class_docstr: Create plots for `PDPIsolate`
  
  Methods
  -------
  plot : generate the plot
  plot_matplotlib : plot using matplotlib
  plot_plotly : plot using plotly
class_docstr_tok: ["Create","plots","for","`","PDPIsolate","`","Methods","--","--","--","-","plot",":","generate","the","plot","plot_matplotlib",":","plot","using","matplotlib","plot_plotly",":","plot","using","plotly"]
code: def wrapup(self, title, line_axes, dist_axes=None):
      self._set_pdp_xticks(line_axes, is_line=True)
      _axes_modify(line_axes, self.plot_style)
  
      if self.plot_style.plot_pts_dist:
          self._set_pdp_xticks(dist_axes, is_line=False)
          _axes_modify(dist_axes, self.plot_style, grid=False)
  
      label, _ = self.get_axes_label()
      label_axes = dist_axes or line_axes
      label_axes.set_xlabel(
          label, fontdict=self.plot_style.label["fontdict"]
      )
  
      if len(self.plot_obj.target) > 1:
          line_axes.set_title(
              title,
              **self.plot_style.title["subplot_title"],
          )
  
imports: from .utils import _get_string, _to_rgba
  from .styles import _prepare_plot_style, _axes_modify, _display_percentile, _modify_legend_axes, _get_axes_label
  import pandas
  import numpy
  import matplotlib
  import matplotlib.pyplot
  from matplotlib.gridspec import GridSpecFromSubplotSpec
  import copy
  from mpl_toolkits.axes_grid1.inset_locator import inset_axes
  import plotly.graph_objects
  from sklearn.cluster import MiniBatchKMeans, KMeans
  from itertools import cycle
label_desc: Use image node_id 22 for calling the PDPIsolatePlotEngine obj's underlying member method code with example usage: obj.wrapup(title, line_axes, dist_axes) without return types