Interop with Collections

Kotlin DataFrame and Kotlin Collection represent two different approaches to data storage:

DataFrame stores data by fields/columns
Collection stores data by records/rows

Although DataFrame doesn't implement the Collection or Iterable interface, it has many similar operations, such as filter, take, first, map, groupBy etc.

DataFrame has two-way compatibility with Map and List:

List<T>-> DataFrame<T>: toDataFrame
DataFrame<T>-> List<T>: toList
Map<String, List<*>>-> DataFrame<*>: toDataFrame
DataFrame<*>-> Map<String, List<*>>: toMap

Columns, rows, and values of DataFrame can be accessed as List, Iterable and Sequence accordingly:

df.columns() // List<DataColumn>
df.rows() // Iterable<DataRow>
df.values() // Sequence<Any?>

Interop with data classes

DataFrame can be used as an intermediate object for transformation from one data structure to another.

Assume you have a list of instances of some data class that you need to transform into some other format.

data class Input(val a: Int, val b: Int)

val list = listOf(Input(1, 2), Input(3, 4))

You can convert this list into DataFrame using toDataFrame() extension:

val df = list.toDataFrame()

Mark the original data class with DataSchema annotation to get extension properties and perform data transformations.

@DataSchema
data class Input(val a: Int, val b: Int)

val df2 = df.add("c") { a + b }

After your data is transformed, DataFrame instances can be exported eagerly into List of another data class using toList or toListOf extensions:

data class Output(val a: Int, val b: Int, val c: Int)

val result = df2.toListOf<Output>()

data class Output(val a: Int, val b: Int, val c: Int)

val result = df2.toListOf<Output>()

Alternatively, one can create lazy Sequence objects. This avoids holding the entire list of objects in memory as objects are created on the fly as needed.

val df = dataFrameOf("name", "lastName", "age")("John", "Doe", 21)
    .group("name", "lastName").into("fullName")

data class FullName(val name: String, val lastName: String)

data class Person(val fullName: FullName, val age: Int)

val persons = df.toListOf<Person>() // [Person(fullName = FullName(name = "John", lastName = "Doe"), age = 21)]

Converting columns with object instances to ColumnGroup

unfold can be used as toDataFrame() analogue for specific columns inside existing dataframes

22 August 2025