Geocoding Creative Commons License #

Administrative Levels#

Country#

geocode_countries()

Example of geocoding with all countries

World countries

Example of geocoding of countries: Canada

Canada

Example of geocoding of countries: India

India

State#

geocode_states()

Example of geocoding of states: United States

US states

Example of geocoding of states: Australia

Australia states

Example of geocoding of states: Russia

Russia states

County#

geocode_counties()

Example of geocoding of counties: United States

US counties

Example of geocoding of counties: Italy

Italy counties

Example of geocoding of counties: Poland

Poland counties

City#

geocode_cities()

Example of geocoding of cities: New York City

New York

Example of geocoding of cities: Helsinki

Helsinki

Example of geocoding of cities: London

London

Geometries#

Polygons#

geom_map(), geom_polygon()

Example of geocoding with map geometry: Brazil

Brazil

Example of geocoding with map geometry: Nigeria

Nigeria states

Example of geocoding with map geometry: Greece

Greece counties

Points#

geom_point()

Example of geocoding with point geometry: Kazakhstan

Kazakhstan state centroids

Example of geocoding with point geometry: Georgia

Georgia county centroids

Example of geocoding with point geometry: Greenland

Greenland cities

Rectangles#

geom_rect()

Example of geocoding with rectangle geometry: Japan

Japan bounding box with states

Example of geocoding with rectangle geometry: Ireland

Ireland county bounding boxes

Example of geocoding with rectangle geometry: Cuba

Cuba bounding box with cities

Guides to Geocoding#

Documentation: The Geocoding Reference Guide.

An example notebook covering various geocoding use-cases: geocoding_reference.ipynb.

Key Features#

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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.

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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.

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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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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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Customizable Tooltips and Annotations

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

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Formatting

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

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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.

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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.

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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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‘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.