code: def geom_map(
      mapping=None,
      *,
      data=None,
      stat=None,
      position=None,
      show_legend=None,
      sampling=None,
      tooltips=None,
      map=None,
      map_join=None,
      use_crs=None,
      color_by=None,
      fill_by=None,
      **other_args,
  ):
      """
      Display polygons from a reference map.
  
      Parameters
      ----------
      mapping : `FeatureSpec`
          Set of aesthetic mappings created by `aes()` function.
          Aesthetic mappings describe the way that variables in the data are
          mapped to plot "aesthetics".
      data : dict or Pandas or Polars `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.
      stat : str, default='identity'
          The statistical transformation to use on the data for this layer, as a string.
          Supported transformations: 'identity' (leaves the data unchanged),
          'count' (counts number of points with same x-axis coordinate),
          'bin' (counts number of points with x-axis coordinate in the same bin),
          'smooth' (performs smoothing - linear default),
          'density' (computes and draws kernel density estimate).
      position : str or `FeatureSpec`, default='identity'
          Position adjustment, either as a string ('identity', 'stack', 'dodge', ...),
          or the result of a call to a position adjustment function.
      show_legend : bool, default=True
          False - do not show legend for this layer.
      sampling : `FeatureSpec`
          Result of the call to the `sampling_xxx()` function.
          To prevent any sampling for this layer pass value "none" (string "none").
      tooltips : `layer_tooltips`
          Result of the call to the `layer_tooltips()` function.
          Specify appearance, style and content.
      map : `GeoDataFrame` or `Geocoder`
          Data containing region boundaries (coordinates of polygon vertices on map).
      map_join : str 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`.
      use_crs : str, optional, default="EPSG:4326" (aka WGS84)
          EPSG code of the coordinate reference system (CRS) or the keyword "provided".
          If an EPSG code is given, then all the coordinates in `GeoDataFrame` (see the `map` parameter)
          will be projected to this CRS.
          Specify "provided" to disable any further re-projection and to keep the `GeoDataFrame’s` original CRS.
      color_by : {'fill', 'color', 'paint_a', 'paint_b', 'paint_c'}, default='color'
          Define the color aesthetic for the geometry.
      fill_by : {'fill', 'color', 'paint_a', 'paint_b', 'paint_c'}, default='fill'
          Define the fill aesthetic for the geometry.
      other_args
          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.
  
      Returns
      -------
      `LayerSpec`
          Geom object specification.
  
      Notes
      -----
      `geom_map()` draws polygons which boundaries are specified by `map` parameter.
      Aesthetics of ploygons (`fill` etc.) are computed basing on input data and mapping
      (see `data` and `mapping` arguments).
  
      `geom_map()` understands the following aesthetics:
  
      - alpha : transparency level of a layer. Accept values between 0 and 1.
      - color (colour) : color of the geometry lines. String in the following formats: RGB/RGBA (e.g. "rgb(0, 0, 255)"); HEX (e.g. "#0000FF"); color name (e.g. "red"); role name ("pen", "paper" or "brush").
      - fill : fill color. String in the following formats: RGB/RGBA (e.g. "rgb(0, 0, 255)"); HEX (e.g. "#0000FF"); color name (e.g. "red"); role name ("pen", "paper" or "brush").
      - size : line width.
      - linetype : type of the line. Codes and names: 0 = 'blank', 1 = 'solid', 2 = 'dashed', 3 = 'dotted', 4 = 'dotdash', 5 = 'longdash', 6 = 'twodash'.
  
      |
  
      The `data` and `map` parameters of `GeoDataFrame` type support shapes `Polygon` and `MultiPolygon`.
  
      The `map` parameter of `Geocoder` type implicitly invokes `boundaries()` 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']
  
      Examples
      --------
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 5
  
          from lets_plot import *
          from lets_plot.geo_data import *
          LetsPlot.setup_html()
          country = geocode_countries('Italy').get_boundaries(resolution=6)
          ggplot() + geom_map(data=country)
  
      |
  
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 8-11
  
          from lets_plot import *
          from lets_plot.geo_data import *
          LetsPlot.setup_html()
          data = {'city': ['New York', 'Philadelphia'], \\
                  'est_pop_2019': [8_336_817, 1_584_064]}
          boundaries = geocode_cities(data['city']).get_boundaries()
          ggplot() + \\
              geom_map(aes(color='city', fill='city'), data=data, map=boundaries, \\
                       map_join='city', size=.5, alpha=.3, \\
                       tooltips=layer_tooltips().line('@city')\\
                                                .line('population|@est_pop_2019'))
  
      |
  
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 8-11
  
          from lets_plot import *
          from lets_plot.geo_data import *
          LetsPlot.setup_html()
          data = {"city": ["New York", "Philadelphia"], \\
                  "est_pop_2019": [8_336_817, 1_584_064]}
          boundaries = geocode_cities(data["city"]).inc_res().get_boundaries()
          ggplot() + geom_livemap() + \\
              geom_map(aes(color="city", fill="city"), data=data, map=boundaries, \\
                       map_join="city", alpha=.2, \\
                       tooltips=layer_tooltips().title('@city')\\
                                                .line('population|@est_pop_2019'))
  
      """
      return _geom(
          "map",
          mapping=mapping,
          data=data,
          stat=stat,
          position=position,
          show_legend=show_legend,
          sampling=sampling,
          tooltips=tooltips,
          map=map,
          map_join=map_join,
          use_crs=use_crs,
          color_by=color_by,
          fill_by=fill_by,
          **other_args,
      )
  
imports: from lets_plot.geo_data_internals.utils import is_geocoder
  from .core import FeatureSpec, LayerSpec
  from .util import as_annotated_data, is_geo_data_frame, geo_data_frame_to_crs, get_geo_data_frame_meta
label_desc: Use image node_id 18 for calling a global function with example usage: geom_map(mapping) and returns: _geom