code: def geom_qq_line(
      mapping=None,
      *,
      data=None,
      stat=None,
      position=None,
      show_legend=None,
      sampling=None,
      tooltips=None,
      distribution=None,
      dparams=None,
      quantiles=None,
      color_by=None,
      **other_args,
  ):
      """
      Display quantile-quantile fitting line.
  
      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`
          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='qq_line'
          The statistical transformation to use on the data for this layer, as a string.
          Supported transformations: 'identity' (leaves the data unchanged),
          'qq_line' (compare two probability distributions),
          '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.
      distribution : {'norm', 'uniform', 't', 'gamma', 'exp', 'chi2'}, default='norm'
          Distribution function to use.
      dparams : list
          Additional parameters (of float type) passed on to distribution function.
          If `distribution` is `'norm'` then `dparams` is a pair [mean, std] (=[0.0, 1.0] by default).
          If `distribution` is `'uniform'` then `dparams` is a pair [a, b] (=[0.0, 1.0] by default).
          If `distribution` is `'t'` then `dparams` is an integer number [d] (=[1] by default).
          If `distribution` is `'gamma'` then `dparams` is a pair [alpha, beta] (=[1.0, 1.0] by default).
          If `distribution` is `'exp'` then `dparams` is a float number [lambda] (=[1.0] by default).
          If `distribution` is `'chi2'` then `dparams` is an integer number [k] (=[1] by default).
      quantiles : list, default=[0.25, 0.75]
          Pair of quantiles to use when fitting the Q-Q line.
      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
      -----
      The Q-Q line plot is used for comparing two probability distributions
      (sample and theoretical) by plotting line passed through the pair of corresponding quantiles.
  
      Computed variables:
  
      - ..theoretical.. : theoretical quantiles.
      - ..sample.. : sample quantiles.
  
      `geom_qq_line()` understands the following aesthetics mappings:
  
      - sample : 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").
      - linetype : type of the line. Codes and names: 0 = 'blank', 1 = 'solid', 2 = 'dashed', 3 = 'dotted', 4 = 'dotdash', 5 = 'longdash', 6 = 'twodash.
      - size : line width.
  
      Examples
      --------
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 7
  
          import numpy as np
          from lets_plot import *
          LetsPlot.setup_html()
          n = 100
          np.random.seed(42)
          sample = np.random.normal(0, 1, n)
          ggplot({'sample': sample}, aes(sample='sample')) + geom_qq() + geom_qq_line()
  
      |
  
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 9
  
          import numpy as np
          from lets_plot import *
          LetsPlot.setup_html()
          n = 100
          np.random.seed(42)
          sample = np.random.exponential(1, n)
          ggplot({'sample': sample}, aes(sample='sample')) + \\
              geom_qq(distribution='exp') + \\
              geom_qq_line(distribution='exp', quantiles=[0, 1])
  
      """
      return _geom(
          "qq_line",
          mapping=mapping,
          data=data,
          stat=stat,
          position=position,
          show_legend=show_legend,
          sampling=sampling,
          tooltips=tooltips,
          distribution=distribution,
          dparams=dparams,
          quantiles=quantiles,
          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 34 for calling a global function with example usage: geom_qq_line(mapping) and returns: _geom