code: def _compute_plot_data(self):
      colname = self.data.name
      spark_column_name = self.data._internal.spark_column_name_for(
          self.data._column_label
      )
      data = self.data
  
      # Updates all props with the rc defaults from matplotlib
      self.kwds.update(PandasOnSparkBoxPlot.rc_defaults(**self.kwds))
  
      # Gets some important kwds
      showfliers = self.kwds.get("showfliers", False)
      whis = self.kwds.get("whis", 1.5)
      labels = self.kwds.get("labels", [colname])
  
      # This one is pandas-on-Spark specific to control precision for approx_percentile
      precision = self.kwds.get("precision", 0.01)
  
      # # Computes mean, median, Q1 and Q3 with approx_percentile and precision
      col_stats, col_fences = BoxPlotBase.compute_stats(
          data, spark_column_name, whis, precision
      )
  
      # # Creates a column to flag rows as outliers or not
      outliers = BoxPlotBase.outliers(
          data, spark_column_name, *col_fences
      )
  
      # # Computes min and max values of non-outliers - the whiskers
      whiskers = BoxPlotBase.calc_whiskers(spark_column_name, outliers)
  
      if showfliers:
          fliers = BoxPlotBase.get_fliers(
              spark_column_name, outliers, whiskers[0]
          )
      else:
          fliers = []
  
      # Builds bxpstats dict
      stats = []
      item = {
          "mean": col_stats["mean"],
          "med": col_stats["med"],
          "q1": col_stats["q1"],
          "q3": col_stats["q3"],
          "whislo": whiskers[0],
          "whishi": whiskers[1],
          "fliers": fliers,
          "label": labels[0],
      }
      stats.append(item)
  
      self.data = {labels[0]: stats}
  
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 3 for calling the PandasOnSparkBoxPlot obj's underlying member method code with example usage: obj._compute_plot_data() without return types