code: def geom_rect(
      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 an axis-aligned rectangle defined by two corners.
  
      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.
      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`
          Bounding boxes of geometries will be drawn.
      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_rect()` draws rectangles.
  
      `geom_rect()` understands the following aesthetics mappings:
  
      - xmin : x-axis value.
      - xmax : x-axis value.
      - ymin : y-axis value.
      - ymax : y-axis value.
      - 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 : lines 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 `MultiPoint`, `Line`, `MultiLine`, `Polygon` and `MultiPolygon`.
  
      The `map` parameter of `Geocoder` type implicitly invokes `limits()` 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: 3
  
          from lets_plot import *
          LetsPlot.setup_html()
          ggplot() + geom_rect(xmin=-1, xmax=1, ymin=-1, ymax=1)
  
      |
  
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 16-18
  
          import numpy as np
          import pandas as pd
          from lets_plot import *
          LetsPlot.setup_html()
          n = 1000
          centers = {'a': (-2, -2), 'b': (3, 0), 'c': (0, 3)}
          np.random.seed(42)
          c = np.random.choice(list(centers.keys()), size=n)
          x = np.array([centers[k][0] for k in c]) + np.random.normal(size=n)
          y = np.array([centers[k][1] for k in c]) + np.random.normal(size=n)
          df = pd.DataFrame({'x': x, 'y': y, 'c': c}).sort_values(by='c')
          agg_df = df.groupby('c').agg({'x': ['min', 'max'], \\
                                        'y': ['min', 'max']}).reset_index()
          agg_df.columns = ['c', 'xmin', 'xmax', 'ymin', 'ymax']
          ggplot() + \\
              geom_rect(aes(xmin='xmin', xmax='xmax', ymin='ymin', \\
                            ymax='ymax', color='c', fill='c'), \\
                        data=agg_df, alpha=.2) + \\
              geom_point(aes(x='x', y='y', color='c'), data=df)
  
      |
  
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 7
  
          from lets_plot import *
          from lets_plot.geo_data import *
          LetsPlot.setup_html()
          geometry = geocode_countries("Kazakhstan").get_boundaries().iloc[0].geometry
          bbox = geometry.bounds
          ggplot() + geom_livemap() + \\
              geom_rect(xmin=bbox[0], ymin=bbox[1], xmax=bbox[2], ymax=bbox[3], alpha=.5)
  
      """
      return _geom(
          "rect",
          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 38 for calling a global function with example usage: geom_rect(mapping) and returns: _geom