class_docstr: Series/Frames plotting accessor and method.
  
  Uses the backend specified by the
  option ``plotting.backend``. By default, plotly is used.
  
  Plotting methods can also be accessed by calling the accessor as a method
  with the ``kind`` argument:
  ``s.plot(kind='hist')`` is equivalent to ``s.plot.hist()``
docstr: Draw a stacked area plot.
  
  An area plot displays quantitative data visually.
  This function wraps the plotly area function.
  
  Parameters
  ----------
  x : label or position, optional
      Coordinates for the X axis. By default it uses the index.
  y : label or position, optional
      Column to plot. By default it uses all columns.
  stacked : bool, default True
      Area plots are stacked by default. Set to False to create an
      unstacked plot (matplotlib-only).
  **kwds : optional
      Additional keyword arguments are documented in
      :meth:`DataFrame.plot`.
  
  Returns
  -------
  :class:`plotly.graph_objs.Figure`
      Return an custom object when ``backend!=plotly``.
      Return an ndarray when ``subplots=True`` (matplotlib-only).
  
  Examples
  --------
  
  For Series
  
  .. plotly::
  
      >>> df = ps.DataFrame({
      ...     'sales': [3, 2, 3, 9, 10, 6],
      ...     'signups': [5, 5, 6, 12, 14, 13],
      ...     'visits': [20, 42, 28, 62, 81, 50],
      ... }, index=pd.date_range(start='2018/01/01', end='2018/07/01',
      ...                        freq='M'))
      >>> df.sales.plot.area()  # doctest: +SKIP
  
  For DataFrame
  
  .. plotly::
  
      >>> df = ps.DataFrame({
      ...     'sales': [3, 2, 3, 9, 10, 6],
      ...     'signups': [5, 5, 6, 12, 14, 13],
      ...     'visits': [20, 42, 28, 62, 81, 50],
      ... }, index=pd.date_range(start='2018/01/01', end='2018/07/01',
      ...                        freq='M'))
      >>> df.plot.area()  # doctest: +SKIP
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code: def area(self, x=None, y=None, **kwds):
      """
      Draw a stacked area plot.
  
      An area plot displays quantitative data visually.
      This function wraps the plotly area function.
  
      Parameters
      ----------
      x : label or position, optional
          Coordinates for the X axis. By default it uses the index.
      y : label or position, optional
          Column to plot. By default it uses all columns.
      stacked : bool, default True
          Area plots are stacked by default. Set to False to create an
          unstacked plot (matplotlib-only).
      **kwds : optional
          Additional keyword arguments are documented in
          :meth:`DataFrame.plot`.
  
      Returns
      -------
      :class:`plotly.graph_objs.Figure`
          Return an custom object when ``backend!=plotly``.
          Return an ndarray when ``subplots=True`` (matplotlib-only).
  
      Examples
      --------
  
      For Series
  
      .. plotly::
  
          >>> df = ps.DataFrame({
          ...     'sales': [3, 2, 3, 9, 10, 6],
          ...     'signups': [5, 5, 6, 12, 14, 13],
          ...     'visits': [20, 42, 28, 62, 81, 50],
          ... }, index=pd.date_range(start='2018/01/01', end='2018/07/01',
          ...                        freq='M'))
          >>> df.sales.plot.area()  # doctest: +SKIP
  
      For DataFrame
  
      .. plotly::
  
          >>> df = ps.DataFrame({
          ...     'sales': [3, 2, 3, 9, 10, 6],
          ...     'signups': [5, 5, 6, 12, 14, 13],
          ...     'visits': [20, 42, 28, 62, 81, 50],
          ... }, index=pd.date_range(start='2018/01/01', end='2018/07/01',
          ...                        freq='M'))
          >>> df.plot.area()  # doctest: +SKIP
      """
      from pyspark.pandas import DataFrame, Series
  
      if isinstance(self.data, Series):
          return self(kind="area", **kwds)
      elif isinstance(self.data, DataFrame):
          return self(kind="area", x=x, y=y, **kwds)
  
imports: import importlib
  import pandas
  import numpy
  from pandas.core.base import PandasObject
  from pandas.core.dtypes.inference import is_integer
  from pyspark.ml.feature import Bucketizer
  from pyspark.mllib.stat import KernelDensity
  from pyspark.sql import functions
  from pyspark.pandas.missing import unsupported_function
  from pyspark.pandas.config import get_option
  from pyspark.pandas.utils import name_like_string
label_desc: Use image node_id 11 for calling the PandasOnSparkPlotAccessor obj's underlying member method code with example usage: obj.area(x, y) and returns: self, self