data-icon Data

Every layer may have some data associated with it. The “data” refers to a table of data where each row contains an observation and each column represents a variable that describes some property of each observation.

Data in this format is sometimes referred to as tidy data, flat data, primary data, atomic data, and unit record data.

You can pass tidy data to Lets-Plot in form of a Pandas Dataframe, a Polars Dataframe or just a dictionary: example notebook.

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


discrete-icon Discrete

bar, pie, lollipop, boxplot


as_discrete-icon Ordering Categories, as_discrete()


Learn more: Function as_discrete().


contours-icon Contours

contours, filled contours


visualization-of-distribution-icon Visualization of Distribution

histogram, density, dotplot, ydotplot, violin, ridgeline, frequency polygon


stats-icon Stats

stat_ecdf(), stat_summary(), stat_summary_bin()


function-icon Function



marginal-icon Marginal Plots


See also: Joint Plot, Residual Plot.


visualization-of-errors-icon Visualization of Errors

crossbar, errorbar, linerange, pointrange


smoothing-icon Smoothing

smoothing line


bivariate-distribution-icon Bivariate Distribution

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


time_series-icon Time Series

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


images-icon Images

geom_imshow(), matrix of images


facets-icon Facets

facet_grid(), facet_wrap()


coordinate-systems-icon Coordinate Systems

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


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.


grouping-plots-icon Grouping Plots

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


presentation-options-icon Presentation Options

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

Predefined themes:

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

Color schemes (flavors):

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





This book will walk you through the main tools and technics of data science in Python: importing, cleaning, transforming, and visualising data.

In the visualization chapter you will find easy to read and comprehencive guides to data visualization using the Lets-Plot.


Key Features


ggplot2-like API

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


Customizable Tooltips

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


Suitable for Scientist and Developer

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



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


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.



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


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.


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.


Interactive Maps

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


‘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.