Lets-Plot is a multiplatform plotting library built on the principles of the Grammar of Graphics.

The library design is heavily influenced by Leland Wilkinson's work The Grammar of Graphics describing the deep features that underlie all statistical graphics.

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"

A bridge between R (ggplot2) and Python data visualization.
To learn more, see the documentation site at lets-plot.org/python.

Create plots in Kotlin Notebook, Datalore, Jupyter with Kotlin Kernel
or any other notebook that supports Kotlin Kernel.
To learn more, see the Lets-Plot Kotlin API project at GitHub.

Embed Lets-Plot charts in Compose Multiplatform applications.
To learn more, see the Lets-Plot Compose Frontend project at GitHub.

Embed Lets-Plot charts in JVM (Swing, JavaFX) and Kotlin/JS applications.
To learn more, see the Lets-Plot Kotlin API project at GitHub.

Kotlin API documentation site: lets-plot.org/kotlin.

Scientific mode in PyCharm and in IntelliJ IDEA provides support for interactive scientific computing and data visualization.

Lets-Plot in SciView plugin adds support for interactive plotting to IntelliJ-based IDEs with the Scientific mode enabled.

Note: The Scientific mode is NOT available in communinty editions of JetBrains IDEs.

Also read:

• Scientific mode in PyCharm
• Scientific mode in IntelliJ IDEA

• geom_pointdensity() Geometry

  

  See example notebook.

• Explicit group aesthetic now overrides default grouping behavior instead of combining with it

[!IMPORTANT] BREAKING CHANGE:

Previously, setting group='variable' would group by both the explicit variable AND any discrete aesthetics (color, shape, etc.).
Now it groups ONLY by the explicit variable, matching ggplot2 behavior.
Use group=[var1, var2, ...] to group by multiple variables explicitly,
and group=[] to disable any grouping.

See example notebook.

• gggrid(): support for shared legends (parameter guides)

  

  See example notebook.

• Better handling of missing values in geom_line(), geom_path(), geom_ribbon(), and geom_area()

  

  See example notebook.

• geom_histogram(): custom bin bounds (parameter breaks)

  See example notebook.

• Legend automatically wraps to prevent overlap — up to 15 rows for vertical legends and 5 columns for horizontal ones

  See example notebook.

• flavor_standard() resets the theme's default color scheme

  Use to override other flavors or make defaults explicit.

  See example notebook.

• 'left', 'right', 'top', and 'bottom' legend justification

  See example notebook.

• ggtb(): Added size_zoomin and size_basis parameters to control point size scaling behavior when zooming (works with geom_point and related layers).

  See: example notebook.

• And More

  See CHANGELOG.md for a full list of changes.

CHANGELOG.md

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Code and documentation released under the MIT license. Copyright © 2019-2025, JetBrains s.r.o.