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
  
  .. code-block::
  
      import holoviews as hv
      hv.help(the_holoviews_object)
  
  to learn more about its parameters and options.
  
  Examples
  --------
  
  .. code-block::
  
      import pandas as pd
      import hvplot.pandas
  
      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: The `area` plot can be used to color the area under a line or to color the space between two
  lines.
  
  Reference: https://hvplot.holoviz.org/reference/pandas/area.html
  
  Parameters
  ----------
  x : string, optional
      Field name(s) to draw x-positions from. If not specified, the index is
      used. Can refer to continuous and categorical data.
  y : string, optional
      Field name to draw the first y-position from
  y2 : string, optional
      Field name to draw the second y-position from
  stacked : boolean, optional
      Whether to stack multiple areas. Default is False.
  **kwds : optional
      Additional keywords arguments are documented in `hvplot.help('area')`.
  
  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.
  
  Example
  -------
  
  .. 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"],
          },
      )
      df["min"] = df[["actual", "forecast"]].min(axis=1)
      df["max"] = df[["actual", "forecast"]].max(axis=1)
  
      area = df.hvplot.area(
          x="numerical",
          y="min",
          y2="max",
          ylabel="value",
          legend="bottom",
          height=500,
          color=["#55a194"],
          alpha=0.7,
          line_width=2,
          ylim=(0, 200),
      )
      area
  
  References
  ----------
  
  - Bokeh: https://docs.bokeh.org/en/latest/docs/user_guide/plotting.html#directed-areas
  - HoloViews: https://holoviews.org/reference/elements/matplotlib/Area.html
  - Pandas: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.area.html
  - Plotly: https://plotly.com/python/filled-area-plots/
  - Matplotlib:  https://matplotlib.org/stable/gallery/lines_bars_and_markers/fill_between_demo.html
  - Wiki: https://en.wikipedia.org/wiki/Area_chart
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code: def area(self, x=None, y=None, y2=None, stacked=True, **kwds):
      """
      The `area` plot can be used to color the area under a line or to color the space between two
      lines.
  
      Reference: https://hvplot.holoviz.org/reference/pandas/area.html
  
      Parameters
      ----------
      x : string, optional
          Field name(s) to draw x-positions from. If not specified, the index is
          used. Can refer to continuous and categorical data.
      y : string, optional
          Field name to draw the first y-position from
      y2 : string, optional
          Field name to draw the second y-position from
      stacked : boolean, optional
          Whether to stack multiple areas. Default is False.
      **kwds : optional
          Additional keywords arguments are documented in `hvplot.help('area')`.
  
      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.
  
      Example
      -------
  
      .. 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"],
              },
          )
          df["min"] = df[["actual", "forecast"]].min(axis=1)
          df["max"] = df[["actual", "forecast"]].max(axis=1)
  
          area = df.hvplot.area(
              x="numerical",
              y="min",
              y2="max",
              ylabel="value",
              legend="bottom",
              height=500,
              color=["#55a194"],
              alpha=0.7,
              line_width=2,
              ylim=(0, 200),
          )
          area
  
      References
      ----------
  
      - Bokeh: https://docs.bokeh.org/en/latest/docs/user_guide/plotting.html#directed-areas
      - HoloViews: https://holoviews.org/reference/elements/matplotlib/Area.html
      - Pandas: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.area.html
      - Plotly: https://plotly.com/python/filled-area-plots/
      - Matplotlib:  https://matplotlib.org/stable/gallery/lines_bars_and_markers/fill_between_demo.html
      - Wiki: https://en.wikipedia.org/wiki/Area_chart
      """
      if "alpha" not in kwds and not stacked:
          kwds["alpha"] = 0.5
      return self(x, y, y2=y2, kind="area", stacked=stacked, **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 hvPlotTabular obj's underlying member method code with example usage: obj.area(x, y, y2, stacked) and returns: self