code: def _plot(
      cls,
      ax,
      y,
      style=None,
      bins=None,
      bottom=0,
      column_num=0,
      stacking_id=None,
      **kwds,
  ):
      if column_num == 0:
          cls._initialize_stacker(ax, stacking_id, len(bins) - 1)
  
      base = np.zeros(len(bins) - 1)
      bottom = bottom + cls._get_stacked_values(
          ax, stacking_id, base, kwds["label"]
      )
  
      # Since the counts were computed already, we use them as weights and just generate
      # one entry for each bin
      n, bins, patches = ax.hist(
          bins[:-1], bins=bins, bottom=bottom, weights=y, **kwds
      )
  
      cls._update_stacker(ax, stacking_id, n)
      return patches
  
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 4 for calling the PandasOnSparkHistPlot obj's underlying member method code with example usage: obj._plot(cls, ax, y, style, bins, bottom, column_num, stacking_id) and returns: patches