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Kotlin API for Lets-Plot - an open-source plotting library for statistical data.

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Lets-Plot for Kotlin official JetBrains project

Latest Lets-Plot Kotlin API Version
Latest Lets-Plot Version


Lets-Plot for Kotlin is a Kotlin API for the Lets-Plot library - an open-source plotting library for statistical data which is written entirely in the Kotlin programming language.

Lets-Plot Kotlin API is built on the principals of layered graphics first described in the Leland Wilkinson work The Grammar of Graphics and later implemented in the ggplot2 package for R.

This grammar [...] is made up of a set of independent components that can be composed in many different ways. This makes [it] very powerful because you are not limited to a set of pre-specified graphics, but you can create new graphics that are precisely tailored for your problem. - Hadley Wickham, "ggplot2: Elegant Graphics for Data Analysis"

Read Lets-Plot Usage Guide for quick introduction to the Grammar of Graphics and Lets-Plot Kotlin API.

Lets-Plot in Jupyter with Kotlin Kernel


In Jupyter notebook with a Kotlin Kernel, Lets-Plot library is available out-of-the-box. To install Kotlin Kernel and OpenJDK into a Conda environment, run the following command:

shell script
conda install kotlin-jupyter-kernel -c jetbrains

For more information about Jupyter Kotlin kernel, see the Kotlin kernel for Jupyter/iPython project.

"Line Magics"

You can include all the necessary Lets-Plot boilerplate code to a notebook using the following "line magic":

%use lets-plot

This will apply the lets-plot
library descriptor
bundled with the Kotlin Jupyter Kernel installed in your environment.


line magic will force Kotlin Kernel to pull and apply the latest repository version of all
library descriptors

You can override lets-plot

library descriptor
settings using the lets-plot line magic parameters, like:
%use lets-plot(api=1.1.0, lib=1.5.4, js=1.5.4, isolatedFrame=false)

Where: -
- version of Lets-Plot Kotlin API. -
- version of Lets-Plot library (JAR-s). -
- version of Lets-PLot JavaScript bundle. -
- If
: load JS just once per notebook (default in Jupyter). If
: include Lets-Plot JS in each output (default in Datalore notebooks)

See: Line Magics documentation in the Kotlin Jupyter project for more details.

Quickstart in Jupyter

  • In Jupyter, create a new notebook and choose the Kotlin kernel (see the instructions for more details on how to select a kernel).

  • Add the following code to a Jupyter notebook:

    %use lets-plot
val rand = java.util.Random()
val data = mapOf(
    "rating" to List(200) { rand.nextGaussian() } + List(200) { rand.nextGaussian() * 1.5 + 1.5 },
    "cond" to List(200) { "A" } + List(200) { "B" }

var p = lets_plot(data) p += geom_density(color="dark_green", alpha=.3) {x="rating"; fill="cond"} p + ggsize(500, 250)

  • Execute the added code to evaluate the plotting capabilities of Lets-Plot.

Couldn't load quickstart.png

Example of notebooks

Try the following examples to study features of the



Lets-Plot-Kotlin in Datalore notebooks

Datalore is an online data science notebook by JetBrains.

In Datalore notebook you can run Kotlin code directly in your browser. Many popular Kotlin libraries are preinstalled and readily available (see the list of supported Kotlin libraries).

See Quickstart in Datalore example notebook to learn more about Kotlin support in Datalore.

Watch the Datalore Getting Started Tutorial video for a quick introduction to Datalore.

Lets-Plot in JVM-based application

Apart from Jupyter notebooks, Lets-Plot library and Kotlin API enables embedding plots into a JVM-based application.

See to learn more about creating plots in a JVM environment.

Lets-Plot Kotlin API

User guide and API reference

Data sampling

Sampling is a special technique of data transformation, which helps to deal with large datasets and overplotting.

Learn more: Data Sampling.


GGBunch allows to show a collection of plots on one figure. Each plot in the collection can have arbitrary location and size. There is no automatic layout inside the bunch.


Saving plot to a file


function is a convenient way of saving a plot or a GGBunch object to a file.

The supported export formats are:


For example, the code below will save plot as a PNG image to the file

%use lets-plot

val rand = java.util.Random(123) val n = 400 val data = mapOf ( "rating" to List(n/2) { rand.nextGaussian() } + List(n/2) { rand.nextGaussian() * 1.5 + 1.5 }, "cond" to List(n/2) { "A" } + List(n/2) { "B" } )

var p = lets_plot(data) + geom_density { x = "rating"; color = "cond" } + ggsize(500, 250)

ggsave(p, "density.png")

Couldn't load ggsave_demo.png


documentation for more information about the function arguments and default values.

Tooltip customization

You can customize the content of tooltips for the layer by using the parameter


Learn more: Tooltip Customization.

GeoTools support

GeoTools is an open source Java GIS Toolkit.

Lets-Plot supports visualization of a set of

-s stored in
, as well as individual

Learn more: GeoTools Support.

What is new in 1.2.0

  • Correlation plot builder.

Usage: ```kotlin import jetbrains.letsPlot.bistro.corr.CorrPlot

val plot = CorrPlot(data, title = "threshold = 0.5, no diag", threshold = 0.5) // data and optional parameters .points(type = "upper", diag = true) // Add one or more layers .build() // Finally, build the plot ```

Example: correlation_plot.ipynb

  • The
    plot layout utility

Arranges plots in cells of a regular grid.

Example: correlation_plot.ipynb

  • Tooltip Customization API
    • new options:
    • new option

See Tooltip Customization for details.

Example: tooltip_config.ipynb

Change Log



Code and documentation released under the MIT license. Copyright © 2019-2020, JetBrains s.r.o.

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