class_docstr: Series Accessor & Method for creating Vega-Lite visualizations.
  
  Examples
  --------
  >>> s.vgplot.line()  # doctest: +SKIP
  >>> s.vgplot.area()  # doctest: +SKIP
  >>> s.vgplot.bar()  # doctest: +SKIP
  >>> s.vgplot.barh()  # doctest: +SKIP
  >>> s.vgplot.hist()  # doctest: +SKIP
  >>> s.vgplot.kde()  # doctest: +SKIP
  >>> s.vgplot.density()  # doctest: +SKIP
  
  Plotting methods can also be accessed by calling the accessor as a method
  with the ``kind`` argument: ``s.vgplot(kind='line', **kwds)``
  is equivalent to ``s.vgplot.line(**kwds)``
docstr: Kernel Density Estimation plot for Series data
  
  >>> series.vgplot.kde()  # doctest: +SKIP
  
  Parameters
  ----------
  bw_method : str, scalar or callable, optional
      The method used to calculate the estimator bandwidth. This can be
      'scott', 'silverman', a scalar constant or a callable.
      See `scipy.stats.gaussian_kde` for more details.
  alpha : float, optional
      transparency level, 0 <= alpha <= 1
  width : int, optional
      the width of the plot in pixels
  height : int, optional
      the height of the plot in pixels
  ax: altair.Chart, optional
      chart to be overlayed with this vis (convinience method for `chart1 + chart2`)
  
  Returns
  -------
  chart : alt.Chart
      altair chart representation
docstr_tok: ["Kernel","Density","Estimation","plot","for","Series","data",">",">",">","series.vgplot.kde","(",")","#","doctest",":","+SKIP","Parameters","--","--","--","--","--","bw_method",":","str",",","scalar","or","callable",",","optional","The","method","used","to","calculate","the","estimator","bandwidth",".","This","can","be","'scott","'",",","'silverman","'",",","a","scalar","constant","or","a","callable",".","See","`","scipy.stats.gaussian_kde","`","for","more","details",".","alpha",":","float",",","optional","transparency","level",",","0","<","=","alpha","<","=","1","width",":","int",",","optional","the","width","of","the","plot","in","pixels","height",":","int",",","optional","the","height","of","the","plot","in","pixels","ax",":","altair.Chart",",","optional","chart","to","be","overlayed","with","this","vis","(","convinience","method","for","`","chart1","+","chart2","`",")","Returns","--","--","--","-","chart",":","alt.Chart","altair","chart","representation"]
code: def kde(
      self,
      bw_method=None,
      alpha=None,
      width=450,
      height=300,
      ax=None,
      **kwds,
  ):
      """Kernel Density Estimation plot for Series data
  
      >>> series.vgplot.kde()  # doctest: +SKIP
  
      Parameters
      ----------
      bw_method : str, scalar or callable, optional
          The method used to calculate the estimator bandwidth. This can be
          'scott', 'silverman', a scalar constant or a callable.
          See `scipy.stats.gaussian_kde` for more details.
      alpha : float, optional
          transparency level, 0 <= alpha <= 1
      width : int, optional
          the width of the plot in pixels
      height : int, optional
          the height of the plot in pixels
      ax: altair.Chart, optional
          chart to be overlayed with this vis (convinience method for `chart1 + chart2`)
  
      Returns
      -------
      chart : alt.Chart
          altair chart representation
      """
      from scipy.stats import gaussian_kde
  
      data = self._data
      tmin, tmax = data.min(), data.max()
      trange = tmax - tmin
      t = np.linspace(tmin - 0.5 * trange, tmax + 0.5 * trange, 1000)
  
      kde_ser = pd.Series(
          gaussian_kde(data, bw_method=bw_method).evaluate(t),
          index=t,
          name=data.name,
      )
  
      kde_ser.index.name = " "
      f = self.__class__(kde_ser)
      return f.line(
          alpha=alpha, width=width, height=height, ax=ax, **kwds
      )
  
imports: import numpy
  import pandas
  import altair
  from ._utils import infer_vegalite_type, unpivot_frame, warn_if_keywords_unused, validate_aggregation
  from ._pandas_internals import PandasObject, register_dataframe_accessor, register_series_accessor
label_desc: Use image node_id 7 for calling the SeriesPlotMethods obj's underlying member method code with example usage: obj.kde(bw_method, alpha, width, height, ax) and returns: f