Charts

basic-building-blocks-icon Basic Building Blocks

Points: points, jittered points

Lines: line, path, diagonal line, horizontal line, vertical line, segment, step-function

Areas: area, ribbon

Polygons: polygon, map

Tiles: tiles, rectangles, raster plot

Text: text

Examples:

discrete-icon Discrete

Bar, boxplot

Examples:

as_discrete-icon Ordering Categories, as_discrete()

as_discrete()

Learn more: Function as_discrete().

Examples:

contours-icon Contours

Contours, filled contours

Examples:

visualization-of-distribution-icon Visualization of Distribution

Histogram, density, frequency polygon

Examples:

visualization-of-errors-icon Visualization of Errors

Crossbar, errorbar, linerange, pointrange

Examples:

smoothing-icon Smoothing

Smoothing line

Examples:

bivariate-distribution-icon Bivariate Distribution

Heatmap of 2d bin counts, 2d density, filled 2d density

Examples:

images-icon Images

Image, matrix of images

Examples:

facets-icon Facets

facet_grid(), facet_wrap()

Examples:

correlation-plot-icon Correlation Plot

Correlation plot

Examples:

geopandas-icon GeoPandas Shapes

GeoPandas GeoDataFrame is supported by the following geometry layers: polygon, map, point, text, path, rect.

Learn more: GeoPandas Support.

presentation-options-icon Presentation Options

theme(), theme_none(), theme_classic(), theme_grey(), theme_light(), theme_minimal(), theme_minimal2(), ggtitle(), ggsize(), xlab(), ylab(), labs(), guide_legend(), guide_colorbar()

Examples:

Examples

Key Features

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ggplot2-like API

A bridge between R (ggplot2) and Python Data visualization.

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Grouping Plots

GGBunch shows a collection of plots on one figure. Each plot in the collection can have an arbitrary location and size.

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Suitable for Scientist and Developer

Works in computational notebooks (Jupyter, Datalore, Kaggle, Colab, Deepnote) and in JetBrains professional IDEs: PyCharm and DataSpell.

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Customizable Tooltips

You can customize the content, values formatting and appearance of tooltip for any geometry layer in your plot. Learn more.

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Kotlin API

R, Python, what’s next? Right. Lets-Plot Kotlin API enables data visualization in JVM and Kotlin/JS applications as well as in scientific notebooks like Jupyter and Datalore.

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Formatting

Lets-Plot supports formatting of numeric and date-time values in tooltips, legends, on the axes and text geometry layer. Learn more.

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Geospatial Visualization

Find spatial objects with the help of our powerful and easy to use Geocoding module. In case you already have GeoDataFrame on hand - plot it straight away.

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Sampling

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

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Interactive Maps

Interactive maps allow zooming and panning around your geospatial data with customizable vector or raster basemaps as a backdrop. Learn more.

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Export to SVG and HTML

The ggsave() function is an easy way to export plot to a file in SVG or HTML formats.

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‘No Javascript’ and Offline Mode

In the ‘no javascript’ mode Lets-Plot generates plots as bare-bones SVG images. Plots in the notebook with option offline=True will be working without an Internet connection. Learn more.