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, label

Examples:

discrete-icon Discrete

bar, pie, lollipop, 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, dotplot, ydotplot, violin, ridgeline, frequency polygon

Examples:

marginal-icon Marginal Plots

ggmarginal

Examples:

visualization-of-errors-icon Visualization of Errors

crossbar, errorbar, linerange, pointrange

Examples:

smoothing-icon Smoothing

smoothing line

Examples:

bivariate-distribution-icon Bivariate Distribution

2d bins, 2d density, filled 2d density

Examples:

time_series-icon Time Series

scale_x_datetime(), scale_y_datetime(), scale_x_time(), scale_y_time()

Examples:

images-icon Images

geom_imshow(), matrix of images

Examples:

facets-icon Facets

facet_grid(), facet_wrap()

Examples:

coordinate-systems-icon Coordinate Systems

coord_cartesian(), coord_fixed(), coord_flip(), coord_map()

Examples:

bistro-icon ‘bistro’ Plots

Exploratory Data Analysis (EDA) is an open-ended, highly interactive, iterative process, whose actual steps are segments of a stubbily branching, tree-like pattern of possible actions.

Learn more about instruments for EDA in Lets-Plot: ‘bistro’ Plots.

geopandas-icon GeoPandas Shapes

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

Learn more: GeoPandas Support.

Examples:

grouping-plots-icon Grouping Plots

GGBunch and gggrid shows a collection of plots on one figure.

Examples:

presentation-options-icon Presentation Options

theme(), ggtitle(), ggsize(), xlab(), ylab(), labs(), guide_legend(), guide_colorbar()

Predefined themes:

minimal2, bw, grey, classic, light, minimal, none

https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/examples/cookbook/complete_themes.ipynb
https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/examples/cookbook/complete_themes.ipynb
https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/examples/cookbook/complete_themes.ipynb
https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/examples/cookbook/complete_themes.ipynb
https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/examples/cookbook/complete_themes.ipynb
https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/examples/cookbook/complete_themes.ipynb

Color schemes (flavors):

darcula, solarized light, solarized dark, high contrast light, high contrast dark

https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/examples/cookbook/theme_flavors.ipynb

Examples:

Cookbooks

Articles

Examples

Key Features

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ggplot2-like API

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

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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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Suitable for Scientist and Developer

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

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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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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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Sampling

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

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