Dataframe 1.0 Help

Kotlin DataFrame Compiler Plugin

Kotlin DataFrame Compiler Plugin is a Kotlin compiler plugin that automatically generates
type-safe extension properties for your dataframes,
allowing you to access columns and row values in a type-safe way and avoid mistakes in column names.

Why use it?

  • Access columns as regular properties: df.name instead of df["name"].

  • Get full IDE and compiler support: autocompletion, refactoring, and type checking.

  • Improve code readability and safety when working with DataFrame.

Check out this video that shows how expressions update the schema of a dataframe:

Setup

Install IntelliJ IDEA EAP. Going forward, compiler plugin updates will be released with Kotlin plugin updates. Next release: 2025.2

Setup plugins in build.gradle.kts:

kotlin("jvm") version "2.2.20-dev-3524"
kotlin("plugin.dataframe") version "2.2.20-dev-3524"

Setup library dependency:

implementation("org.jetbrains.kotlinx:dataframe:1.0.0-Beta2")

Plugin is released as a dev version, available in this maven repository:

maven("https://packages.jetbrains.team/maven/p/kt/dev/")

Setup repositories for dependencies in build.gradle.kts:

repositories { maven("https://packages.jetbrains.team/maven/p/kt/dev/") mavenCentral() }

Setup repositories for plugins in settings.gradle.kts

pluginManagement { repositories { maven("https://packages.jetbrains.team/maven/p/kt/dev/") mavenCentral() gradlePluginPortal() } }

Add this line to gradle.properties:

kotlin.incremental=false

Sync the project.

Disabling incremental compilation will no longer be necessary when https://youtrack.jetbrains.com/issue/KT-66735 is resolved.

Features overview

Static interpretation of DataFrame API

Plugin evaluates dataframe operations, given compile-time known arguments such as constant String, resolved types, property access calls. It updates the return type of the function call to provide properties that match column names and types. The goal is to reflect the result of operations you apply to dataframe in types and have convenient typed API

val weatherData = dataFrameOf( "time" to columnOf(0, 1, 2, 4, 5, 7, 8, 9), "temperature" to columnOf(12.0, 14.2, 15.1, 15.9, 17.9, 15.6, 14.2, 24.3), "humidity" to columnOf(0.5, 0.32, 0.11, 0.89, 0.68, 0.57, 0.56, 0.5) ) weatherData.filter { temperature > 15.0 }.print()

The schema of DataFrame, as the compiler plugin sees it, is displayed when you hover on an expression or variable:

image.png

@DataSchema declarations

Untyped DataFrame can be assigned a data schema - top-level interface or class that describes names and types of columns in the dataframe.

@DataSchema data class Repositories( @ColumnName("full_name") val fullName: String, @ColumnName("html_url") val htmlUrl: java.net.URL, @ColumnName("stargazers_count") val stargazersCount: Int, val topics: String, val watchers: Int ) fun main() { val df = DataFrame .readCsv("https://raw.githubusercontent.com/Kotlin/dataframe/master/data/jetbrains_repositories.csv") .convertTo<Repositories>() df.filter { stargazersCount > 50 }.print() }

Learn more about data schema declarations

Examples

16 June 2025