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Geometric object – a geometric object that represents a particular type of plot.Aesthetic mapping – describes how variables in the dataset are mapped to the visual properties of the layer, such as color, shape, size, or position.One plot can combine multiple different datasets (one per layer). Data – the set of data can be specified either once for all layers or on a layer-by-layer basis basis.The Layer is responsible for creating the objects painted on the ‘canvas’ and it contains the following elements: It can be built based on the default dataset with the aesthetics mappings, set of scales, or additional features applied. In Lets-Plot, the plot is represented by at least one layer.
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Using Kotlin? Make sure to check out this blog post to learn how to use Lets-Plot for visualizations in Kotlin. Try playing around with it in this quick start guide, or go straight to a complete Lets-Plot tutorial. If you have experience with the R language and ggplot2 API, then working with Lets-Plot will be especially familiar to you. After you create a notebook, just import the package and start creating interactive plots right away. The Lets-Plot library comes pre-installed in Datalore. Make sure that your Python version is 3.6 or higher and the iPython module is installed.
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The Lets-Plot library can be easily configured in SciView in P圜harm Professional edition, and comes already pre-installed in Datalore, the online Jupyter notebooks by JetBrains. Its architecture was inspired by the ggplot library for the R language, and is built with layered graphic principles in mind.īut what sets Lets-Plot apart from the well-known Matplotlib and Seaborn Python libraries? With Lets-Plot you can produce interactive visualizations, and do it with just a few lines of code.
The Lets-Plot library is an open-sourced interactive plotting library developed by JetBrains for Python and Kotlin.