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: Histogram plot for Series data
  
  >>> series.vgplot.hist()  # doctest: +SKIP
  
  Parameters
  ----------
  bins : integer, optional
      the maximum number of bins to use for the histogram (default: 10)
  alpha : float, optional
      transparency level, 0 <= alpha <= 1
  histtype : string, {'bar', 'step', 'stepfilled'}
      The type of histogram to generate. Default is 'bar'.
  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: ["Histogram","plot","for","Series","data",">",">",">","series.vgplot.hist","(",")","#","doctest",":","+SKIP","Parameters","--","--","--","--","--","bins",":","integer",",","optional","the","maximum","number","of","bins","to","use","for","the","histogram","(","default",":","10",")","alpha",":","float",",","optional","transparency","level",",","0","<","=","alpha","<","=","1","histtype",":","string",",","{","'bar","'",",","'step","'",",","'stepfilled","'","}","The","type","of","histogram","to","generate",".","Default","is","'bar","'",".","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 hist(
      self,
      bins=10,
      alpha=None,
      histtype="bar",
      width=450,
      height=300,
      ax=None,
      **kwds,
  ):
      """Histogram plot for Series data
  
      >>> series.vgplot.hist()  # doctest: +SKIP
  
      Parameters
      ----------
      bins : integer, optional
          the maximum number of bins to use for the histogram (default: 10)
      alpha : float, optional
          transparency level, 0 <= alpha <= 1
      histtype : string, {'bar', 'step', 'stepfilled'}
          The type of histogram to generate. Default is 'bar'.
      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
      """
      df = self._data.to_frame().reset_index(drop=False)
      df.columns = df.columns.astype(str)
      y, x = df.columns
  
      marks = {
          "bar": "bar",
          "barstacked": "bar",
          "stepfilled": {"type": "area", "interpolate": "step"},
          "step": {"type": "line", "interpolate": "step"},
      }
  
      if histtype in marks:
          mark = marks[histtype]
      else:
          raise ValueError(
              "histtype '{0}' is not recognized" "".format(histtype)
          )
  
      chart = self._plot(
          data=df,
          width=width,
          height=height,
          title=kwds.pop("title", ""),
          figsize=kwds.pop("figsize", None),
          dpi=kwds.pop("dpi", None),
      )
  
      chart.mark = mark
      chart = chart.encode(
          x=_x(x, df, bin={"maxbins": bins}),
          y=_y(y, df, aggregate="count"),
      )
  
      if alpha is not None:
          assert 0 <= alpha <= 1
          chart = chart.encode(opacity=alt.value(alpha))
  
      if ax is not None:
          return ax + chart
  
      warn_if_keywords_unused("hist", kwds)
      return chart
  
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 6 for calling the SeriesPlotMethods obj's underlying member method code with example usage: obj.hist(bins, alpha, histtype, width, height, ax) and returns: chart, unknown