lets_plot.geom_livemap(mapping=None, *, data=None, show_legend=None, sampling=None, tooltips=None, map=None, map_join=None, symbol=None, location=None, zoom=None, projection=None, geodesic=None, tiles=None, **other_args)

Display an interactive map.


Set of aesthetic mappings created by aes() function. Aesthetic mappings describe the way that variables in the data are mapped to plot “aesthetics”.

datadict or DataFrame or GeoDataFrame

The data to be displayed in this layer. If None, the default, the data is inherited from the plot data as specified in the call to ggplot.

show_legend: bool, default=True

False - do not show legend for this layer.


Result of the call to the sampling_xxx() function. Value None (or ‘none’) will disable sampling for this layer.


Result of the call to the layer_tooltips() function. Specifies appearance, style and content.

mapGeoDataFrame or Geocoder

Data containing coordinates of points.

map_joinstr or list

Keys used to join map coordinates with data. First value in pair - column/columns in data. Second value in pair - column/columns in map.


The marker used for displaying the data. There are: ‘point’ for circles of different size and color; ‘pie’ for pie charts; ‘bar’ for bar charts.


Initial position of the map. If not set, displays the United States. There are [lon1, lat1, lon2, lat2,…, lonN, latN]: lon1, lon2,…, lonN are longitudes in degrees (positive in the Eastern hemisphere); lat1, lat2,…, latN are latitudes in degrees (positive in the Northern hemisphere).


Zoom of the map in the range 1 - 15.

projectionstr, default=’epsg3857’

The map projection. There are: ‘epsg3857’ for Mercator projection; ‘epsg4326’ for Equirectangular projection. projection only works with vector map tiles (i.e. Lets-Plot map tiles).

geodesicbool, default=True

Enables geodesic type of all paths and segments.


Tiles provider, either as a string - URL for a standard raster ZXY tile provider with {z}, {x} and {y} wildcards (e.g. ‘http://my.tile.com/{z}/{x}/{y}.png’) or the result of a call to a maptiles_xxx() functions.


Other arguments passed on to the layer. These are often aesthetics settings used to set an aesthetic to a fixed value, like color=’red’, fill=’blue’, size=3 or shape=21. They may also be parameters to the paired geom/stat.


Geom object specification.


geom_livemap() draws map, which can be moved and zoomed.

geom_livemap() understands the following aesthetics mappings:

  • alpha : transparency level of the point. Understands numbers between 0 and 1.

  • color (colour) : color of the geometry lines. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.

  • fill : color of a geometry internals. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.

  • size : radius for point, pie chart.

  • sym_x : value order for pie chart and bar chart.

  • sym_y : value specifying the sector size for pie chart and the heigth for bar chart.

The data and map parameters of GeoDataFrame type support shapes Point and MultiPoint.

The map parameter of Geocoder type implicitly invoke centroids() function.

The conventions for the values of map_join parameter are as follows.

  • Joining data and GeoDataFrame object

    Data has a column named ‘State_name’ and GeoDataFrame has a matching column named ‘state’:

    • map_join=[‘State_Name’, ‘state’]

    • map_join=[[‘State_Name’], [‘state’]]

  • Joining data and Geocoder object

    Data has a column named ‘State_name’. The matching key in Geocoder is always ‘state’ (providing it is a state-level geocoder) and can be omitted:

    • map_join=’State_Name’

    • map_join=[‘State_Name’]

  • Joining data by composite key

    Joining by composite key works like in examples above, but instead of using a string for a simple key you need to use an array of strings for a composite key. The names in the composite key must be in the same order as in the US street addresses convention: ‘city’, ‘county’, ‘state’, ‘country’. For example, the data has columns ‘State_name’ and ‘County_name’. Joining with a 2-keys county level Geocoder object (the Geocoder keys ‘county’ and ‘state’ are omitted in this case):

    • map_join=[‘County_name’, ‘State_Name’]


1from lets_plot import *
3ggplot() + geom_livemap()