Maps

Create beautiful maps just by adding an interactive basemap layer to your plot: geom_livemap().

Proportional Symbol Map

ggplot(data) + geom_livemap() + geom_point(aes(..))

Choropleth Map

ggplot(data) + geom_livemap() + geom_polygon(aes(..))

Combine Layers on Map ggplot2 Style

Quick Start

Quick start guide to maps.

Primitives

point, pie, path, tiles, polygon, map, horizontal line, vertical line, rectangle, segment, curve, text, label, pointdensity.

Cookbooks:

• Geodesic option
• Controlling lines curvnes on a livemap with flat parameter

Contours

contour, filled contour.

Bivariate Distribution

2d bins, 2d hexagonal bins, 2d density, filled 2d density.

GeoPandas Shapes

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

Learn more: GeoPandas Support.

Use a Basemap That is Right for You

Use quality Lets-Plot vector basemaps or choose among many raster map tiles available through 3rd party providers.

Learn more: Configuring Basemap Tiles for Interactive Maps.

PyCharm

Create maps in PyCharm with the help of Lets-Plot in SciView plugin.

Example Notebooks

• Visualization of the Titanic's voyage
• Pushkin as a traveller
• Visualization of airport data on map
• Beijing housing prices on a map with spatial join
• Plotting Airbnb prices Boston
• Spatial prediction of soil pollutants with multi-output Gaussian processes
• COVID-19 in India: EDA and spatial visualization
• African cities density
• Visulizing spatial information - California housing
• Exploring Minard's 1812 plot with Lets-Plot
• Montenegrin independence referendum

Key Features

Inspired by ggplot2

A faithful port of R’s ggplot2 to Python.

You can learn R’s ggplot2 and the grammar of graphics in the “ggplot2: Elegant Graphics for Data Analysis” book by Hadley Wickham.

Multiplatform

A Grammar of Graphics for Python - works in Python notebooks (Jupyter, Datalore, Kaggle, Colab, Deepnote, Nextjournal) as well as in PyCharm and Intellij IDEA IDEs.

A Grammar of Graphics for Kotlin - a Kotlin multiplatform visualization library which fulfills your needs in the Kotlin ecosystem: from Kotlin notebooks to Compose-Multiplatform apps.

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.

Interactive Maps

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

‘bistro’ Plots

Ready-to-use compound plots - correlation matrices, Q-Q plots, joint plots, residual plots - that combine multiple geoms, scales, and settings into one call. Learn more.

Panning and Zooming

Enable an interactive toolbar with ggtb() to pan and zoom any chart - rubber-band zoom, center-point zoom, and pan tools. Learn more.

Customizable Tooltips and Annotations

You can customize the content, values formatting and appearance of tooltip and annotation for layers of your plot.

Formatting

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

Export to SVG, HTML, PNG and PDF

Use the ggsave() function to save your plot to a file. Alternatively, leverage the to_svg(), to_html(), to_png(), or to_pdf() methods of the plot object to save it to a file or an in-memory file-like object. Learn more.

Option to Display Plots in External Browser

With the “show externally” mode enabled, you can easily display a plot in an external browser by invoking its show() method. Learn more.

Sampling

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