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 `scatter` plot visualizes your points as markers in 2D space. You can visualize
  one more dimension by using colors.
  
  The `scatter` plot is a good first way to plot data with non continuous axes.
  
  Reference: https://hvplot.holoviz.org/reference/pandas/scatter.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 or list, optional
      Field name(s) to draw y-positions from. If not specified, all numerical
      fields are used.
  marker : string, optional
      The marker shape specified above can be any supported by matplotlib, e.g. s, d, o etc.
      See https://matplotlib.org/stable/api/markers_api.html.
  c : string, optional
      A color or a Field name to draw the color of the marker from
  s : int, optional, also available as 'size'
      The size of the marker
  by : string, optional
      A single field or list of fields to group by. All the subgroups are visualized.
  groupby: string, list, optional
      A single field or list of fields to group and filter by. Adds one or more widgets to
      select the subgroup(s) to visualize.
  scale: number, optional
      Scaling factor to apply to point scaling.
  logz : bool
      Whether to apply log scaling to the z-axis. Default is False.
  color : str or array-like, optional.
      The color for each of the series. Possible values are:
  
      A single color string referred to by name, RGB or RGBA code, for instance 'red' or
      '#a98d19.
  
      A sequence of color strings referred to by name, RGB or RGBA code, which will be used
      for each series recursively. For instance ['green','yellow'] each field’s line will be
      filled in green or yellow, alternatively. If there is only a single series to be
      plotted, then only the first color from the color list will be used.
  **kwds : optional
      Additional keywords arguments are documented in `hvplot.help('scatter')`.
  
  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"],
          },
      )
      scatter = df.hvplot.scatter(
          x="numerical",
          y=["actual", "forecast"],
          ylabel="value",
          legend="bottom",
          height=500,
          color=["#f16a6f", "#1e85f7"],
          size=100,
      )
      scatter
  
  You can overlay the `scatter` markers on for example a `line` plot
  
  .. code-block::
  
      line = df.hvplot.line(
          x="numerical", y=["actual", "forecast"], color=["#f16a6f", "#1e85f7"], line_width=5
      )
      scatter * line
  
  References
  ----------
  
  - Bokeh: https://docs.bokeh.org/en/latest/docs/user_guide/plotting.html#scatter-markers
  - HoloViews: https://holoviews.org/reference/elements/matplotlib/Scatter.html
  - Pandas: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.scatter.html
  - Plotly: https://plotly.com/python/line-and-scatter/
  - Matplotlib:  https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.scatter.html
  - Seaborn: https://seaborn.pydata.org/generated/seaborn.scatterplot.html
  - Wiki: https://en.wikipedia.org/wiki/Scatter_plot
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otlib.pyplot.scatter.html","-","Seaborn",":","https",":","\/\/seaborn.pydata.org\/generated\/seaborn.scatterplot.html","-","Wiki",":","https",":","\/\/en.wikipedia.org\/wiki\/Scatter_plot"]
code: def scatter(self, x=None, y=None, **kwds):
      """
      The `scatter` plot visualizes your points as markers in 2D space. You can visualize
      one more dimension by using colors.
  
      The `scatter` plot is a good first way to plot data with non continuous axes.
  
      Reference: https://hvplot.holoviz.org/reference/pandas/scatter.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 or list, optional
          Field name(s) to draw y-positions from. If not specified, all numerical
          fields are used.
      marker : string, optional
          The marker shape specified above can be any supported by matplotlib, e.g. s, d, o etc.
          See https://matplotlib.org/stable/api/markers_api.html.
      c : string, optional
          A color or a Field name to draw the color of the marker from
      s : int, optional, also available as 'size'
          The size of the marker
      by : string, optional
          A single field or list of fields to group by. All the subgroups are visualized.
      groupby: string, list, optional
          A single field or list of fields to group and filter by. Adds one or more widgets to
          select the subgroup(s) to visualize.
      scale: number, optional
          Scaling factor to apply to point scaling.
      logz : bool
          Whether to apply log scaling to the z-axis. Default is False.
      color : str or array-like, optional.
          The color for each of the series. Possible values are:
  
          A single color string referred to by name, RGB or RGBA code, for instance 'red' or
          '#a98d19.
  
          A sequence of color strings referred to by name, RGB or RGBA code, which will be used
          for each series recursively. For instance ['green','yellow'] each field’s line will be
          filled in green or yellow, alternatively. If there is only a single series to be
          plotted, then only the first color from the color list will be used.
      **kwds : optional
          Additional keywords arguments are documented in `hvplot.help('scatter')`.
  
      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"],
              },
          )
          scatter = df.hvplot.scatter(
              x="numerical",
              y=["actual", "forecast"],
              ylabel="value",
              legend="bottom",
              height=500,
              color=["#f16a6f", "#1e85f7"],
              size=100,
          )
          scatter
  
      You can overlay the `scatter` markers on for example a `line` plot
  
      .. code-block::
  
          line = df.hvplot.line(
              x="numerical", y=["actual", "forecast"], color=["#f16a6f", "#1e85f7"], line_width=5
          )
          scatter * line
  
      References
      ----------
  
      - Bokeh: https://docs.bokeh.org/en/latest/docs/user_guide/plotting.html#scatter-markers
      - HoloViews: https://holoviews.org/reference/elements/matplotlib/Scatter.html
      - Pandas: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.scatter.html
      - Plotly: https://plotly.com/python/line-and-scatter/
      - Matplotlib:  https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.scatter.html
      - Seaborn: https://seaborn.pydata.org/generated/seaborn.scatterplot.html
      - Wiki: https://en.wikipedia.org/wiki/Scatter_plot
      """
      return self(x, y, kind="scatter", **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 3 for calling the hvPlotTabular obj's underlying member method code with example usage: obj.scatter(x, y) and returns: self