class_docstr: The plotting method: `df.hvplot(...)` creates a plot similarly to the familiar Pandas
  `df.plot` method.
  
  For more detailed options use a specific plotting method, e.g. `df.hvplot.line`.
  
  Reference: https://hvplot.holoviz.org/reference/index.html
  
  Parameters
  ----------
  x : string, optional
      Field name(s) to draw x-positions from. If not specified, the index is
      used.
  y : string or list, optional
      Field name(s) to draw y-positions from. If not specified, all numerical
      fields are used.
  kind : string, optional
      The kind of plot to generate, e.g. 'area', 'bar', 'line', 'scatter' etc. To see the
      available plots run `print(df.hvplot.__all__)`.
  **kwds : optional
      Additional keywords arguments are documented in `hvplot.help('scatter')` or similar
      depending on the kind of plot.
  
  Returns
  -------
  A Holoviews object. You can `print` the object to study its composition and run `hv.help` on
  the object to learn more about its parameters and options.
  
  Examples
  --------
  
  .. code-block::
  
      import hvplot.pandas
      import pandas as pd
  
      df = pd.DataFrame(
          {
              "actual": [100, 150, 125, 140, 145, 135, 123],
              "forecast": [90, 160, 125, 150, 141, 141, 120],
              "numerical": [1.1, 1.9, 3.2, 3.8, 4.3, 5.0, 5.5],
              "date": pd.date_range("2022-01-03", "2022-01-09"),
              "string": ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"],
          },
      )
      line = df.hvplot.line(
          x="numerical",
          y=["actual", "forecast"],
          ylabel="value",
          legend="bottom",
          height=500,
          color=["steelblue", "teal"],
          alpha=0.7,
          line_width=5,
      )
      line
  
  You can can add *markers* to a `line` plot by overlaying with a `scatter` plot.
  
  .. code-block::
  
      markers = df.hvplot.scatter(
          x="numerical", y=["actual", "forecast"], color=["#f16a6f", "#1e85f7"], size=50
      )
      line * markers
  
  Please note that you can pass widgets or reactive functions as arguments instead of
  literal values, c.f. https://hvplot.holoviz.org/user_guide/Widgets.html.
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docstr: Line contour plot
  
  Reference: https://hvplot.holoviz.org/reference/xarray/contour.html
  
  Parameters
  ----------
  x : string, optional
      The coordinate variable along the x-axis
  y : string, optional
      The coordinate variable along the y-axis
  z : string, optional
      The data variable to plot
  levels: int, optional
      The number of contour levels
  colorbar: boolean
      Whether to display a colorbar
  **kwds : optional
      Additional keywords arguments are documented in `hvplot.help('contour')`.
  
  Returns
  -------
  A Holoviews object. You can `print` the object to study its composition and run
  
  .. code-block::
  
      import holoviews as hv
      hv.help(the_holoviews_object)
  
  to learn more about its parameters and options.
  
  Examples
  --------
  
  .. code-block::
  
      import hvplot.xarray
      import xarray as xr
  
      ds = xr.tutorial.open_dataset("air_temperature")
      ds.hvplot.contour(
          geo=True,
          tiles="EsriImagery",
          z="air",
          x="lon",
          y="lat",
          levels=20,
          clabel="T [K]",
          line_width=2,
          label="Mean Air temperature [K]",
          cmap="reds",
      )
  
  References
  ----------
  
  - HoloViews: https://holoviews.org/reference/elements/bokeh/Contours.html
  - Matplotlib: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contour.html
  - Plotly: https://plotly.com/python/contour-plots/
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code: def contour(self, x=None, y=None, z=None, colorbar=True, **kwds):
      """
      Line contour plot
  
      Reference: https://hvplot.holoviz.org/reference/xarray/contour.html
  
      Parameters
      ----------
      x : string, optional
          The coordinate variable along the x-axis
      y : string, optional
          The coordinate variable along the y-axis
      z : string, optional
          The data variable to plot
      levels: int, optional
          The number of contour levels
      colorbar: boolean
          Whether to display a colorbar
      **kwds : optional
          Additional keywords arguments are documented in `hvplot.help('contour')`.
  
      Returns
      -------
      A Holoviews object. You can `print` the object to study its composition and run
  
      .. code-block::
  
          import holoviews as hv
          hv.help(the_holoviews_object)
  
      to learn more about its parameters and options.
  
      Examples
      --------
  
      .. code-block::
  
          import hvplot.xarray
          import xarray as xr
  
          ds = xr.tutorial.open_dataset("air_temperature")
          ds.hvplot.contour(
              geo=True,
              tiles="EsriImagery",
              z="air",
              x="lon",
              y="lat",
              levels=20,
              clabel="T [K]",
              line_width=2,
              label="Mean Air temperature [K]",
              cmap="reds",
          )
  
      References
      ----------
  
      - HoloViews: https://holoviews.org/reference/elements/bokeh/Contours.html
      - Matplotlib: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contour.html
      - Plotly: https://plotly.com/python/contour-plots/
      """
      return self(x, y, z=z, kind="contour", colorbar=colorbar, **kwds)
  
imports: import itertools
  from collections import defaultdict
  import param
  from ..converter import HoloViewsConverter
  from ..util import is_list_like, process_dynamic_args
label_desc: Use image node_id 4 for calling the hvPlot obj's underlying member method code with example usage: obj.contour(x, y, z, colorbar) and returns: self