compiler-plugin-friendly fashion whenever you need to perform an operation on the entire column without changing its name. For example, parallel reading.

df.convert { name }.asColumn { col ->
    col.toList().parallelStream().map { it.toString() }.collect(Collectors.toList()).toColumn()
}

df.convert {}.to<>() and col.convertTo<>() support automatic type conversions between the following types:

String, Char (uses parse to convert from String to other types)
Boolean
Byte
Short
Int (and Char)
Long
Float
Double (See parsing doubles for String to Double conversion)
BigDecimal (java.math)
BigInteger (java.math)
LocalDateTime (kotlinx.datetime and java.time)
LocalDate (kotlinx.datetime and java.time)
LocalTime (kotlinx.datetime and java.time)
Instant (kotlinx.datetime, kotlin.time, and java.time)
Duration (kotlin.time, and java.time, to/from Long, Int, String, and each other)
DateTimeComponents (kotlinx.datetime, to any other kotlinx-datetime/java.time type, Instant, or Long)
URL (java.net, to IMG or IFRAME)
enum classes (by name)

If you miss a type, or conversion, please let us know by creating a GitHub issue.

df.convert { age }.to<Double>()
df.convert { colsOf<Number>() }.to<String>()
df.convert { name.firstName and name.lastName }.asColumn { col -> col.map { it.length } }
df.convert { weight }.toFloat()

Notice the toFloat() call in the example above. This is a shortcut for to<Float>(). DataFrame has a handful of shortcuts like these

ParserOptions:

It is allowed to pass ParserOptions to conversion functions. This will only be used for String/Char conversions. See parse for more details.

For example:

// String -> Double? conversion
stringDf.convert { value }.to<Double?>(
    parserOptions = ParserOptions(locale = Locale.GERMAN, nullStrings = setOf("-")),
)

// String -> LocalDate conversion
stringDf.convert { date }.to<LocalDate>(
    parserOptions = ParserOptions(
        dateTime = DateTimeParserOptions.Kotlin.withFormat(LocalDate.Formats.ISO),
    ),
)
// shortcut for String -> LocalDate conversion
stringDf.convert { date }.toLocalDate(LocalDate.Formats.ISO)

Automatic conversion from String to enum classes is also supported:

enum class Direction { NORTH, SOUTH, WEST, EAST }

dataFrameOf("direction")("NORTH", "WEST")
    .convert("direction").to<Direction>()

And finally, Value classes can be used with convert too. Both as conversion source and target:

@JvmInline 
value class IntClass(val value: Int)

dataFrameOf("value")("1", "2") // note that values are strings; conversion is done automatically
    .convert("value").to<IntClass>()

05 May 2026