code: def geom_text(
      mapping=None,
      *,
      data=None,
      stat=None,
      position=None,
      show_legend=None,
      sampling=None,
      tooltips=None,
      map=None,
      map_join=None,
      use_crs=None,
      label_format=None,
      na_text=None,
      nudge_x=None,
      nudge_y=None,
      color_by=None,
      **other_args,
  ):
      """
      Add a text directly to the plot.
  
      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 coordinates of points.
      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.
      label_format : str
          Format used to transform label mapping values to a string.
          Examples:
  
          - '.2f' -> '12.45'
          - 'Num {}' -> 'Num 12.456789'
          - 'TTL: {.2f}$' -> 'TTL: 12.45$'
  
          For more info see https://lets-plot.org/pages/formats.html.
      na_text : str, default='n/a'
          Text to show for missing values.
      nudge_x : float
          Horizontal adjustment to nudge labels by.
      nudge_y : float
          Vertical adjustment to nudge labels by.
      color_by : {'fill', 'color', 'paint_a', 'paint_b', 'paint_c'}, default='color'
          Define the color 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
      -----
      Adds text directly to the plot.
  
      `geom_text()` understands the following aesthetics mappings:
  
      - x : x-axis value.
      - y : y-axis value.
      - alpha : transparency level of a layer. Accept values between 0 and 1.
      - color (colour) : color of the geometry. 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 : font size.
      - label : text to add to plot.
      - family : font family. Possible values: 'sans', 'serif', 'mono', any other like: "Times New Roman". The default is 'sans'.
      - fontface : font style and weight. Possible values: 'plain', 'bold', 'italic', 'bold italic'. The default is 'plain'.
      - hjust : horizontal text alignment. Possible values: 'left', 'middle', 'right' or number between 0 ('left') and 1 ('right'). There are two special alignments: 'inward' (aligns text towards the plot center) and 'outward' (away from the plot center).
      - vjust : vertical text alignment. Possible values: 'bottom', 'center', 'top' or number between 0 ('bottom') and 1 ('top'). There are two special alignments: 'inward' (aligns text towards the plot center) and 'outward' (away from the plot center).
      - angle : text rotation angle in degrees.
      - lineheight : line height multiplier applied to the font size in the case of multi-line text.
  
      |
  
      The `data` and `map` parameters of `GeoDataFrame` type support shapes `Point` and `MultiPoint`.
  
      The `map` parameter of `Geocoder` type implicitly invokes `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']
  
      Examples
      --------
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 3
  
          from lets_plot import *
          LetsPlot.setup_html()
          ggplot() + geom_text(x=0, y=0, label='Lorem ipsum')
  
      |
  
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 10-11
  
          import numpy as np
          from lets_plot import *
          LetsPlot.setup_html()
          n = 10
          np.random.seed(42)
          x = np.arange(n)
          y = np.random.normal(loc=10, scale=2, size=n)
          ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + \\
              geom_bar(stat='identity', fill='#2b8cbe', tooltips='none') + \\
              geom_text(aes(label='y'), position=position_nudge(y=1), \\
                        label_format='.1f', angle=45, color='#2b8cbe')
  
      |
  
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 11-12
  
          from lets_plot import *
          from lets_plot.geo_data import *
          LetsPlot.setup_html()
          cities = ["New York", "Los Angeles"]
          states = ["NY", "CA"]
          titles = ['{0} ({1})'.format(city, state) \\
                    for city, state in zip(cities, states)]
          data = {"city": cities, "state": states, "title": titles}
          centroids = geocode_cities(data["city"]).get_centroids()
          ggplot(data) + geom_livemap(tiles=maptiles_lets_plot(theme='dark')) + \\
              geom_text(aes(label="title"), map=centroids, map_join="city", \\
                        size=7, color="yellow", fontface='bold')
  
      """
      return _geom(
          "text",
          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,
          label_format=label_format,
          na_text=na_text,
          nudge_x=nudge_x,
          nudge_y=nudge_y,
          color_by=color_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 41 for calling a global function with example usage: geom_text(mapping) and returns: _geom