code: def plot_series(
      data,
      kind="line",
      ax=None,  # Series unique
      figsize=None,
      use_index=True,
      title=None,
      grid=None,
      legend=False,
      style=None,
      logx=False,
      logy=False,
      loglog=False,
      xticks=None,
      yticks=None,
      xlim=None,
      ylim=None,
      rot=None,
      fontsize=None,
      colormap=None,
      table=False,
      yerr=None,
      xerr=None,
      label=None,
      secondary_y=False,  # Series unique
      **kwds,
  ):
      """
      Make plots of Series using matplotlib / pylab.
  
      Each plot kind has a corresponding method on the
      ``Series.plot`` accessor:
      ``s.plot(kind='line')`` is equivalent to
      ``s.plot.line()``.
  
      Parameters
      ----------
      data : Series
  
      kind : str
          - 'line' : line plot (default)
          - 'bar' : vertical bar plot
          - 'barh' : horizontal bar plot
          - 'hist' : histogram
          - 'box' : boxplot
          - 'kde' : Kernel Density Estimation plot
          - 'density' : same as 'kde'
          - 'area' : area plot
          - 'pie' : pie plot
  
      ax : matplotlib axes object
          If not passed, uses gca()
      figsize : a tuple (width, height) in inches
      use_index : boolean, default True
          Use index as ticks for x axis
      title : string or list
          Title to use for the plot. If a string is passed, print the string at
          the top of the figure. If a list is passed and `subplots` is True,
          print each item in the list above the corresponding subplot.
      grid : boolean, default None (matlab style default)
          Axis grid lines
      legend : False/True/'reverse'
          Place legend on axis subplots
      style : list or dict
          matplotlib line style per column
      logx : boolean, default False
          Use log scaling on x axis
      logy : boolean, default False
          Use log scaling on y axis
      loglog : boolean, default False
          Use log scaling on both x and y axes
      xticks : sequence
          Values to use for the xticks
      yticks : sequence
          Values to use for the yticks
      xlim : 2-tuple/list
      ylim : 2-tuple/list
      rot : int, default None
          Rotation for ticks (xticks for vertical, yticks for horizontal plots)
      fontsize : int, default None
          Font size for xticks and yticks
      colormap : str or matplotlib colormap object, default None
          Colormap to select colors from. If string, load colormap with that name
          from matplotlib.
      colorbar : boolean, optional
          If True, plot colorbar (only relevant for 'scatter' and 'hexbin' plots)
      position : float
          Specify relative alignments for bar plot layout.
          From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center)
      table : boolean, Series or DataFrame, default False
          If True, draw a table using the data in the DataFrame and the data will
          be transposed to meet matplotlib's default layout.
          If a Series or DataFrame is passed, use passed data to draw a table.
      yerr : DataFrame, Series, array-like, dict and str
          See :ref:`Plotting with Error Bars <visualization.errorbars>` for
          detail.
      xerr : same types as yerr.
      label : label argument to provide to plot
      secondary_y : boolean or sequence of ints, default False
          If True then y-axis will be on the right
      mark_right : boolean, default True
          When using a secondary_y axis, automatically mark the column
          labels with "(right)" in the legend
      **kwds : keywords
          Options to pass to matplotlib plotting method
  
      Returns
      -------
      axes : :class:`matplotlib.axes.Axes` or numpy.ndarray of them
  
      Notes
      -----
  
      - See matplotlib documentation online for more on this subject
      - If `kind` = 'bar' or 'barh', you can specify relative alignments
        for bar plot layout by `position` keyword.
        From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center)
      """
  
      # function copied from pandas.plotting._core
      # so it calls modified _plot below
  
      import matplotlib.pyplot as plt
  
      if ax is None and len(plt.get_fignums()) > 0:
          with plt.rc_context():
              ax = plt.gca()
          ax = PandasMPLPlot._get_ax_layer(ax)
      return _plot(
          data,
          kind=kind,
          ax=ax,
          figsize=figsize,
          use_index=use_index,
          title=title,
          grid=grid,
          legend=legend,
          style=style,
          logx=logx,
          logy=logy,
          loglog=loglog,
          xticks=xticks,
          yticks=yticks,
          xlim=xlim,
          ylim=ylim,
          rot=rot,
          fontsize=fontsize,
          colormap=colormap,
          table=table,
          yerr=yerr,
          xerr=xerr,
          label=label,
          secondary_y=secondary_y,
          **kwds,
      )
  
imports: from pyspark.loose_version import LooseVersion
  import matplotlib
  import numpy
  from matplotlib.axes._base import _process_plot_format
  from pandas.core.dtypes.inference import is_list_like
  from pandas.io.formats.printing import pprint_thing
  from pandas.plotting._matplotlib import BarPlot, BoxPlot, HistPlot, PiePlot, AreaPlot, LinePlot, BarhPlot, ScatterPlot, KdePlot
  from pandas.plotting._core import PlotAccessor
  from pandas.plotting._matplotlib.core import MPLPlot
  from pyspark.pandas.plot import TopNPlotBase, SampledPlotBase, HistogramPlotBase, BoxPlotBase, unsupported_function, KdePlotBase
label_desc: Use image node_id 2 for calling a global function with example usage: plot_series(data, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y) and returns: _plot